Every budding data professional would do well for themselves if they learned SQL. This is true for professionals in any field who deal with reports, metrics, numbers, information stored in databases, have to take decisions based on A/B tests or dashboards. Yes, this is a vast set of people and learning SQL will serve them well as they grow in their careers.
I've written about SQL being a superpower on LinkedIn and I continue to advocate that the learning investment into pickup up SQL skills will pay rich dividends both in the short and long term.
SQL is everywhere. From databases that we are all too familiar with such as Oracle, MySQL, Postgres to Big Data offerings such as Hive, SparkSQL, Presto, Redshift, Athena and BigQuery to name a few.
And increasingly companies are investing heavily into developing SQL as the primary interface to enable domain specific Analytics and even Machine Learning.
Imagine being able to do time series analysis and forecasting without leaving SQL. Timescale is a database that has developed time series specific functions and features to make time series analysis fun and easy. Check out their tutorial on time series forecasting here.
SQL also lets you do Machine Learning. Google's BigQuery supports training of ML models. Check out the list of ML models you can train by writing SQL in BigQuery.
As you can see SQL is a gateway to access the ability to carry out both simple and advanced analytical tasks.
Cloud providers today are making available large datasets for you to query using SQL. Check out the list of public Cryptocurrency related datasets on Google Cloud.
I have been dabbling with analyzing the BTC blockchain data and have some case studies available on https://sql.recipes which you can use as a starting point to carry out your own analyses into your favorite cryptocurrency of choice.
I hope this post has kindled in you an inclination to learn SQL. If you are already familiar with SQL I hope you redouble your efforts with SQL.
In the next post I'll show you how you can get started with a CSV file from Kaggle and a simple SQL tool to run a few queries, all within a matter of minutes.