In my last blog I talked about why you need a Data Lake. Now I’m going to share a few helpful steps on this journey and highlight some “gotchas” to avoid.
Step 1 - Feed the Lake
Understand all the data needs of your company/customer. If you don’t have the data, you are dead in the…wait for it—yes, I’m going there since we’re talking about data lake—water.
I can’t count the number of times I’ve requested data only to find it was missing an integral column in: Quotes, Billings, Bookings, Install Base, Contracts, Logistics, Case Management, Headcount, Expenses, Web traffic, Mobile, Telephony, Training, Industry data, DUNS….
With the data lake I finally have a place to ask questions about my business where I can see what is happening end to end without having to use 10 different BI tools.
- Mistake #1: Don’t structure the data into what you think they need. Feed all the data, structured and unstructured. If not, you will always be asked to feed more and paying by the drip is expensive. Also, your customers will always be unhappy and work around your expensive data ingest model by using shadow solutions.
Step 2 - Care for the Lake