Here is my answer to this FAQ: It's not so hard to find sample data and data sources to use for interesting side-projects, or just for practicing writing SQL. In-product sample data Most DBMSes come with sample databases. You can write lots of interesting queries against them, and usually a tutorial accompanies the database in the documentation. Documentation for Microsoft SQL Server's samples ** Microsoft's sample database GitHub , which includes the Contoso database For MySQL: there's the Employees sample database and the Sakila sample database For PostgreSQL: there are several sample DBs in the PostgreSQL wiki a GitHub repository with a collection of PostgreSQL samples from the old pgfoundry site Oracle publishes a manual section about there sample databases Some websites are full of sample data sets. Why not download an interesting one, learn to load it up, and write your own interesting queries? Dataset Websites There are many websites which host data sets. Kaggle.com is full of sample data! FiveThirtyEight.com has lots of neat data sets The github awesomedata repository has a collection of interesting data sets Wikipedia has a list of datasets for machine learning research Third-party sample data Of course, some sample data is built for generic tutorials, by third parties: SqlSkills.com publishes sample databases for SQL Server, which include some corrupt databases so you can practice recovery operations SQLTutorial.com's Sample Database is available for sseveral vendors Practice Sites There are some sites that let you write queries interactively with canned data, rather than having you download data to play with on your own. I haven't used it, but I've seen people recommend SqlZOO.net LearnSQL.com has a blog post called " Learning SQL? 12 Ways to Practice SQL Online " with lots of resources. Sylvia Moestl Vasilik's website (which supports their book) has almost 60 practice problems. Regular dumps Some sites publish data by making their backups available, or dumping the data they use to make their own reports. Wikipedia publishes all of the content of Wikipeida as SQL scripts for MySQL, plus as XML files. You can get that data (or subsets of it) and play around. StackOverflow makes their developer survey data sets available each year. Some governments make data about the city and its residents available openly: London Open Data New York City Open Data Seattle Open Data Tokyo open data (in Japanese, obviously) Find open data at data.gov.uk Live data sources Some data sources produce data live, as it happens. These are itneresting sources becaue they usually represent slowly changing dimensions, and will need to be accumulated or logged before being stored or processed. Wikipedia Event Streams can show edits that are happening on Wikipedia, as they happen. The TWitter API provides a way to stream a subset of all tweets in realtime. GTFS data is provided by many metropolitain areas to describe movement of their transportation infrastructure; where are scheduled busses and trains right now? In the New York City area, the MTA provides GTFS data . You can find GTFS feeds for Seattle , and their live data through other APIs . Tokyo (and other municipalities in Japan) have hosted transit data challenges to encourage use of their data. Some games make gameplay data available in realtime. SuperCell's Clash Royale , for example, has a gameplay API . Finding more There's data everywhere! If you don't like these sources, you can try finding other data sets. Once you know the protocol or format, search for it! The OneBusAway API and GTFS protocols are about public transportation data, so earch for "GTFS Data {YourCity}". Search for APIs for your favortie game or game server. GitHub uses tags for search, so try #sample-databases , #opendata , or #datasets . What other tags can you find? More on reddit.com

SQL Basics W3's SQL Tutorials SQL Server Tutorial SQL Zoo Tutorial Stack Overflow Query SQL Server Oracle Live SQL server [Oracle's Dev Gym for SQL] ( https://devgym.oracle.com/pls/apex/f?p=10001:20011::::20011 ::) Oracle Tutorial Coursera MySQL SQL Exercises W3's SQL Exercises The SQL Mystery Solving Exercise Selectstar SQL Exercises Leetcode's SQL Exercises Hackerrank's SQL Exercises PG Exercises in PostGreSQL Interview Query Exercises Stratascratch Exercises SQL Educational Videos and Programs SQL for Data Scientists FreeCodeCamp 4 hour SQL tutorial FreeCodeCamp Relational Database Courses Database Security Cornell University, Introduction to Database 25 hours Database Systems Research Group Advanced SQL series Brent Ozar Unlimited SQL The SQL programming language was developed in the 1970s by IBM researchers Raymond Boyce and Donald Chamberlin. The programming language, known then as SEQUEL, was created following Edgar Frank Codd's paper, “A Relational Model of Data for Large Shared Data Banks,” in 1970. IBM invented Relational Databases and SQL. IBM SQL Certificate Programs (IBM Programs range from hours to months to almost a year to complete) IBM Data Analyst Career Guide IBM Data Scientist Career Guide IBM Beginner Certificate Programs IBM Intro to Relational Databases IBM Intro to Data Analytics IBM Intro to Data Science IBM Data Engineering Foundations program IBM Data Analyst program IBM Data Science program IBM Applied Data Science program IBM Data Engineering program IBM Data Warehouse Engineering program IBM Data Science with Python & SQL specialization program IBM Data Analysis Visualization program IBM BI Foundations with SQL and more program IBM Data Analysis with R IBM Intro to R programming IBM Applied Data Science with R specialization program IBM SQL for Data Science with R program IBM Developing Applications with SQL and more program IBM Data Analytics with Excel and R program IBM Intermediate Certificate Programs IBM Intermediate Data Analyst Capstone IBM Intermediate Applied Data Science Capstone IBM's Sole Advanced Certificate Program IBM Advanced Data Science program College-Level Notable SQL Programs Duke University's Python / SQL course. UC Davis Learn SQL Cloudera Big Data SQL CS50 All this. This should keep you busy and ranges from training, to education, to practice and all in between down to security. Then there's the gamut of Python you might want to know atop this. So Dr. Chuck's aka Charles Severance Python for Everybody. Python For Everybody Python for Data Analysis: Pandas & NumPy Also, one more thing... OSSU's Data Science Degree equivalent program Open Source Society List of classes to take to learn advanced data science. OSSU's Computer Science Degree equivalent program And Open Source Society's list of classes in computer science. More on reddit.com

That’s a great list of skills, I have about ten years in database analysis and reporting and that sums up 90% of the SQL I use day-to-day. I might suggest other tech integration in addition to SQL itself.

SQL wise, LAG/LEAD, windowed functions, soundex is interesting and I’ve used it in customer comparisons, dynamic SQL, PIVOT/UNPIVOT, read through and optimize some explain plans.

You may want to explore administration and architecture to round out your skills; creating roles and security, standing up a new database, SSIS for bringing in data and SSAS to create cubes, creating database diagrams, building keys and enforcing referential integrity.

Integrate with other technologies; bulk insert from Excel files, utilize some Python or JSON within the newer MS SQL instances, connect to a report tool like PowerBI or Tableau.

Courses are great to introduce you to concepts but I always recommend personal projects to retain that information. Sometimes the best learning I’ve done is troubleshooting something in my own project instead of clicking through a curated tutorial. Take some free or public data or scrape something your interested in then stage, analyze, and display it.

High salary developers not only have the technical skills but can turn that into business application; finding or taking data, doing some analysis of it to answer or explore business questions, and then display it in a way people can use it.

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The goal of /r/SQL is to provide a place for interesting and informative SQL content and discussions. More on reddit.com