The business sector is a field which embraces technology. The sector is constantly in flux because one needs to make the most of novel opportunities to finish first. In such a competitive sector, certain skills are high in demand due to their wide range of applications, and SQL is one of them. And out of the various SQL Developers available, Oracle offers a powerful yet versatile platform suitable for SQL programming.
Structured Query Language - A Widely Accepted Programming Language!
SQL is called so because it uses queries as part of its code. Queries are commands used to manipulate data. Another salient feature of SQL is that it is a structured language, and all data is assumed in a tabular format. These features make it the perfect tool for business purposes, and it has found rising popularity in the same.
SQL Developer is the platform on which you can code, compile and execute various programs in SQL.
Oracle SQL Developer - A Robust Platform
Oracle SQL Developer is an IDE for programming in SQL on Oracle Databases. It is made available by the Oracle Corporation for free and is one of the most popular Relational Database Management Systems today.
Even though all such platforms use SQL, many differences make some better than the other. SQL itself comes in different types, so these programs are diverse in their capabilities. This is because different platforms use different forms of SQL and follow different protocols and mechanisms.
Oracle and PL/SQL - A Powerful Integration
Oracle SQL Developer uses a version of SQL called Procedural Language or PL/SQL, whereas most others, especially Microsoft SQL Server uses T-SQL. This itself gives Oracle an edge over its counterparts, as PL/SQL has many advantages over other formats.
For starters, PL/SQL is different from T-SQL in its syntax as well as capabilities, since they both handle variables, stored procedures and built-in functions differently. PL/SQL can also create packages of grouped procedures, unlike T-SQL.
This also makes it easier to convert applications to a different database without posing many challenges in editing or reworking the code. PL/SQL also has much more DBMS system packages than T-SQL and is better at error exception handling.
Organizing Database objects in Oracle - Highly Structured
Another major feature of Oracle which makes it more desirable is the way Database objects are organized in Oracle. Oracle has a subgroup of collection of database objects under a schema. There are many such Schemas, and they are all shared with the users. The sharing is universal but can be regulated through permissions.
Oracle works across all platforms and operating systems. This makes it a viable option for enterprises running on custom operating systems or freeware.
Transactions are a group of tasks that must be treated as a single unit. These are executed differently in different platforms, and Oracle is more in control of its transactions. Oracle treats each new database connection as a new transaction. As each query is executed, the changes made are only in memory until an explicit statement is given. Upon issuing the COMMIT statement explicitly, the changes are permanently made. This offers great flexibility as you can easily roll back changes and correct errors.
Oracle also has a wider variety of options to choose from in DBMS packages. Other options like Microsoft SQL Server does not contain provisions to declare some object types like public and private synonyms, independent sequence objects and so on. Therefore, Oracle is a more comprehensive option as it covers all the bases.
A cluster of servers refers to a connected group of physically separate servers that act in harmony and are perceived as a single system by networks. This helps in up-scaling by increasing computing power. Oracle can take advantage of Clustered systems, unlike their peers. With the new parallel servers in Oracle, you can place any application on a cluster without affecting the application, and it can be up-scaled by adding another server. This puts it miles ahead of its competing platforms.
Working with computers on anything can be quite a hassle. Even in simple cases such as writing this article, one mistake can cause you to lose all your progress. Therefore, applications have to be reliable in all aspects.
Oracle has many features that ensure a smooth work-flow and contains safeguards against any unexpected issues. It allows you to mirror transaction log files, which show exactly what programs were executed and when. It also prevents crashes occurring as a result of less space on the hard disk, and saves the server from downtimes and rebooting. This makes Oracle a safe option when compared to other DBMS platforms.
Oracle: A Powerhouse
The above-mentioned features show exactly why Oracle is a more desirable option over its competitors. As a freeware, it is readily available. It also has a wider assortment of DBMS packages and options to choose from and is much more flexible. SQL Programming in Oracle works with every platform and OS. It is also more reliable and versatile as a platform, and the Clustering feature alone puts it at the top of the table.
Python is now regarded as a must-have skill for most of the data analytics and data science job roles. And even though its seeming popularity is not the primary reason for it, it seems to be a major contributing factor. Due to its popularity, Python exercises, Python programming proficiency, and Python interview questions form an important aspect of getting a job in the data analytics sector. Almost every recruiter looks for Python as a necessary skill, instead of just one that gives the recruit brownie points. And this is because of how widely accepted it is as a programming language.
Python-based websites and apps are the frontrunners of their sector, and this is a list of some of those.
The tech giant Google which has evolved into a household name even has a saying about it, “Python where we can, C++ where we must.” Quite a bit of Google infrastructure is built using Python, especially YouTube. The largest video sharing platform in the world uses Python for almost everything, most notably their targeted advertisements and suggestions.
Instagram is another popular site that is almost entirely built on Python. The social media platform revolutionized the sharing of pictures on such levels that Google was practically throwing money at it for acquiring it. This all started as a simple website with a Django backend running on just one server. Django is an open-source developer used by Instagram to this day, and it runs on, you guessed it, Python.
The front page of the internet is a massive online society that, if you know, you know. For the uninitiated, Reddit is a place where you can find a community (called a subreddit) or everything. If you don’t know about this site, chances are you’re living under a virtual pile of rocks. This website is also reliant on Python, and cannot survive without its simplicity, and endless libraries.
For those of who are done with seeing examples of social media, here is a breath of fresh air. IBM, which has been and still is a big name in the IT industry uses python for many things, most notably using a Python SDK for IBM’s big data and AI service called Watson, and a free Python tutorial that they have released. And when a company that has been a huge contributor to the tech environment uses Python, that’s a tell-tale sign of Python being capable.
Spotify is the music streaming service that has revolutionized the Music Industry as we know it. Millions of users trust the platform to not only listen to their favorite songs but also put them on new ones with their incredibly personalized and accurate suggestion feature. Spotify uses Python for many backend functions and Analytics, which means that Python is responsible for the suggestion algorithms Spotify is popular for. Netflix, the global Media streaming service also follows in Spotify’s footsteps by using Python for a similar purpose. When you see these two giants using the same language for their exceedingly well-reputed work, that is a testament to the relevance and capability of the language.
Dropbox is a popular online data storage service that makes use of cloud computing to safely store your data. It is one of the most widely used platforms for this purpose across all operating systems, both personal and enterprise-related and has a total value of over $8 billion. Dropbox also uses Python for various purposes, most notably its well-sculpted Desktop version.
Uber has disrupted Taxi services and has brought this part of the transportation sector into the Cyberspace. They use Python as their go-to programming language, helping them with their Analytics and algorithms.
Python is widely used for a plethora of applications in various sectors, from social media to various services. This is even though it is not the fastest computer language out there. Even though computers are preferred for their speed, Python, despite being slower, is used more than faster languages such as C. And the reason behind this trend, simply put, can be summed up as follows.
Python is easy, reliable, and manageable. The script itself is easier to understand, and this makes coding and maintenance of the program easier. And even though it is slower, Python still gets the job done. Since most of these programs are run on a huge scale, the difference of milliseconds or seconds in speed does not matter.
Also, being a glue language makes Python more flexible and easier to write. This means that you can write part of the program in one language, and simply attach that part to the Python language. This is an important feature, as many other languages possess features better suited for certain applications, and they can all be executed in Python.
Taking Advantage Of The Python-philia
When a language is in such a coveted position, learning it can give you an edge over other candidates that do not possess the level of skill as you. Practicing Python exercises online and solving Python Practice sets gives you a grasp over the language, that can put you ahead. Python is overwhelmingly popular, which means knowing it makes you a favorite with the recruiters. In addition to the bigwigs in the Cyberspace, almost all websites and apps are initially written in Python. The ease of handling and its flexibility as a glue language has turned it into a Universal language for Coding.
To take your data analytics career to the next level, visit https://www.stratascratch.com/.
SQL is a prerequisite skill for all those who are aiming for positions in the Data analytics domain. And like any other core topic, the SQL knowledge of a candidate is tested via written examinations, coding tests as well as interviews. Tackling them requires mastery over the subject, but SQL interview questions pose a different kind of threat than conventional SQL exercises or problems.
Interviews, in general, are more stringent than conventional exams because of the nature of the process. Interviews are one on one interactions between the candidate and the examiner, and hence are harder to crack. More often than not, the person may be facing an interviewing board where you never know what's coming next. The level of stress in these situations is much higher and harder to handle. This is why many fail in cracking interviews.
SQL Interview Questions
SQL interviews come under the technical interview category and hence are purely based on the job and the expectations. Markers like personality and spirit take a back seat, and the interviewers judge the technical ability of the candidate first and foremost. Therefore, SQL interview questions are designed to test your knowledge on the subject, and also your ability to correlate the principles with field work, checking your practical application skills.
Types Of Questions
Since it is impossible to find what the interviewers might ask, it is easier to try and figure out what they look for in an employee. The apparent answers are knowledge of the subject and programming skills. So, SQL interview questions are set to measure those markers.
The “Theory” Questions
These are questions that can be considered as bookish knowledge, as these questions are generally about theory, definitions, classifications, and so on. Knowing this might not have a lot of practical value, but it shows that you have sufficiently broad knowledge about the subject as a whole.
Questions such as definitions of standard terms, terminology, the concepts can be considered as this type.
The “Problem” Questions
These are a little more complicated, as they are not as straightforward as the theory questions. These questions test the true mettle of a programmer and are based on realistic situations. Answering these types of SQL interview questions correctly is crucial, as these will set you apart from the rest. They not only reveal your knowledge, but also showcase your awareness about using it in a professional capacity.
Preparing for SQL Interview questions
SQL is just like any other subject, so preparing for SQL interview questions has the same necessary steps as any other subject. One must have a firm grasp of the basics of the subject and the expected questions. Awareness about the latest developments and current trends are also necessary to nail the interview. Each question is designed to test you in different aspects. Therefore every answer counts.
Here are some of the common questions asked in SQL interviews.
More questions can be found in online resources.
SQL interviews can seem daunting at first, and prove to be impossible to conquer if unprepared. The subject has grown to be so important that it is now deemed as a must have for all Data analysts and scientists. Therefore, mastering it is of paramount importance for all aspirants. SQL interviews can easily be nailed with ample preparation and confidence.
All the best!
To take your data analytics career to the next level, visit https://www.stratascratch.com/.
Structured Query Language or SQL is the backbone of data analytics and data science. SQL assumes data in the form of tables similar to spreadsheets. The language is based on relational algebra, which allows it to sort, filter, and recall data. The language has also undergone many modifications to add new functions and capabilities. This has caused SQL to evolve and branch into many different versions, each of them distinct but all based on the same relational mathematics that forms the skeleton of SQL.
SQL in Data Analytics
SQL has assumed a position of industry standard within the field of Data Analytics. This is because the data structure considered within the program is a spreadsheet format, which has the most amount of applications in businesses. This is also because of the salient features of SQL, which make it easier to use for all.
This has also resulted in SQL being an unavoidable skill for data analysts and developers. Basic SQL knowledge is now tested during the recruitment process of these jobs. SQL and Python problem solving, SQL Interview questions and SQL Exercises are given to aspirants in this sector to measure their proficiency in the language.
SQL Proficiency Testing
As SQL has become an essential subject in the industry, the SQL proficiency of possible recruits is also being put to the test. All companies concerned with data science hire people who are well versed in SQL, among other things.
As it is with coding, tests are conducted by companies to measure the proficiency of possible recruits, and only those who do well are selected for the jobs. SQL exercises, interview questions and SQL problem-solving are the main methods used by these companies to choose the cream of the crop.
Practice results in perfection is a tried and tested principle. Since their early schooling of elementary mathematics, students have been encouraged to practice using the theoretical knowledge that they gain, not only to excel in the subject but also to improve problem-solving and analytical skills.
SQL exercises fulfil the same purpose. The activities are the same as any other exercises for any other subjects. They are available on various online platforms and come in a variety of difficulty levels. There are many benefits to practising SQL Exercises online and solving them.
SQL exercises are designed with two main goals in mind.
Correlating With Theory
SQL exercise questions and answers have to be related to all the main theory parts of the programming language. A good SQL exercise set will have a variety of problems touching upon every part of the language and in various difficulty level. Practising with them as you study helps the student to master the practical applications of the language and hence stay up to date.
Practical Application Of SQL Programming
SQL tutorials will also have problems that mimic the real-life usage of SQL in various sectors. As the course in itself aims at enabling the learner to master SQL at a professional capacity, these problems are necessary. SQL problems and answers will be similar to what a Data scientist will have to encounter in the line of their work.
SQL Exercises Online: Difficulty Levels
As it is with all exercises, this subject also comes with a variety of questions in different tiers of difficulty. Depending on the knowledge and skill of the student, they can choose from varying levels of difficulty of the items, that check the test taker's knowledge on any one specific topic or in the broad sense. This range of difficulty allows the user to not only measure their progress but also work to attain the next tier of their skills.
SQL Exercises Online: The Benefits
It makes sense for SQL problem sets to be available online, as SQL is first and foremost a programming language. Even if a person learns all the theory in the world about SQL, it is still useless without solving SQL problem sets. With that being said, these exercises help the student to improve their skill set in a way that can't be satisfied with conventional schooling.
The obvious reason for this is that SQL is a computing language. The fundamental process is coding, the raw material is digitally structured data, and the application lies in Data Analytics. Therefore, it is only logical for SQL exercises to be done on a digital platform.
Another reason why one should opt for SQL exercises online is due to the nature of the subject. As an essential tool in the digital world, SQL is fluid and ever-evolving. The language itself is changing, and the quality of tasks are becoming more complex. The volume of data handled is increasing, and the queries are becoming more and more complex. The ecosystem is in a constant state of flux, and any professional worth their salt has to keep up with these changes. Therefore, using online resources that provide SQL problem sets make more sense.
SQL is growing in significance and is now an irreplaceable tool for every aspirant in the field. The scope of this subject keeps expanding, and one must be able to keep up with it to reach the top. SQL exercises are available online to enable the technicians to be better at the trade. Practice makes perfect.
To take your data analytics career to the next level, visit https://www.stratascratch.com/.
This blog post follows our “SQL Interview Questions From Real Companies” video which can be found at https://www.youtube.com/watch?v=n6gM265zG68.
In this post we’ll go through 4 SQL questions you’re bound to encounter during a technical interview. While these problems are on the easy side, it’s still important that you bring along the interviewer. You want to show your interviewer your thought process. It’s okay if you don’t have enough time to solve the problem. Interviewers care more about how you solve problems in general than whether you can solve this specific problem. So during an interview, remember to take your time and describe each step to your interviewer.
We’ll use a three-step approach to problem-solving that you can use during your technical interviews. First, remember to build up a query step by step and explain each step to the interviewer. Your interviewer wants to see that you know what you’re doing and why you’re doing it. Second, you should be looking for edge cases throughout an interview. By asking your interviewer questions about edge cases you’ll show the interview your attention to detail. Finally, you should be able to explain to the interviewer the effect of every clause and expression.
We’ll be using Strata Scratch for our SQL exercises. Strata Scratch is a platform that helps you prepare for technical interviews. Every problem in this post is available to you on Strata Scratch.
Question 1: Find the drafts that contain the word optimism.
For our first interview question, we’re given a table called google_file_store and asked to find all the draft files containing the word optimism.
We’ll start every problem by looking at the table. I can pull keywords out of the question and use them to understand the table. Looking for ‘draft’, I see a few file names start with ‘draft’. All draft files must follow the format of the word ‘draft’ followed by a number. I also see that some of the contents contain the word ‘optimism’. Now is a good chance to ask the interviewer some questions. It’s always important that you ask the interviewer questions because helps you solve the problem and it helps the interviewer understand your thought process.
A good question would be, where in the content is the word ‘optimism’ located? Is it in the beginning, middle, or end of the string? It might seem obvious from looking at the table that the position of optimism doesn’t matter for this question, but asking questions can still benefit you. Currently, we’re making assumptions about the problem, and by asking questions we guarantee we’re solving the problem correctly and showing the interviewer our attention to detail. For this problem, the position and the case of ‘optimism’ do not matter.
Let’s start writing our query. Every interview problem starts with writing out the basic query. For these problems, we’re using the SELECT * statement. The SELECT * statement is used whenever you want to return all columns of information from a table. The next clause in the basic query is the FROM clause. This clause is used to choose which table we’re getting information from. We’ll add ‘FROM sql_interviews.google_file_store’. As expected, when you run this query, it returns all the information from the table.
To solve this problem, we need a way to filter the results. We do that using a WHERE clause. Understanding the WHERE clause is critical when going into a technical interview. Almost every question will involve understanding the context of the problem, and describing that context as a WHERE clause. The WHERE clause works by taking an expression, which is something that returns true or false. Each row is evaluated using the expression; if it’s true the row is returned, and it’s false it gets filtered out. We’ll need to write an expression that matches the two conditions of our problem so that we can filter out what we need. Each file has to be a draft and the contents must contain the word optimism.
Let’s deal with the first condition first. We need an expression that can do simple pattern matching. In this case, the ILIKE expression is perfect. This expression takes the name of a column and a pattern string, and only returns rows which match the pattern. Pattern strings have two special characters. The % character represents 0 or more of any character, and the _ character which represents exactly 1 of any character. Using those 2 characters we can use pattern matching to match many strings. We need to write a pattern that can match any string starting with ‘draft’. The pattern is ‘draft’ followed by 0 or more of any character so we’ll use ‘draft%’. This pattern string will match any string starting with 'draft'.
Now that we have a pattern string we can write our expression. After our WHERE clause, we’ll as a tab, and write “filename ILIKE ‘draft%’”. Now when we run the query it only returns drafts.
Now we can deal with the second condition. The second condition is that the contents contain the word ‘optimism’. We’ll add an AND expression. AND expressions allow us to have two conditions. They will check the expression before and after, and only return true if both expressions are true. Now we can add an expression for the second condition. This condition requires more pattern matching so we can use ILIKE again. The only difference is that optimism is located in the middle of the contents so we need a different pattern string. There can be zero or more characters before and after optimism so we use ‘%optimism%’ as our pattern string. We write ‘contents ILIKE ‘%optimism%’ after the AND expression.
Now that we’re filtering based on all conditions, we’ve solved the problem. I can run the query and I get the expected results.
Side note on the ILIKE expression. ILIKE has a sister expression called the LIKE expression. Both expressions work the same with one exception, the LIKE expression is case sensitive and the ILIKE expression is not. For this problem, the case of ‘draft’ and ‘optimism’ do not matter so we used ILIKE.
Question 2: Print all workers who are also managers
For our second question, we’re given two tables, worker and title, and asked to write a query that lists all of the managers.
As always, we’ll look at the table first. You’ll see that the worker table has all the information about each worker, but doesn’t list their job title. The title table lists the job title of each worker, but it only has a reference to the worker. For this problem, we need information from both tables so we will need a JOIN.
We’ll write our basic query first. SELECT * FROM sql_interviews.worker table, because we don’t know which columns we want to return yet.
Now I need to combine this table with the title table. To combine tables we use the JOIN clause. The JOIN clause is another clause that you need to know. Your interviewer will want to see that you have a solid understanding of how JOIN clauses work. JOIN clauses work by creating a table containing every possible pair from both tables and filtering that table with an ON clause. An ON clause is like a WHERE clause for JOINs. So to combine these tables we’ll add ‘JOIN sql_interviews.title’.
Now that we’re working with two tables we want to name each table with an AS clause so we can directly reference them. It’s common when writing queries to name a table after the first character in its original name. I’ll be naming the worker title ‘w’ and the title table ‘t’ so I can directly reference later in the query.
Now when we run the query we have a table that has the information about the worker and their title. We have to filter this table with an ON clause. If we could run this query without an ON clause, we would get a table that had every possible pair of worker and job title combined. Obviously, this isn’t what we want; we want every worker to be paired with their job title. We can get this table by adding our ON clause. ON clauses work the same as WHERE clauses so all we need is the correct expression. In this case, the worker_id of the worker should equal the worker_ref_id of the job title. By adding ‘ON w.worker_id = t.worker_ref_id’ we get the table we want. Now we have a table where each row has the information of a worker and their job title.
Finally, we need to filter the table such that it only contains the managers. We have two choices for filtering out the managers. We can expand our ON clause. The ON clause works the same as a WHERE clause so we can add an AND expression followed by our condition. Then we can add our second condition, “t.worker_title = ‘Manager’” and the resulting table will only have managers. That works, but we can also add a WHERE clause. The new table created by a JOIN clause works just like the original table. That means we can filter it with a WHERE clause. Just add the WHERE clause with our expression. I prefer adding a WHERE clause because it makes your ON clause simple and easy to understand.
To finish the problem I’ll choose which columns to SELECT. For this problem, I only want each manager’s first name and job title. Running this query returns all of the managers, and solves the problem.
Question 3: List employees with the same salary
For our third interview question, we’re given the worker table and we’re asked to write a query that lists all the workers with the same salaries.
To solve this problem we need to use a self-join.
As always, we first look at the table. Looking at the table we see that each row has all the information we need for the problem. It lists their worker id, name, and salary. We need to find some way to select all the pairs of workers who have the same salary.
I’ll start by writing a basic query. We’re going to SELECT * FROM sql_interviews.worker because I don’t know which columns I need. Now we’ll compare this table to itself.
Comparing a table to itself doesn’t require a new clause. If we look back to problem 2, this isn’t any different from comparing the worker table to the title table. We want every pair of workers that have the same salary. To get that we can JOIN this table with itself. To start the join we’ll add ‘JOIN sql_interviews.worker’ to our query. Now that we have two tables we need to name them. I choose to name my tables w1 for worker 1 and w2 for worker 2. Next, we’ll add our ON clause. The conditions of this problem are that the salary of the workers should be equal and we can describe that using an expression. I’ll add ‘ON w1.salary = w2.salary’ to the query. Running this query will give us a table containing every pair of workers with the same salary.
There is one issue. If we run this query, it returns more rows than expected. If you’re paying careful attention you’ll see the problem. Obviously, every worker shares the same salary as themselves. That means there is an additional row in the table for every time a worker is compared with themselves. We need to expand our ON clause so each pair must have different workers. I’ll add an AND expression followed by the new condition ‘w1.worker_id != w2.worker_id’. Now when we run this query we get a table that only contains pairs of different workers with the same salary.
Finally, we can finish our SELECT statement. For this problem, we’re interested in who has the same salary. We should return the columns for each worker’s name and the column for their salary. Running this query should return Amitah and Vivek, and Vivek and Amitah, which is correct. We’ve solved the problem.
Question 4: Find the first 5 entries of joined contacts and searches
For our fourth interview question, we’re given the tables airbnb_contacts and airbnb_searches and told to merge the tables on an appropriate key and display the first 5 results.
This problem can be more challenging because we aren’t told what to match on. It’ll require quickly forming an understanding of the tables and making a judgment based on that.
It should be noted that we’ve changed schemas from sql_interviews to datasets for this problem.
Let’s look at the tables. Immediately we see a problem, while these tables do have shared columns, the ds_checkin column, and ds_checkout column, those columns are not uniquely identifying. If a column isn’t uniquely identifying, then we can’t join on it alone. We need to understand the table better to solve this problem.
In a situation like this, it’s best to ask the interviewer questions so we don’t make incorrect assumptions. You’ll never be penalized for asking questions about the problem, so don’t worry. First, we can ask what each row represents in airbnb_contacts. The interviewer will say, each row in this table represents a contact between a guest and a host about a listing. It’s important to note that this table has the unique user id of the guest and the host. Then, we can ask what each row represents in airbnb_searches. They’ll say, each row represents a search performed by a user trying to find a listing to stay in. Given that information, we can start to form a solution. In this case, we know the users that perform the searches found in airbnb_searches are also the guests in airbnb_contacts. We can ask the interviewer if id_user column represents the same user as the id_guest column. They do, and that’s something we can JOIN on.
We’re going to write our basic query. Like before we’ll SELECT * FROM datasets.searches. Because we know we’re going to need two tables we should name our table now. I choose to name it ‘s’ for search.
This problem requires information from two tables like in previous. We’ll be using the JOIN clause again. This join is just like the JOINs we used in question two and three. Based on the questions we asked the interviewer, we know that id_user from the searches table represents the same user as id_guest in the contacts table. That’s what we’ll be joining on. We’ll JOIN with the datasets.airbnb_contacts table, naming it with an AS clause, and add ‘ON id_user = id_guest’. When we run this query it returns a table where each row represents a search that leads to contact. This is technically a solution, but we can do better.
To improve our query we need to ask our interviewer what questions they’re trying to answer with this data.
One way to improve our query is to choose the correct type of JOIN. There are two types of JOINs in SQL. We’ve been using an INNER JOIN which only returns matching pairs. We can also use an OUTER JOIN if we want information on rows that have no match. If the interviewer is only interested in matching searches where users contacted their host, then an INNER JOIN is appropriate for this query. If instead, the interviewer wanted to know the ratio of searches that resulted in contact, then an OUTER JOIN would be more appropriate. We would want to return all searches that don’t result in contact so we would use a LEFT JOIN in this case. That is the case so we’ll replace our JOIN clause with a LEFT JOIN clause.
Another way to improve our query is to make our ON clause more specific. The ds_checkin column and ds_checkout column are common across the two tables. It makes sense that adding them to the ON clause will create a more accurate representation of a user’s search intention. Some users will have multiple searches and contacts, and if we only want to return searches that lead to a contact, then each search should be for the same day as the contact. If we don’t check for this condition, then one contact in the table could result from multiple searches. We’ll improve the ON clause by adding the conditions that ds_checkin and ds_checkout are equal across the tables. Improving your ON clause in this way will show the interviewer that you have good table comprehension.
During an interview, it should be your goal to continuously improve your solutions. By asking the interviewer questions you can solve a problem exactly how they want. Even if your initial assumptions are correct and you don’t change your query, you’re still showing your interviewer that you’re through.
We only want 5 results for this problem, so we add a LIMIT clause. LIMIT clauses work by taking a number, and only returning that number of rows. For this problem, we want all the information so SELECT * works. Running this query gives us our valid solution.
Watch Our Youtube Video On These Four Questions
The last three of these problems show how important understanding JOIN clauses are. It can be challenging understanding what’s going on. If you want to practice writing SQL, I recommend joining Strata Scratch. You’ll have access to over 450 questions taken directly from real companies and you can use them to prepare yourself for an interview.
If you’ve made it this far, and you still haven’t seen the related video, then I highly recommend watching it now. The visuals will make understanding this material easier.
The twenty-first century is the age of information. The internet is now an essential part of human life, and some countries even see Right to Internet Access as inalienable. Knowledge is power, and information is the lifeblood of today’s world.
This level of connectivity has drastically changed the lifestyle of our generation. People are now more accustomed to using services online. Work, Shopping, Banking, and even social interactions are now ruled by the internet. In this day and age, an online presence is part and parcel of a healthy and interactive lifestyle.
The Growing Demand For Data Scientists
Data Scientists are in huge market today in all sectors. As computers have disrupted every primary industry in the world, experts on the subject are sought after in all areas. The same goes for Data Analytics, including but not restricted to Big Data.
All industries work based on and generate some amount of information regarding their products or their customers — for example, the healthcare industry. Terabytes of data related to innovations, medication, and patients are generated every year in this industry from research as well as day to day operations of establishments. The same can be extrapolated to any trades. Hence, Data Analysts and Scientists are needed in all fields in some capacity.
The Hottest Job Profile
It is no surprise that Data Scientist is a profession that is in demand in all fields. Every sector has its own share of digitization, and Data Analysts and Scientists are needed to look after their online presence and also make the most out of the virtual resources they have at their disposal. This is why Data Science has blown up as a hot topic in all sectors.
As far as the statistics go, all jobs that fit this profile demand basic computer programming skills as a prerequisite. It used to be that knowing SQL served as an added bonus point that put you above the competition. But the times have changed, and SQL has gone from an additional skill to a pre-requisite. It is widely accepted as the industry standard in domain-specific coding and is an unavoidable tool in the arsenal of every analyst.
SQL in Data Sciences
With Data science disrupting every industry, the role of a Data Scientist is no longer just restricted to Computer Science. There is more demand for analysts, and their work is more oriented towards a practical purpose than research or programming. Their role is to work with the data generated by their respective industry, and this is where SQL programming proves to be useful.
SQL belongs to a class of programming languages called Declarative Programming, a language that uses declarations for coding and commands. The writing itself is easy to learn and understand, and there are not many commands to learn. It is a language that is more practical than others and can be mastered by those from non-technical backgrounds as well.
“Structured” Query Language
Basic SQL proficiency is required for Data Analysts due to the nature of the job. Most businesses find it easy to perceive data in a spreadsheet or table format, which calls for a language that works based on that structure. SQL fits this description and hence is widely accepted as the industry standard.
The spreadsheet format in which SQL structures data is similar to MS Excel or other spreadsheet programs, that are popular in business as well as management circles for storing and analyzing data manually. This popularity is exploited in SQL.
Data Analytics In Other Industries
As explored earlier, the rising demand for Data Analysts in other industry is because of the disruption caused by the IT Industry in these sectors. Computers here are mainly used for storing and processing data that are harder to document manually. It also performs tasks like monitoring, tracking, performing simulations, designing, billing and so on. Almost all processes that are done using computers involve some form of Data generation, which has to be stored for later study.
In any case, most businesses end up generating and storing data in a tabular format. This is how SQL penetrated these industries, as it was created for this very purpose, of analyzing and handling such data.
SQL Proficiency: Staying A Step Ahead
SQL is a tool that has been relevant in the industry for decades and is not about to go obsolete anytime soon. Therefore, mastering it is in the best interest of all hopefuls that aspire to be a Data Scientist. SQL can be learned like any other subject, and the resources are all available online. SQL courses, SQL Problem sets, and SQL exercises are available online for studying and practice purposes.
SQL is like any other tool, and hence it serves best when it is at maximum sharpness. Therefore, regular practice is necessary to become proficient in the subject. Also, it is essential that every aspirant learns about the latest developments, and keeps expanding their knowledge on the subject.
To take your data analytics career to the next level, visit https://www.stratascratch.com/.
Structured Query Language or SQL is a domain specific language that is used to code and manage information held in a relational database management system. The Language is based on relational algebra and was developed by Edgar. F. Codd at IBM. SQL has now grown in importance, and basic knowledge of SQL is now a prerequisite for those who aim for a job in Data Analytics.
Job Opportunities In Data Science
Data Science has been blowing up in the past decade, creating thousands of jobs all over the world. Database Management Systems are used in many industries and not just core IT jobs. All sectors have an IT division which acts as the anchor to cyberspace for these firms, and this anchor is becoming more critical as the Internet as a realm of business continues to grow.
SQL In Data Science
SQL is very much in demand for jobs in the Data Science sector. It is one of the basic skills necessary, and one of the things that make you employable in this sector. SQL has been an irreplaceable tool for Data Analytics, and there are a few reasons that make it more preferable over other similar languages.
SQL is a relatively simple language and is suited for business purposes. To put it in layman’s terms, SQL is similar to MS Excel, which makes it “good for business.”
The reason for this simplicity is because SQL is a language that structures data in similar to a tabular or spreadsheet format. This is a relatively uncomplicated form of Data arrangement and makes it the natural language for businessmen, analysts, and even data scientists.
Not just the Data Structure, but the coding done in SQL is also in a simple format. The primary operations in SQL are Projections, Filters and Joins, and Aggregations. These are respectively for selecting, filtering and grouping data. The code in itself is understandable and hence can be studied from simple reading.
SQL was designed to be the industry standard. In the 1970s, there were a lot of platforms with their own compatible operating systems. This made migration a nightmare until SQL was developed. SQL today has many different versions, as not all problems can be solved by relational databases. All these versions have their applications and are all based on SQL.
SQL is also easy to learn and a popular choice as a first step towards programming. Unlike other languages, the program does not require the coder to understand the mechanics of the commands. Each query is simplistic, and this type of programming is called “Declarative Programming.”
SQL uses declarative statements as commands in the language, which are simple words or phrases that call data or perform a function. These commands either work or don’t, which means the user does not need intricate knowledge about coding. This is also the reason why even non-technical personnel are encouraged to study SQL as a part of broadening their CV.
SQL is also more optimized than other languages. As the language itself is simple, the platform does all the heavy lifting and hence can optimize the query in any way necessary. This saves a lot of effort for the developer and time for running the program.
SQL Queries are faster than others because of the structured data and optimized searching. The entire data is organized under appropriate headings and tags, so quick filtering and selection are also enabled. This also makes SQL capable of handling large volumes of data in a short time.
SQL has been relevant for over half a century because it has managed to evolve with the times. The core of SQL is still based on relational algebra, but many functions have been added to it over time. Statistical function calculations, pattern matching capabilities, and approximations. This has made it a popular language and a fundamental skill for all data analysts and developers.
Due to its popularity and ease of usage, SQL is adopted by many companies. Even big names like Amazon uses SQL for providing suggestions for users, and also provides SQL usage as a part of AWS. The search is input as a simple SQL query that pulls all data of subsequent searches by previous users and suggests the most similar and common ones.
SQL In Data Analytics Jobs
All these qualities make SQL the ideal choice to act as the universally accepted platform for Data Analytics. SQL is the go-to language for many websites, applications, and platforms for data management. The language itself requires only necessary coding skills to develop programs on and is easy enough to understand. This makes this a popular choice for even non-technical personnel to learn. This is where SQL becomes a crucial part of your CV.
As a result, SQL Interview questions and SQL problems are pervasive in Data Analytics job selection processes, as basic SQL knowledge is demanded these jobs. The language is an industry standard, and learning as well as practicing SQL online is necessary to nail these jobs. Therefore one must strive to learn advanced SQL skills to get ahead. This can be done by using online resources, SQL practice, and SQL problem set. A firm grasp on SQL is now a necessity for these jobs.
To take your data analytics career to the next level, visit https://www.stratascratch.com/.
So you’ve just managed to score an interview with an aspiring silicon valley company that you’ve had in your eyesight for years? But now the anxiety is starting to set in, and you may be afraid you oversold yourself in your resume and cover letter? Well, you should be nervous, as large tech companies are notorious for asking tough, adrenaline squeezing questions to force you out of your comfort zone. So why not go out of step out of your comfort zone right away voluntarily?
Below you’ll find a quick breakdown of potentially employment-saving advice ranging from cortisol-killing habits to ideal factual preparation. It is time to channel your nervosity into motivation to make yourself a bullet-proof candidate. Ideally, your job interview lies a couple of weeks ahead. If this is the case, start with the bottom of this list and work your way down. It is never too early to prepare for such a life-changing appointment.
Early preparations (1 month to 1 week before the interview)
Read up about the company
Reading up does not mean just scrolling through their Wikipedia page and memorize their CEO, Net Income and recent controversies. This research process is one of the best ways you can shine as a stand-out candidate during the hiring process.
When researching your (hopefully) future employer, try to answer the following questions:
If you are still wondering, why this intricate research may make or break your application. Read this overuses Art of War-quote: “If you know the enemy and know yourself, you need not fear the result of a hundred battles. If you know yourself but not the enemy, for every victory gained you will also suffer a defeat. If you know neither the enemy nor yourself, you will succumb in every battle.”
Checking your CV
Chances are if you’ve already scored an interview, you most likely sent them your CV. If not, make sure the CV you bring with you flawless. A great CV will do most of the talking for you. Besides, you may want to tailor your CV for this particular employer. There may be some qualities the employer values, that you didn’t think were necessary to include in your CV. Check the answer to question 2 mentioned above, and dig out relevant experience from your past that reflects these skills.
Refreshing Your Skills
Whether its hard or soft skills, brief but continuous refresher a couple of weeks before the interview will do you right. Especially if your previous job didn’t necessarily demand the same skillset. If you’re a developer, you’d most likely be doing light SQL. If you haven’t used SQL in a while, it would be highly advisable to find out which SQL database your employer uses, as they all have a specific syntax. Refresh your skills on how to get, insert and update data, as well as basic table creation. An excellent way to refresh these skills and prepare for potential SQL-related questions is through our dedicated service. While refreshing your skill-based knowledge usually doesn’t take more than a couple of hours, it would be preferable to get it out of the way weeks ahead and then take a glimpse of your work the day before.
The physical aspect of what causes nervosity should not be underestimated. It is no secret that exercise lowers your cortisol (stress) and is another excellent way to prove yourself, that you can step out of your comfort zone if necessary. Ideally, you should already be exercising routinely anyways, as part of a healthy lifestyle. If you are not, get off the couch as soon as possible.
Short term preparation: (1 week to 1 day before)
Read up on standard interview questions
This is perhaps the most critical aspect of preparing for a job interview. While the refresher of your technical skills from earlier should already have you confident in technical questions, it is more likely that the personal items are what makes and breaks your interview.
Even though many of these personal questions, like: Tell me about yourself? Or How did you hear about this Job? Seem to demand a spontaneous answer, it is important to not rely on your instinctive reasoning, when encountering such a potentially stressful situation. Clearly write down your answer to these common questions in bullet points, then look over them and be spontaneous in how you word your response, but make sure the content and message are consistent. When crafting your answer, please look back over the company research you conducted a couple of weeks earlier.
Some of the most common questions include:
Advice for Day Zero
While many people care to look presentable on such an important day, there are still some things you should consider specifically for tech companies. And yes, being overdressed can be very damaging you will seem out of place and alienated. While many people wear jeans, chances are they didn’t wear them on the day of the interview, since that would be downplaying it too much. Nowadays a polo with a pair of slacks is a common sight for silicon valley job interviews and is usually a safe bet. If you know someone at the company try to find out what most employees there are wearing.
Fake it til you make it. If you pretend to be Superman, you shall become Superman! Even though that may be an exaggeration, chances are you will be blown away by the noticeably positive effects power posing can have on you. And best of all, it doesn’t take time or money to do. Before you enter the interview, recede to the restroom and try a two-minute superman power pose. Stare in the mirror, rest your hands on your hips and spread your feet wide and expose those chest muscles.
Don’t mention weaknesses that are actually strengths
This is an often overlooked point, and if you inquire advice for job interviews elsewhere, they will most likely tell you to mention strengths as weaknesses. For example:
Q: What would you consider your greatest weakness?
A: I tend to get too immersed with work and sometimes forget I am well into my supposed lunch break.
These kinds of responses make any well-seasoned interviewer cringe and will never yield you a positive impression. It makes you seem pretentious and inauthentic. Instead, mention a legitimate weakness and what steps you have taken to overcome these weaknesses. The interviewer will see you as merely human, but as a dedicated problem solver at the same time.
Do you have a passion to work with data and want to pursue a career as a web developer, data analyst, business analyst or a data scientist? If yes, then it becomes imperative that you must master the basic SQL concepts.
It would not be wrong to say that SQL skills have become indispensable in most of the job roles. Being the most ‘in demand’ database programming language, knowing beforehand what kind of questions are asked during a job interview can definitely give you an idea on the level of preparation you need in order to get your dream job.
We have SQL interview modules that consist of real-life questions from top technology companies that can boost up your interview preparation. These questions can definitely help all aspiring data analysts, web developers, and data scientists in acing their technical interviews.
How can Strata Scratch platform help you?
Proficiency in SQL along with an analytical bent of mind can definitely help you to achieve your career goals. The recruiters mostly look out for professionals who have expertise in the subject. So in order to crack the interview we have incorporated the frequently asked interview questions on SQL.
Our endeavor has always been to help and guide the aspiring professionals in this field. Keeping this in mind this new feature which we have added in our SQL educational modules contains SQL interview questions from top tech companies like; Facebook, Yelp, Google, and AirBnB.
Using Strata Scratch’s SQL interview modules to enhance your skills
The SQL interview questions from these top technology companies are real questions that are typically used in interviews and in their daily lives. We start with basic SQL questions and then allow the users to gradually graduate to more advanced techniques. Most importantly, all the questions are relevant to working at real companies, so that your skills are directly applicable.
The SQL questions and answers incorporated in the module are from HackerRank and LeetCode. These two are the top sites that currently help technical professionals with their interview preparations.
The modules are user-friendly, you simply need to login and click on the SQL exercises. You will see the following screen -
Then you can run a query on the above screen, for instance- AirBnB, and it will display the results as follows -
One the left-hand side of the screen under the educational tracks you can find the SQL interview questions.
You can then select the option SQL interview questions under the education tracks and then view the interview questions pertaining to that company under education modules.
Ace the game with SQL interview modules
As a young professional, when you are new to the job market or when you look out for a new job and expand your skill sets, we know how hard it is to find resources that can help you in improving your technical capabilities. Most of the resources are often too technical or they are irrelevant to the interview process.
However, at Strata Scratch we have designed our SQL interview modules specifically for professionals who are looking to pick up new SQL skills or want to improve on their existing SQL skill set.
So go ahead and achieve your career goals today!
The growing importance of business analytics
Analytics allows businesses to take a data-driven approach to achieve their goals. By leveraging technology, data modeling, and statistics, businesses can develop new insights that can help them in developing or marketing their products better (better is measured by increased sales or user engagement).
The growing trend is that most of today’s companies, big and small, are investing heavily in their technology stack to supercharge their analytics — both for product (i.e., data scientists) and sales/marketing (i.e., marketing scientists). The way we do business has changed over the years, in that technology products themselves, like iPhone apps, are the core product/services of many businesses. This allows for real-time monitoring and insights, and delivering marketing and product experiments in real-time to increase sales and engagement, which ultimately results in so much data that insights can only be mined using heavy duty technology stacks that were traditionally developed and used by engineers.
How can non-technical students fit into this role?
With the demand for technical skills in all departments in a company, there’s always a need for someone that cannot only think in a data-driven way but also operate and execute analytically. Non-technical professionals, I would argue, hold a better understanding of the business that often needs a holistic understanding of the industry, competitive advantage, high-level strategy, and tactics that drive the company. If only they can mine through all the data, they would be the unicorn all employers seek.
Three things I find important when learning analytics
1.Keep things simple
I believe that platforms should not require software installation. Companies would never have you install your own software -- nor would you have the permission to do so. When was the last time you installed a database locally on your laptop at work? Being able to work with tools and data accessible via a web browser is basically a requirement if you want to start. Basically, look for a SAAS platform to learn. Don't install any software, it's an unnecessary step in trying to learn analytics.
2. Specific content designed for marketing and business professionals
The course content you choose should be focused on edifying business and marketing students. This sounds obvious, but there are few, if any, course curriculum for business and marketing students interested in learning analytics.
In addition, I never rely on textbooks. It’s too static and rarely has an interactive component to it. Those that do have an interactive component often requires you to install databases and other tools to get hands-on. I try to use platforms, where the tools used, are common industry tools. SAAS platforms like Strata Scratch are built for non-technical marketing/business students and deploy common analytical tools often used in the industry.
This makes sense because marketing and business analytics professionals aren’t interested in developing new machine learning algorithms. They’re probably more interested in designing and executing on marketing experiments.
3. Technical expertise is not mandatory to become good at analytics, but a technical mindset is
You don’t need to know much about analytics or technology, but you do need to change your mindset. The mindset of learning, breaking down a problem, developing a solution is different between technical and non-technical people. Non-technical professionals often have a difficult time approaching and attacking a problem. Most often, I’ve found that they struggle because (1) they can’t seem to find an example in the notes that exactly match the problem at hand and (2) they can’t seem to break down the problem into smaller workable pieces so they become overwhelmed. Problems are like puzzles. Most often, engineers and scientists don’t know how to exactly solve problems or build the desired models, but through research and iterating through the problem and various approaches, they often are able to build something that achieves their goals. You must be comfortable not knowing what to do and you must be comfortable struggling along the way. Changing this mindset is done through practice and reinforcement. Technical people were once novices too, and they struggled with the exact same problems.
In marketing and business analytics, if you want to jump-start your career then knowing how to manipulate and analyze large datasets using python is a necessary skill set . Python tops the chart for the best career option for software engineers. And why not? Career opportunities in python are growing manifold across the globe.
Some of the reasons why Python is popular today:
1. Python is a High-level language.
2. Python is easy to learn.
3. Python is used to build server-side applications.
4. Python is an open source platform.
5. Python is Object Oriented Programming language.
Needless to say, learning Python has numerous benefits. Even it has been used by numerous big companies like Instagram, IBM, Google, Yahoo, and a few others to name. Since a lot of multinational companies are using python, there is no dearth of big opportunities for Python experts.
Have a look at various profile options you can proceed with after learning this amazing language:
There are plenty of platforms out there offering online guides and tutorial on Python, Strata Scratch is one name that is getting popularity for offering the best online Python Tutorials.
Top 5 Guides of Strata Scratch:
1. How to Clean Data with Pandas
In order to have glitch free data, the need arises to clean the ambiguous or fix missing data. So the need arises to clean the data using Pandas (pandas is an open source licensed library with easy to use data analysis tools for Python programming language.)
This tutorial introduces you to functions that will help you fill in missing values, remove null values. By the end of this tutorial, you should be able to learn how to drop unnecessary values and clean your dataset.
2. Functions, Lambda Functions, Loops, and List Comprehensions
In data analytics, there is a strong need to perform advanced operations on data such as reading lists, deleting vowels from the list and many others. Lambda functions are used to create a list.
In this tutorial, you learn about python comprehension using lambda or python loop functions.
3. Exploring Your Data
The essential part of data analytics is to explore data. It allows us to extract insights from data. Exploratory Data Analysis (EDA) using Python is very important for data modeling and getting insights from a large set of data
This tutorial teaches you an exploratory data analysis using techniques like histograms, boxplots and scatter plots.
4. Combining Data for Analysis (Joining/ Merging Dataframes)
Concatenation is very helpful in computer programming. In business analytics, most of the times need arises to make a single file from multiple files and spreadsheets. Python offers us very powerful tools to get this job easily done.
In this strata scratch tutorial, you learn how to concatenate or merge data frames with the help of various exercises.
Hope you enjoyed working on these practice exercises and learned different basics and advanced Python Queries. Wish you best of luck for your future. Stay connected with us for more challenging Practice sheets. Don’t forget to give your valuable feedback and comments for further improvements.
Are you planning to quick start your career? Do you wish to have some kind of technical job, or willing to have a sitting job in IT field? Then start learning SQL because the benefits of learning SQL are amazing and highly considerable and you can have a lucrative job by learning SQL.
SQL stands for Structured Query Language. It is used to retrieve data from databases in an easy manner and without writing too much code.
Benefits of Learning SQL:
1 Easy to Use
2.No Coding Required
Now when you have read the amazing benefits of SQL, you are ready to quick start SQL. StrataScratch is here to help you learn SQL for free, find some amazing Tutorials and Practice Exercises.
This tutorial is designed to guide you from the scratch. Here's the first practice set for you.
1. Basic SQL Exercise:
This Section is aimed to provide you with the basics of SQL. The questions in this section are quite easy but are interesting enough to motivate you to learn at a high pace and solve problems quickly.In this Exercise use commands ‘SELECT, FROM, WHERE, GROUP BY, ORDER BY’.
To start this Exercise for free, you can click here (Freemium access)
2. Basic SQL Exercise 2:
This section is in continuation of the first exercise to make your grasp bit stronger by applying some more commands in a bit challenging way. In this exercise you are required to use commands like ‘SELECT, FROM, HERE, GROUP BY, ORDER BY, LIMIT, DISTINCT, OR AND, AS, DESC, ASC, IN, HAVING. You will get enough examples and explanations to use all the commands and functions in our exercises / tutorials.
3. Advanced SQL Exercises:
Now if you think that the previous exercises were too basic or were just entry-level questions for you, don’t worry, here is a bit challenging and a new set of SQL Exercise. This set is intended for users who have cleared first two basic exercises. There are 15 tables used in this exercise. You have to use commands like ‘AVG, DATE, MAX, JOIN and many other. This can help to improve your skills.
4. SQL and Business Insights:
Now when you have got your basics clear so is the time to move one step further and try exercises which are designed to challenge your analytical skills and solve actual business problems. This section provides you 6 different exercises. You can check this SQL Exercise right here.
5. Hotel Reviews Exercise:
This section is composed of questions related to Tourism and Business Management. In this Exercise, you have to use most of the commands which you have learnt in the basics and Advanced Sections but questions asked in this section are really challenging and tricky enough to use all your analytical skills.
Hope you enjoyed working on these Practice Exercises and learned all the basics and advanced SQL Queries. Stay connected with us for more Challenging Practice sheets. Don’t forget to give your valuable feedback and comments for further improvements.
If you’re reading this post, chances are you’re interested in learning SQL and Python. And why not? These two scripting languages are in huge demand, especially for data science, marketing analytics, and business operations.
So, if you are really interested to learn SQL and Python, don’t miss your chance to sign up for freemium plans offered at Strata Scratch. Strata Scratch is glad to announce the freemium plans. Let’s find out what guides and exercises these freemiums include.
SQL Tutorials & SQL Guide
Basic and Intermediate SQL Guide
If you are an absolute beginner, you shouldn’t miss this opportunity. This guide is designed to offer you a basic to intermediate knowledge of SQL.
Additionally, this guide will contain various SQL problem sets specifically tailored for students and novices.
Advanced SQL Guide
Don’t be sad If you are an advanced learner, as Strata Scratch brings you freemium access to advanced SQL guide. This SQL guide is meant to help you grasp the advanced SQL concepts. Our Advanced SQL Guide also includes SQL Data Types, SQL Date Format, Data Wrangling with SQL.
Basic SQL Exercises 1
At Strata Scratch, we not only allow you to read out tutorials but also let you practice SQL exercises. We are pleased to announce that our Basic SQL Excercise 1 is also free for all users.
So, if you want to increase your data analytical skills, don’t forget to sign up for this Basic SQL Exercise. The exercise will help you test how good you are at basic SQL coding. In this exercise, you will be asked to answer the questions.
Note: For other basic and advanced SQL exercises you will need to upgrade to our premium plans. Since premium exercises are also affordable, you can access our monthly prepaid plan as well.
Python Guides & Problem Sets
Similar to SQL, Strata Scratch also lets you walk through the python datasets free of cost. Our first Python Guide helps you learn connecting to a database and query datasets using Python.
Cleaning Data in Python
Most of the data scientists spend their 80% of the time in cleaning and manipulating data. This free Strata Scratch course will teach you how to clean data with Pandas and Data Cleanup Excercise with The Titanic Dataset.
However, for SQL problem sets such as NumPy Tutorial, DateTime, Creating Visualizations, etc. you will need to have premium access. The good news is, even in the Practice Problems section, you will get freemium access to short Pandas Tutorial for Data Analysis.
So, if you are in search of an affordable online platform to learn SQL and Python online, don't let this once a year opportunity from Strata Scratch pass you by. If you have a premium account with Strata Scratch, you may use another email account to access easy to learn freemium guides and exercises.
For those who don’t know, data science is multidisciplinary, having a blend of statistical (data) inference, algorithm development, and technology. Today, data science has been used to solve a wide range of analytically complex issues.
Numerous businesses and companies across the globe have adopted data science to leverage robust mathematical techniques and improve decision-making skills in the workplace.
The brands like Airbnb and Amazon are good examples that assimilated data science into their services and products. It’s worth mentioning that data science helped them get a competitive advantage. There has been so much achievement that now every industry and department leveraging data science to help make right decisions.
In fact, it would not be wrong to say that data science is going to be the best career of the 21st century. At Strata Scratch, we help you build a career in data science. We help you enhance your analytical skills by offering you over 40 + problem sets of SQL and Python. We have more than 80 datasets and guides to improve your analytical skills.
Although there a number of tools available in the market that promise to help you with analytically complex issues, data science is something that you can’t buy as software. You may use this software to assist you but you must have a sound knowledge of data science as well.
Strata Scratch is an ideal platform to learn data analytical skills and become a data scientist. Whether you are an aspiring data scientist, student or professional who has to deal with a large amount of data every day, we can help you learn basic data programming.
It is true that the use of software reduces the need for hiring in-house analytical experts. But it is not going to be as effective as it should be for organizations where data science is the competitive advantage of the product.
Here is why it’s not possible to automate data science completely and still expect a positive ROI. The reason is data science is 80% data cleansing and 20% model building.
The initial steps of data cleansing are quite easy and can easily be automated. However, the next steps are more complicated and need deep domain knowledge of your industry. After all, it often involves dealing with feature section and formation of new proxy metrics that characterize your business.
The rest 20% of data science is building the model using mathematical equations. It is you who choose the building model according to your business’s issues. But once you have implemented your model, how would you know that if the output is good or not in comparison to other approaches?
Consequently, the human component is important in data science. After all, it ensures that the data model best represents your business.
You should invest in a product that helps you save time on low-value tasks but it is also true that you shouldn't’ completely rely on them to make high-impact decisions.
Strata Scratch lets you practice basic and advanced SQL and Python and improve your marketing skills. If you want to pursue a career as a data scientist, you may signup for Strata Scratch and start learning today!
Do you want your online business to succeed? If yes, it is important that you understand your data perfectly. Well, SQL or Structured Query Language can help you with that. This popular programming language is used to pull information from a database.
Though SQL can’t be used to create web applications, it can interact with the relational database systems built into many applications. Knowing how to use SQL lets you retrieve just any kind of data you want to know about your customers and business. When the SQL language has so many benefits why not learn it?
Strata Scratch is a well-known online platform where you can learn SQL and enhance your analytical and marketing skills to a great extent. At Strata Scratch, you can practice SQL and Python with more than 40 problem sets. Isn’t it great?
In terms of marketing and data management, SQL has many advantages over traditional data programs. Suppose you have an Excel Spreadsheet containing every bit of data about your customers such as what plans they are on, when they sign up, how often they purchase your product/service, what marketing campaign they see. In short, every action they take on your website and within your application.
With the help of SQL, you can utilize this data to cohort analysis and see if your targeted audience is using your product more or less over time, to examine different marketing campaigns, to see what actions your users are taking and to figure out the demographics of your targeted audience – that will help you in creating ad campaigns targeting similar demographics.
As business departments are becoming more data-driven nowadays, learning SQL is quite important. Here at Strata Scratch, we teach you the fundamentals of writing SQL queries to pull and process your data.
We have designed our SQL guides and exercises specifically for marketing and business applications. Whether you are a newbie who wants to start the coding right away or an expert eager to learn the latest perspective in data analytics, we can serve you. Additionally, we go through the real-world business and case studies to better understand data-driven analytical methodologies. In short, with us, you can rest assured that you will build your confidence in SQL and data analytics.
For most students, SQL could be among the easiest programming languages to look at because the codes read the same like regular English. You will often find the three magic words SELECT, FROM, and WHERE as the core in database querying. But later on as you progress, you will find more complex statements for joins, aggregations, case statements, and subqueries which can be intimidating for newbies and even intermediate learners.
The good news is that SQL shouldn’t scare you at all, especially for business and marketing students who don’t have a coding background. We have tailored our guides and exercises specific for business and marketing applications, hoping to help SQL newbies start coding right away or even experienced users of SQL who wants to learn a new perspective in data analytics.
What You Can Learn from the Tutorials
Learning and remembering the lessons are simpler when it is designed to be something intuitive. Our guides and tutorials aim to break the barrier of entry for non-technical or non-developer students and professionals who will find SQL useful in their career. We hope that new and intermediate learners will be able to master the fundamentals of database querying with a lesser amount of time.
SQL newbies are expected to learn how to use the keywords SELECT, FROM, and WHERE statements in manipulating data. These are the fundamentals of database management until you progress to the more advanced skills useful in data analytics.
To up your skills, you will then have to go through the intermediate level tutorials where you will be introduced to more complex statements and database manipulation techniques. Among the most important topics to learn are common operators for numerical and non-numerical data, how to sort data using the ORDER BY statement, aggregations, how to manipulate rows and columns, how to use GROUP BY with ORDER BY and HAVING phrases, and CASE statements.
Problem Sets and Exercises
The learning experience wouldn’t be complete without problem sets and case studies you can practice to apply your newly acquired skills. Instead of a generalized approach, we have designed our problem sets that tackle common problems encountered in business and marketing. Here, you will have to use your SQL and analytical skills to manipulate or retrieve data, make visualizations, analyze trends, and make a sound judgement based on your solution.
Our problem sets are continuously being updated to constantly challenge your skills! We have included questions that are related to common business problems, such as the Forbes Global exercises, French Employment Exercises, Hotel Reviews Exercises, Library Usage Exercises, QB Stats Exercises, Spotify Exercises, and Yelp Exercises. Case Studies are also available for the more advanced learners. Here, you can use any languages you like aside from SQL to answer open-ended questions. You can use all of these problem sets and case studies for your projects as well. Intermediate and even experienced SQL users can find these problem sets helpful for review and references.
We hope that through our tutorials and problem sets, we are able to help you build your confidence in SQL and data analytics. We encourage you to master our guides and exercises to ace in your business and marketing career.
Head over to our Educational content to find problem sets.
If you are new to data analytics, chances are you might have never heard about Google Colab before. In our Python exercises, we have introduced you to Jupyter notebook which is a popular open-source application where you can create and run live codes, visualizations and perform mathematical operations. However, we have discovered something better which will enhance your learning experience in Python. We have added Google colab as a tool for you to create and share Jupyter notebooks easier without installing anything. This free research tool has a lot of nice features that will interest both students and teachers, especially for sharing works related to machine learning and research.
Why Use Google Colab?
Google Colab is a cloud service created for research and machine learning education. It now comes with a GPU which is totally free. We have moved our Python exercises to Google Colab for convenience on both the students and the teacher. Since you can easily share and collaborate your work with others, you can improve your Python skills and easily use the available libraries for your applications. If you are used to working with Jupyter notebooks, you can easily upload and share them without any set-up required.
Google Colab can be used with common browsers, such as Chrome and Firefox. Since you don’t have to install any software to work on your codes, you can simply run your notebooks using the browsers of your choice.
All your notebooks will be saved in your Google Drive and can be shared like your Google Sheets or Docs. Your shared notebooks will include its full contents (code, text, etc.) except for the virtual machine and custom libraries you’ve used. If you need to share this as well, it is advised that you include the cells that automatically install and load the custom files needed for your application.
Another thing that’s great about Google Colab is that it supports both Python 2.7 and Python 3.6. So if you have previously worked on your code using any of these versions, you should be able to upload and run them without any problems. Most of our Python exercises support either of these two versions.
What’s the Difference Between Jupyter and Colaboratory?
We have already talked about the main features of Jupyter and Google Colab, but you may have asked what is the difference between the two. First of all, the creation of Google Colab was actually inspired from the open-source Jupyter notebook. Unlike Jupyter, Google Colab allows you to immediately run your codes without any installations required. It works like how you would upload and share your Google Docs or Sheets. Since it allows you to use the cloud service for free, you can take advantage of its GPU and computation capabilities for your projects, especially for machine learning. However, you cannot use it for applications that require long-running computations like cryptocurrency mining. This will automatically result in service unavailability. Google Colab is intended for interactive usage and if you need to continuously run your code for your project, you need to use a local runtime through Colaboratory’s UI.
Data analytical skills are important whether you are aspiring to become a data scientist or simply a student or a professional specializing a different field but somehow needs to deal with a large chunk of data. This page is the ideal place to start learning the basics about database programming and how to manipulate a massive amount of data using our platform. The steps below will first introduce you to SQL Lab and the basic functions you need to know to start using our platform effectively.
The SQL Editor
The SQL editor is a powerful tool that allows you to type SQL commands, build and run queries, create and edit your data, visualize results, and many others.
Accessing Public and Private Datasets
If you are a new user, you will see an untitled query tab on the left side of the page. Below the tab are configuration options which allow you to choose a database and dataset. A public schema dataset is uploaded by default for your convenience. It is composed of public datasets which you can use as a reference. However, the schema is read-only so you cannot make any changes to it.
You also have access to your own dataset repository under your private schema username where you will have full privileges, such as reading or editing your datasets. Under your private schema, you are given the freedom to move data from other schemas or upload your own CSV file.
Running the SQL Query
Next to the configuration sidebar is a workspace where you can type SQL queries. You can start with basic commands such as SELECT, FROM, WHERE, GROUP BY and ORDER BY. We will learn more about this in the next tutorial. For now, it is enough for you to familiarize the functionality of the SQL editor.
Visualizing Your Dataset
You can also have the option to visualize data and turn them into meaningful graphs.
Saving a CSV File
Now you have the CSV file saved in your folder, you should be able to open it using a compatible program installed on your computer (such as MS Excel) to view your dataset.
SQL Guides and Exercises
Our platform offers guides and exercises to help you with your journey in learning SQL. The SQL tutorials are designed for absolute beginners with no technical background in programming. The available guides discuss the basic and general concepts of SQL which covers the common syntax needed to get you started right away! We make sure that the steps are very easy to follow and comes with actual images to help you visualize the process. We have also prepared exercises to help you apply what you have learned from the tutorials. These exercises are composed of questions specific for business and marketing students. We hope that through our guides and exercises we are able to ease the barrier of learning SQL for newbies in coding and data analytics.
Nowadays, analytics is being considered as the core of every business. By gathering an immense amount of data from various business channels, we can get an insight into whether our marketing initiatives are indeed successful. The question is how can we turn these raw data into a form that can be understood by marketing professionals?
A few years back, database management has created a gap in the business and marketing world because professionals in this field are often not equipped with coding skills to manage database systems. Today, we are privileged to have access to tools that allow us to make our tasks easier.
StrataScratch is a platform curated to help business and marketing students or professionals make analytics easier even without advanced technical knowledge in programming. The platform is also equipped with features, such as graphical functions, easy-to-use SQL editor, and numerous datasets which you can use as practice or reference for your projects.
We have prepared a number of tutorials and exercises which you can use as a learning tool or a reference for projects. These contents are designed for both beginners and advanced learners. You can visit our website to gain access to all the materials needed to get you started.
Practice Problems for Business and Marketing Analytics
The best way to learn database coding is to actually apply what you have learned from the tutorials. To challenge your skills, we have prepared practice problems and exercises which you can try using our SQL editor. These problems are categorized as basic, intermediate, and advanced so that your learning experience becomes progressive.
The problems and exercises challenge your basic skills in SQL and Python which includes applying basic syntax to access, transfer, and manipulate data. Some questions will also require you to visualize the result for you to gain insights and be able to find an answer to the problem.
Python and SQL Tutorials
We have added more tutorials to enhance your learning experience in Python and SQL. For example, we have included topics that cover SQL techniques for business analytics, data cleaning using Pandas, lambda functions and list comprehensions in Python, merging dataframes for data analysis, NumPy, and many others.
Access to Exercises Written in Python and SQL
A lot of the exercises on our page are written in Python and SQL. For convenience, the exercises can be accessed through Google CoLab links and run using Jupyter notebooks. You don’t need to install any software since the code will run online. You may also have the option to download the files in ipynb format so you can open it offline using any compatible software installed in your computer.
Solve Case Studies with Any Programming Tools
We have included case studies about business, medical appointments, and machine learning for those who are up for more challenge. These case studies are designed with open-ended questions to test your analysis and judgment. Moreover, you are given the choice to use any of your favorite tools, such as Python, R, and Tableau.
How to Access our Guides, Problem Sets, and Case Studies
All our guides, practice problems, and case studies can be accessed under the Education tab of our website. Choose a category which you want to access to. This will lead you to our page with a list of available tutorials and exercises. Clicking a guide or exercise will open a new page. The guide contains the step by step tutorials about your chosen topic, such as how to use Strata Scratch and the basic tutorial on SQL. When you click on the exercises, a new page will open containing the questions linked to our Github and the solutions linked to our Google CoLab.
We hope you will find all of these materials and practice sets useful to enhance your data analytics skills. Enjoy!
If you’re a professional in the workforce, you’ve probably seen a cultural shift towards making data-driven decisions. If you’re a student, you’ve probably seen new classes teaching business and marketing majors new data analytical tools and coding languages. You don’t need us to convince you that new skills and capabilities are needed to stay competitive in the workforce, especially in business and marketing functions.
But which skills or capability do I need to learn to stay competitive? It’s been said that engineers have the technical skills necessary to analyze the data but don’t know how to ask the right questions. Business professionals ask the right questions but don’t know how to analyze the vast amount of data. The ideal case is to obviously find a person that can ask the right business questions and analyze the data.
So, again, which skills or capabilities do I need to learn? Almost all data these days are stored in a database. So you can learn any tool that can take data out of the database and analyze it. But most common tool/language is SQL but there are also other tools out there like python, R, and Tableau. Once the data is out of the database, you’ll need to put on your business hat to analyze the dataset in a meaningful way.
We have some guides to help you along your journey. You should get started right away!
Here are the some reasons why understanding databases and having data analytical skills are useful in business analytics:
Easily Access and Manipulate Data
As more and more data come on your way, there’s no better option than having a database system. Here, you can just pull out the specific information you need from a vast ocean of data. Simply type a query to get what you need – sounds more convenient, right? An SQL database keeps your data organized and speed up data processing. Having a database management system definitely makes your life easier!
Analyze Data with Only A Few Commands
There’s no easier way to analyze trends than visualizing them with colorful details! By adding the parameters you need and setting up the graphics command, your data instantly comes to life. In business, understanding trends is very important. You will be updated with new insights and come up with wiser decisions for your business operations.
Help You Support Prototyping, Data Management, and Reporting
With the advancement of technology, a lot of systems being used in businesses today are already automated. A few basic skills in SQL will help you understand the data and provide you the information you want to extract from the system. This in return makes it easier for you to create analysis and reports, as well as build prototypes for your projects or case studies.
More Opportunities in the Business World
As a business and marketing student or professional, having analytical skills allows you to gather insights from large sets of data. As large organizations continue to flourish, more and more companies use automated database systems to efficiently run business operations. Being able to navigate the vast amount of data will definitely help you answer complex business questions.
So, what’s next?
Learning SQL and other powerful tools/languages does not really require you to be a hardcore software engineer. All you have to know are the basic functionalities on how to select particular rows or columns of data, the basic mathematical operations to manipulate data, and some simple queries to visualize the information you have.
If you want to learn the basics of SQL, just go to our tutorial.
You will find an easy-to-follow guide with all the basics you need to start learning SQL right away. Moreover, Strata Scratch provides a user-friendly platform you can use to practice writing simple queries. The platform also provides sample datasets which you can use in designing your prototype or answering your case studies.
Happy analyzing! And if you have any questions, email us at email@example.com.
In the business world, data is everything. We use data to help us understand the market and our customer. Successful businesses are data-driven and integrate their data-driven decision making into their business processes. We’ve seen the continuous growth of the tech industry – think Facebook and Google – in part due to their data-driven approach to building and growing products.
Data itself has been democratized. Companies collect vast amounts of internal and external data. Data engineering and science teams are formed to help turn data into insights, and it’s becoming apparent that if you want to stay competitive in your career, you will need to develop enough technical capabilities to analyze large amounts of data using sophisticated and powerful tools beyond Excel.
How does a non-technical business and marketing professional build powerful analytical skills? Most books and tools are written by engineers for engineers. We, at Strata Scratch, understand this problem. It’s impossible to find resources tailored to the non-technical professionals – there are no tools easy enough for novices; there are no guides and exercises written for business and marketing professionals that also leverage these powerful tools.
We hope to help the new business and marketing professionals. We have a tool easy enough for non-technical novices to use, with SQL and Python guides and exercises tailored to the business and marketing professional. We’ll keep posting here with useful advice for the data-driven business and marketing professionals. We hope you follow along with us.