Data assembly is now the biggest barrier to good analytics
Business Intelligence continues to become more and more strategic to companies in order to compete in today’s global economy. Every department is now using analytics to better understand financials, business processes, customers, competitors and market trends – critical understanding needed to optimize execution.
As we all know, analytics is no better than the data behind it, and thus discovery and assembly of data has become an ever more important part of successful business intelligence.
As your company ecosystem grows beyond your firewall into partner apps, competitor websites and social networks, data rapidly spreads and more and more data assembly is now tied up in manual harvesting methods or the purchase of dubious data from vertical information providers.
This means that the knowledge worker spends more time with Data Discovery and Data Assembly, leaving less time for analysis of and execution on the results.
I often see scenarios where knowledge workers spend more than 50% of their time on just data assembly, time which takes away from analysis, reporting and execution.
This is not good.
And it’s exactly why more companies rely on automating the data assembly process. Finding methods to easily and scalably instruct which data to get from where and how to transform it into the needed format – basically they look for a solution to do automated data delivery.
The good news is that this solution already exists. The Kapow Katalyst platform is proven by more than 500 companies all over the world.
Here’s a concrete example. Fiserv, a large financial services company, needed to understand the value of their assets in real-time for compliance reasons. To solve this problem the treasurer hired a group of people to manually log-in to Fiservs accounts spread over more than 300 banks in more than 20 countries. This was expensive, error-prone, and data was often outdated.
Consequently, Fiserv looked for an automated solution and found Kapow Katalyst. Within 3 months they had built Kapow ETL robots that could automatically log-in to the web front-end of Fiserv accounts at all 300 banks and pull out the required information. Not only did this relieve the knowledge workers from manual data assembly it also gave the treasurer real-time data for point-in-time regulatory compliance.
Needless to say this created a lot of value for Fiserv.
By: Stefan Andreasen