Over the past several weeks, Mike and I have been talking to various CIOs, data scientists, software developers and business analysts in financial services, insurance and mortgage companies. It’s been extremely interesting to hear what challenges these people are facing in their daily jobs. Here’s some of the consistent feedback:
- There is some value to be had out of the standard reports from their existing applications, but top management is coming to expect more and more.
- CIOs are becoming more relevant again the enterprise. Infrastructure is a very basic requirement in the modern company, and CIOs are being asked to pursue the “I” in CIO – namely Information. How can we get more information from our assets?
- One of our hypotheses, that disjointed data is a challenge, has been validated by everyone we’ve spoken with. At literally every single company we’ve talked to, there are multiple systems for specific business processes that aren’t integrated or connected, and each system has a partial view of the data.
- Most companies still don’t know what exactly they want to try to learn from their data. In and of itself, this is a problem. It leads to a bit of “analysis paralysis,” where companies aren’t even acting. At least in a data warehouse scenario, they can work backwards from their targeted report to figure out the data they need, from what systems, and reverse engineer the necessary ETL.
- But again, most don’t even have a clear view of that report. And without a clear view, many are a bit concerned about acting too quickly to implement a system, for fear that it will need to be changed to accommodate new reports, data types, etc as they move forward.
Getting all the data together is one of the first steps that these companies are looking at, in order to start becoming data-driven organizations.
Just as integrating applications is tricky under the best of circumstances, integrating data poses its own set of challenges.
Data comes in different shapes and sizes.
This is part of what makes it hard to bring all the information together? What format should it take? Do we use tables with rows and columns? Multiple sets of tables?
FlockData looks at this challenge differently.
By handling data in a near-native, context-aware modern approach, we can use technologies like NoSQL and JSON to let the data describe itself. This helps businesses solve the problem of getting the data together. Bringing data together the foundation for answering questions based on your data.
If you want to know how FlockData can help you, just drop us a line anytime.