It’s an absolute myth that you can send an algorithm over raw data and have insights pop up… NYT, Aug 2014
In-database analytics is just the tip of an in-database process iceberg. Supporting the analytics are vast, largely hidden data exploration processes. Roughly 75% of in-database analytics is data management and data mining; only 25% is analytics.
In-Database Analytics — Benefits
Incredible speed. The ability to accurately repeat analytics anytime. Providing instant visibility into shopping behaviors and empowering marketers to use data as competitive weapons.
Work efforts plunge from hours to seconds. Gone are data transfers across networks. Gone are data manipulations on workstations. Instead, the data warehouse handles data management. Analytical data sets are created at the source. And analytics complete in seconds, not hours. This part of in-database processing – the hidden part of the iceberg – is where analysts gain the greatest benefits.
In-Database Analytics — Challenges
In-database analytics require exhaustive in-database processing – drilling deep into transactions, and easily include several hundred million data rows.
In-house reporting tools fail at deep-dive analytics and create incomplete reports. So Marketers lose confidence in both reports and data.
Business managers traditionally relied on IT to provide the analytic systems. The broad constituencies IT supports led to massive, general-purpose solutions…. These solutions resulted in tremendous frustration for the business manager in need of answers. — HBR, Oct 2015
Another challenge is that business analysts aren’t trained in in-database processing or in deep-dive analytics; they can’t manage complex data structures, or disparate data sources. So analysts create inappropriate or error-filled analytics. And again marketers lose confidence in both the analytics and the supporting data.
In-Database Analytics — IDP
With IDP, marketers control their data, their analytics and their marketing technology. Marketable analytics require accurate supporting data. But we know that your data will be challenging, and that you have limited resources.
We remove the requirement that business analysts manage large data volumes or complex data structures — bridging the gap between data management and analytics — so analysts focus, not on data, but on making recommendations from the analytics.
At IDP, we manage large data volumes with complex structures and we integrate disparate data sources. We build rock-solid analytical data sets. And we always collaborate with marketers to generate the right methodologies that produce actionable results.