In your industry, you’ve been around the block, and then some. The value that your business acumen, experience, and domain expertise bring is immense. Yet, businesses are digitizing with increasing speed, especially since e-commerce is important for survival in a post-COVID-19 world. Therefore, you’ve probably thought about learning SQL – but as a busy mid-career executive, you wonder how you’ll fit this into your packed schedule.
Learning SQL mid-career unlocks opportunities
Having the right numbers to prove a point is increasingly key with the shift towards “data-driven” business decision making. Here are some of the business questions you can answer with SQL:
- What were the top performers for a particular category or market?
- How did your product perform vs other products in your company?
- Performance took a dip (or a surge). Which sub-category drove this change?
Some of these information may already be available in ready-made dashboards or apps. Yet, your message is more powerful with numbers that get right to that specific point – and fast. So, the flexibility to self-serve with data can bring you great advantages.
Who is this series for?
This series is aimed at people in business roles (strategy, product management, project management, retail, marketing etc). If your company is moving towards “data-driven” business methods, and you need to ramp up in SQL to populate your business presentations with data, you are my target audience! My goal is not to replace a good reference book, but to guide your focus towards the topics most relevant for business. Because most courses and books are targeted at aspiring developers, they tend to spend a lot of time on technical details. So with the help of this series, you can save time when learning and get to the most useful aspects of SQL for your role rapidly.
Survival SQL: Table of Contents
Here’s a list of all the posts in this series. By the time you get to post 4, you can write a query to pull business performance over time, for different business categories. Some of the subject matter in later posts belong to intermediate books but are important time-savers. Hope this material makes your SQL learning journey more relevant and smooth!
|Contents||Link to post|
|1. Basic query structure, choose a book||Using a beginner SQL book efficiently|
|2. Understand the key table(s) in your database||Your first SQL joins: Reading the “FROM” clause|
|3. Gain control over the data you want to pull||Filtering the data you want: The “WHERE” clause|
|4. Summarize your metrics into easy-to-understand groups||Aggregating metrics: Using “GROUP BY”|
|5. Create your own metrics and categories||Define your own metrics: Operators and conditionals|
|6. Troubleshoot situations when a simple inner join might omit or duplicate data||When to use more complex joins|
|7. Save time by sorting your data in SQL instead of Excel||Sort your data with “ORDER BY”|
|8. Automate Excel tasks involving calculations across rows (e.g. rank products by market, get moving averages) with window functions||Window functions: Automate lengthy Excel tasks|
|9. Solve multi-step problems using subqueries. Use common table expressions to organize your thoughts more clearly.||Subqueries and CTEs: Multi-step problems|
|Conclusion: Become a proactive partner to your business intelligence and data science teams||Take ownership of your data: The end-goal|
Kaggle notebook for sample queries
You can find all the code used in the examples in this Kaggle notebook. To access it, you’ll need to create an account with Kaggle, which is free. I chose to use Kaggle for all the examples because they offer free access to real-life datasets on Google BigQuery. This gives you the opportunity to practice with actual databases, instead of “toy” data.