Daniel Lawson

Right off the bat I can tell you that I’m not your average data analyst. I’ve spent most of my career running my own business as a photographer and videographer, with a sprinkling of Web Development and SEO work as well. My approach to life and work is very T-shaped, in that I have a small set of specific skills complemented by a very broad range of interests; I like to think of myself as a dedicated non-specialist. Data Analytics, and Programming, started as a hobby that quickly grew into a passion.

The more I leaved the more I looked for opportunities to pull, manipulate, and join data from disparate sources in my life. I learned to interact with REST APIs for services I used, personal data from services I use like Spotify, and health data captured by my devices. I learned SQL to create and query databases, as well as analyse SQLite files containing my iMessages and Photos data on my Mac. Every technique I learned opened up more possibilities; now I’m hooked and there’s no turning back.

Every Data Analyst Should Learn SQL: My Experience

Every Data Analyst Should Learn SQL: My Experience

SQL is essential for working with large datasets and performing tasks that may be difficult or impossible with other tools. In one project, I used SQL to quickly analyze a table with 74 million rows, cutting the task time down from hours to seconds. Here I share my experience with using SQL in my work and why I believe it is an important skill for data analysts.