So you’re a marketer, product manager, or data scientist? Chances are you need to analyze data at work. And you need to know SQL. The language has always been popular among data engineers and data scientists and is the most mentioned skill on job sites. It’s becoming a required skill for marketing and product management. Almost all tech companies, like Google, Facebook, and Uber, interview for these skillsets. Learning even the basics of SQL can give you an edge in the job market.
We have over 300+ questions from the top tech companies like Facebook, Lyft, and Airbnb. These questions are specific to help prepare you for marketing, product management, and data scientist interviews and work.
Learning SQL with Strata Scratch
Our SQL course begins with the basics of the language and has been divided into three categories -- basic, intermediate, and advanced SQL guides.
The basic guide helps the students to get started with SQL. The guide is accompanied by datasets that provide a more hands-on-experience where students can code live with tools that are used in the industry.
The intermediate guide is meant for students who already know the basics and is also appropriate for beginners who need a reference when coding. Whereas, the advanced guide includes a more practical knowledge of SQL, from writing Subqueries in SQL to SQL data types to data wrangling to using SQL strings and much more.
The lectures have also been divided into three levels- basic, intermediate, and advanced. The basic SQL lectures comprise of
Using the SQL modules to improve your SQL skills
The modules are user-friendly, so once you become part of the Strata Scratch, you simply need to login and click on the SQL exercises, where you will see the following screen.
Educational tracks for all levels
We have provided solutions for all the questions. The solution will run on our platform to provide you with an answer to the questions given in the exercises.
Random Question Generator
Get started now with the free exercises
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.