Martyn Richard Jones
San Luis Obispo 16th April 2017
Taking a Pop at Traditional Data Warehousing
Pitch: I recently read a report from a data visualisation company on the “Top Ten Big Data Trends for 2017”. This is what they told me “Hadoop is no longer just a batch-processing platform for data-science use cases. It has become a multi-purpose engine for ad hoc analysis. It’s even being used for operational reporting on day-to-day workloads—the kind traditionally handled by data warehouses.”
Reaction: Complete and utter nonsense. There is no way, shape or form that Hadoop (DFS and MapReduce) could realistically or viably replace workloads of the kind traditionally handled by data warehouses”. Unless of course they weren’t using a traditional data warehouse in the first place.
Analysis: I am in the business of ensuring that data warehousing is done for all the right reasons and that there is a rigorous application of “what works” at every step of the data warehouse process. So, any abject and shallow nonsense that is thrown into the arena and that makes my life harder is not going to be welcome. When added to the gushing and byzantine tripe about other data related fads, such as data lakes and deep-learning and predictive analytics, it just compounds the inane totality of the whole queered pitch.
Outcome: Acquired aversion to anything this vendor has to pitch.
Many thanks for reading