Discover more from Three Data Point Thursday
In Case You Missed It: September 2023 Recap
How To Evaluate Hot Data Trends; Why People Are Lying To You About Big Data; The (Not So Subtle) Art of Not Giving A Fuck About Data; Analytics Engineering (NOT DBT!) 101.
This is the Three Data Point Thursday, making your business smarter with data & AI.
This special in-between issue serves as a recap of the last editions and more of my writing. It features a few quotes from each piece so you can get a feel for them and quickly jump around the Three Data Point Thursday universe.
F*ck best practices, data quality, data/ML teams, adversity, BI & Analytics, Data as Product, data & what to do instead.
“In over a decade in data, I've cared deeply about data projects, decision-makers, and machine learning algorithms. Sometimes, I've decided to say fuck it, I didn't give a fuck about best practices, projects, or people. These decisions made all the difference.”
We need to get comfortable with the idea of genAI for videos. Synthesia is a great example of what is coming to all of us, yet our fear of AI still blinds us. Watch this video to learn everything you need to know.
“While Tristan Handy, the Fishtown Analytics gang, and DbtLabs might’ve invented the term analytics engineering, analytics engineering today, per se, has nothing to do with this specific tool.
We think it’s most helpful to think about analytics engineering as an organizational change.
To be clear: Just because you have dbt doesn’t mean you’re doing analytics engineering.
Why? Because analytics engineering is about bridging a gap in communication between analytics and data engineering. That’s a people problem, not a tech problem.”
“So what? So, how do you then deal with data trends?
Never ignore a trend because it affects multiple organizational units; all do.
Rate each trend based on the number of affected units + where they sit on the tech vs. processes spectrum.
Then simply try them out if you feel your company is ready!”
“So what? Well, there are three ways to get more value from data. And big data is where it’s all headed.
The three only ways of getting more value out of data:
Getting more data (tap more sources)
Getting more value out of the data you already have (the stuff you have lying around)
Selecting more value-rich data pieces.”