The data synthesis challenge: How to integrate and analyze scattered enterprise data

By Jonathan Hassell

Every business has data. Organizations everywhere are accumulating terabytes of data every single day. You might even have a fair claim that the world is drowning in data. Not only is the data generated by general business interactions and transactions, but the IoT is allowing sensors and other tools to remain connected to the internet, always transmitting information in a constant stream. This rich corpus of data presents opportunities, but it does not come without challenges — one of which is data synthesis.

One of the problems with having all this data is that it’s scattered across so many different places. Business systems store data in silos, so your line-of-business application has a database, your HR department has a database and your self-service machines have a database. However, rare is the organization that has built the glue in between these services and products in a way that meaningful data can be gleaned after the fact. Often, organizations are thrilled enough with simple integrations, such as populating customer data into a sales application or transferring employment information automatically from an HR system to a directory service. Yet they look past the substantial amounts of data in each system without direct access or natural abilities to access it, examine it and make meaningful analysis around it.

Overall, businesses want to keep data — or at least err on the side of caution and retain as much of it as they reasonably can. Better data leads to better decision-making, regardless of whether they can seamlessly access that data. The idea behind this is the opposite of garbage in, garbage out. The better the analysis of your inputs in any substantial decision, the better the outcome of the decision you make on the other side. In general, more data can only be more helpful, informative and able to promote a well-founded conclusion.

So, how do you reconcile these two concepts? If data is scattered, then how does a smart organization synthesize it to yield better operational decisions? How might they go about that data synthesis?

Experts are developing a solution to this madness: agile data integration and governance solutions. These engines take data that is spread on-premises, in the cloud, in siloed data systems and in previously unreachable places, synthesizing them into a system that can help organizations discover, enrich, integrate and manage data over its entire useful life. These solutions can empower companies to make the most of their growing data ecosystems.

This article was originally published on Mobile Business Insights.