Building A Million Dollar Data Analytics Service

Some companies focus 100% on selling data insights.

I’m not talking about vendors that promise you self-service analytics without telling you how much work it will take to get you there. I mean companies that take raw data and provide metrics, machine learning APIs, and insights on the other side. Hundreds of these companies exist and they exist in every industry.

Dental analytics, Gaming (casino) analytics, healthcare, insurance, HR, etc, etc, etc.

These companies can often make 7, 8, and 9 figures easily, and you don’t even know they exist.

Over the past few years, I have worked with well over a dozen of these companies, either as an employee, a customer, or a consultant. Since these companies are so prevalent and I imagine some of my readers may be considering starting said type of company, I wanted to provide some advice on how to best do it.

So let’s discuss some of the key points when starting a third-party analytics provider.

Ingestion - How in the World Are You Getting the Data

Now, if you’ve worked in data engineering for over a few months, you know the concept of ETL or ELT. When you work for a single company, this generally means you only need to pull data from a few sources, and only one to maybe a few instances of each source (considering you might be pulling from multiple instances of workday or Salesforce depending on how your company is set up).

The point being that this is very different when you work for a company that is a third-party analytics company.

Because instead of a few data sources, you’re likely dealing with 50, 100, 1,000, etc. companies who all are sending data to you, and this is the first place where you can easily make mistakes.

You can get your customers' data into your system in a few ways:

• Directly connect to their data sources (really only works with Saas)

• Require files to be sent to an SFTP

• Use shared data platforms like Snowflake/Databricks