Reading From The Data Lake

Bill Vorhies discusses technologies to analyze and use data in a data lake:

So the takeaway that many DB developers would have you believe is ‘Hadoop Good’, ‘RDBMS Bad’.

But wait.  RDBMS EDW hasn’t gone away and won’t. That’s where we keep our single version of the truth, the business data that record legal transactions with customers, suppliers, and employees.  We also get strong SLAs, strong fault tolerance, and highly curated data based on strong ETL, provenance, and governance.  Those are all things that are missing in our Data Lake.

Anybody who sells you on one technology to solve all problems is shilling snake oil.  Bill’s answer is an Adjunct Data Warehouse, which sits separate from the Enterprise Data Warehouse.  You go to the EDW when you risk getting fired or going to jail if the data’s wrong; you go to the ADW when you need data not in your EDW, or when you need larger-scale analytics in which it’s okay to be 1% off.

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