7 Reasons Why You Should Consider a Data Lake

7 Reasons Why You Should Consider a Data Lake - A data lake doesn’t need to be the end destination for you need data. Data is constantly flowing, moving, and changing its form and shape.

Data warehouses have long been the standard approach to managing Big Data, but are data lakes more suitable for your needs? Here are seven reasons why the answer is yes.

With the volume, velocity, and variety of today’s data, we have all started to acknowledge that there is no one-size-fits-all database for all data needs. Instead, many companies have shifted towards choosing the right data store for a specific use case or project. The distribution of data across different data stores brought the challenge of consolidating data for analytics. Historically, the only viable solution was to build a data warehouse — extract data from all different sources, clean and bring it together, and finally, load this data to polished Data Warehouse (DWH) tables in a well-defined structure. While there is nothing wrong with this approach, a combination of a data lake and a data warehouse may be just the solution you need. Let’s investigate why.

Why You Should Create a Data Lake

1. Building a Staging Area for Your Data Warehouse

2. Audit a Log of All Data Ever Ingested Into Your Data Ecosystem Thanks to the Immutable Staging Area

3. Increase the Time-to-Value and Time-to-Insights 

4. A Single Data Platform for Real-Time and Batch Analytics

5. Costs

6. Convenience

7. Future Proof

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