Today’s lineage that reflects the “current state” of your solutions might be beautifully represented, but what about lineage for yesterday? …or last week? How about last quarter or a specific date from last year? We have all had the experience where an analyst with their hair on fire comes running into the office and needs to know “Where did we get our revenue results from Q3 of the last fiscal year?!”
As we modernise our client server architecture how can we ensure that we understand and deliver exisitng data requirements?
Date lineage is increasing important to business users looking to understand and trust data. Yet tradtional solutions provide incomplete and inaccurate results
Andrew C. Oliver’s (@acoliver) recent post “How to create a data lake for fun and profit” is an interesting take on the value of a data lake – an unstructured data warehouse where you pull in all your different sources into one large “pool” of data. In contrast to data marts and warehouses a data lake…
