What Should Have Happened Vs. What Actually Happens
Back to the original point. If data scientists don’t have the right data that’s easily accessible, then an analytics project will most likely fail, and honestly, data scientists become a huge overhead.
Here are my three guiding principles to making your next analytics project a success:
1. Make it easy for business and IT functions to access data
Jeff Bezos infamously had a mandate in 2002 that forced every team to expose their data and functionality through service interfaces, as well as designing each interface to be consumed externally.
Amazon, an online bookstore company at the time, essentially kickstarted the entire cloud movement by allowing third-party developers to use Amazon’s internal services (AWS, S3, etc) for their own business.
Every executive meeting I have, one of my first points I stress is a change in how the company views data. Either you make your data easily accessible by IT and Business or you will have a hard time succeeding.
2. Make the data usable
For the executives we interviewed, their teams struggled to create any value from the data simply because they couldn’t get the right systems data into one central location.
The reason data lakes and data warehouses have grown in importance in many organizations is because they solve a massive problem that enterprises face every day: It is hard to centralize data because of the amount of data, various types of data (structured and unstructured), and how long it will take teams to ingest, cleanse, and transform the data for every single source.
3. Get traction by focusing on a single use case
If an organization is new to data engineering and analytics, waterfall-style project methodologies are your worst enemy. Value should be proven in three months, not 18.
My recommendation is to focus on tangible business use cases for reporting and predictive analytics. Examples:
- Build a report that tells me which doctors and which regions prescribe the most opioids.
- Tell me which locations we should open up retail branches in. (Based on market research data, financials, geographics, etc.)
- Predict which patients will be readmitted to the hospital within 15 days.
Build your projects/proof-of-concepts around individual business use cases. You should have a clear idea of simple use cases before you start trying to transform the entire organization.
Start small and get quick wins.