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Learning SQL, Part 1 - Setup Your Environment

I’m often asked how accessible SQL as a programming language is for those looking to build Data Analytics or BI skills. My answer is always very! I’m of the belief that anyone with the interest can learn SQL. The next question is often where to start, I’m hoping this will help. This is the first article in a series where I’ll be walking you through the basics of SQL in short articles. Articles in this series:

Installation and Setup

If you do not have a personal SQL environment setup on your PC, I highly recommend doing so. It will allow you to follow along with the examples and have a place to practice and develop your skills (where you won’t screw up your company’s production environment!). The basic steps are as follows:

  1. Download SQL Server Management Studio (SSMS): SSMS is the tool we’ll use to query our database. It’s used to interact with the database and is an interface to do thing such as create tables, load or modify tables, and most importantly for this series - write SQL queries to retrieve data. You can find more information on how to install SSMS here.
  2. SQL Server Developer Edition: SSMS just interacts with a database. In order to setup the actual database instance on your PC, you need to get a SQL Server up and running. Luckily for us, Microsoft offers SQL Server Developer Edition, which is perfect for the job (and free!).
  3. Datasets to interact with: You’re company will likely have data already populated, but for these exercises we’ll use sample data from the AdventureWorks Dataset. You can download the 2017 “bak” file DW download here.

I’d recommend going through the installation instructions for #30DQUERY by Alex Powers (and check it out in full if you’re looking to learn Power Query and M). He walks through in a better way than I could how to get your setup up and running and complete the above steps.

That’s it for Part 1. Future articles will walk through the language and how to pull data using SQL!

Check out these books I recommend for learning Data Analytics and Power BI: