Big Data became a buzzword around 2012. It refers to datasets so massive, so fast, and so unstructured that traditional databases literally break when trying to process them. We're talking about petabytes of information. We're talking about recording every single mouse movement of a billion users simultaneously.
That is Big Data.
Your Shopify transaction history? Your HubSpot contacts list? Your Google Ads export?
That is Small Data.
I don't say this to minimize your business. I say it to liberate you. "Small Data" is fantastic. It fits in your RAM. It can be queried in milliseconds. It costs pennies to store.
The problem is that when you treat Small Data like Big Data, you introduce Complexity Debt.
The High Cost of Resume-Driven Development
Why do companies build these over-engineered stacks?
Often, it's what we call "Resume-Driven Development." Engineers (and consultants) love building complicated things because it looks great on a CV. It's fun to spin up a Kubernetes cluster. It's boring to write a simple SQL script.
But for your business, complexity is a tax.
- It's expensive: You are paying for compute power you aren't using.
- It's fragile: A system with 20 moving parts breaks 20 times more often than a system with two.
- It's slow: I've seen teams wait days to fix a pipeline for a report that could have been automated in Excel.
If you are building a Ferrari engine to drive to the grocery store, you aren't going to get there faster. You're just going to spend a lot more on gas and maintenance.
At Hard Refresh, we believe in the "Minimum Viable Stack."
If your data fits in a spreadsheet, use a spreadsheet (with some governance). If it's getting too big for that, use a simple SQL database. If you have multiple sources, use a lightweight cloud warehouse like BigQuery or Snowflake-but turn off the bells and whistles you don't need.
You don't need real-time streaming if your marketing team only checks the dashboard on Monday mornings. A daily batch update is fine. It's reliable. It's cheap. And it never breaks.
Your Competitive Advantage
Someone like Google has to deal with the headache of Big Data. They have no choice.
You have a choice. You can be agile. You can move fast. You can answer business questions in minutes, not weeks, because your data isn't trapped behind a wall of unnecessary engineering.
So, stop trying to be Google. Be you.
Focus on the insights, not the infrastructure. Because at the end of the day, your customers don't care if your data pipeline uses Apache Kafka. They just care if you know who they are.