I am Back ! Yes, I am back (on the track) on my learning track. Sometime, it is really necessary to take a break and introspect why do we learn, before learning. Ah ! it was 9 months safe refuge to learn how Big Data & Analytics can contribute to Data Product.
Data strategy has always been expected to be revenue generation. As Big data and Hadoop entering into the enterprise data strategy it is also expected from big data infrastructure to be revenue addition. This is really a tough expectation from new entrant (Hadoop) when the established candidate (DataWarehouse & BI) itself struggle mostly for its existence. So, it is very pertinent for solution architects to raise a question WHERE and WHY to bring the Big data (Obviously Hadoop) in the Data Strategy. And, the safe option for this new entrant should the place where it supports and strengthen the EXISTING data analysis strategy. Yeah! That’s the DATA LAKE.
Hope, you would have already understood by now the 3 Ws (What: Data Lake, Who: Solution Architect, Where: Enterprise Data strategy) of Five Ws questions for information gathering. Now look at the diagram to depict WHERE and WHY.
Precisely, 3 major areas of opportunity for new entrant (Hadoop):
- Semi-structured and/or unstructured data ingestion.
- Push down bleeding data integration problems to Hadoop Engine.
- Business need to build comprehensive analytical data stores.
Absence of any one of these 3 needs above would make Hadoop case weak to enter into the existing enterprise strategy. And, this data lake approach believes to be aligning to the business analysis outcomes without much disruption, hence it will also create comfortable path in the enterprise. We can further dig into Data Lake Architecture and implementation strategy in detail.