Introduction and use cases — A large portion of any data-related job is data cleaning but often times writing SQL statements can be tedious, especially coding the same SQL logic over multiple columns in a table. This is until I discovered I could create user-defined functions (UDFs) in BigQuery to meet my specific data cleaning…

And how to use them — As a long-time SQL user, I’m always looking for ways to make it easier to analyze data with SQL. In a previous article, I reviewed 6 BigQuery SQL functions I wish I had known earlier, and today I want to share 4 more functions I hope you’ll find useful. 1. PERCENTILE_CONT PERCENTILE_CONT…

An introduction — As a long-time SQL user, I’ve often had to run the same code over and over with minor changes in my where statement. In programming languages such as Python, this copy and replacement wouldn’t be necessary because I could create a function to pass in different parameter values to rerun…

Use cases and functions to apply — Data cleaning is an essential part of any data-related position whether you’re a data engineer, data scientist, or data analyst. Today I want to share a few BigQuery SQL functions for data cleaning and a use case I would’ve used them for. Invisible Special Characters In String Values String values can contain special characters that don’t…

Check if your database has them too — In my previous article, I discussed 4 BigQuery SQL shortcuts that can simplify your queries. Since then I discovered 6 more useful SQL functions I wished I had known earlier and that I’d like to share today. 1. GENERATE_ARRAY The GENERATE_ARRAY function allows you to create an array with a start and…

Check if your database has them too — The most common advice when you start learning SQL is to practice the basic statements because they’ll work across multiple databases. The downside is you may never discover database-specific syntax that can simplify your queries because there’s never any need to read the documentation. …

What’s a data mart and why data scientists should use one — As a data scientist, you can spend up to 80% of your time cleaning and transforming data in order to generate actionable insights and build machine learning models to create business impact. Now imagine a world where you can spend more time on analysis and model development instead of cleaning…

A marketing case study — In a previous article, I discussed reasons why your dashboards are ignored but how do you decide if you should create a dashboard or an ad hoc report for stakeholders. …

And what to do instead — When I first became a data analyst I made my fair share of mistakes dealing with stakeholders. Today I’d like to share my experience and what I learned to give you a head start on how to work effectively with your stakeholders. 1. Don’t assume stakeholders know what they want I was once asked by a stakeholder to…