As the calendar turns – Part 2


In this two-part series, which posts as the calendar turns to a new year, I revisit the top data management topics of 2015 (Part 1) and then try to predict a few of the data management trends of 2016 (Part 2).

Data management in 2016

42-27611110The Internet of Things (IoT) made significant strides in 2015. It made progress in health care, manufacturing, energy, retail and other industries – as well as the mass market – in the form of consumer electronics and household appliances enabled by embedded software and sensors to collect and exchange data. With Gartner predicting 5.5 million new things will get connected every day in the new year, a lot of data management trends in 2016 will be connected to IoT-related initiatives.

The connection I will be looking for throughout the new year, however, is whether the data emanating from IoT can be integrated. IoT will produce a lot of new data sources related to data already being managed by existing applications, systems and processes. For example, sensors added to track the shipping and inventory of manufactured parts and products have to be connected to supply chain management systems. In a previous post I discussed why, without integration, the immense potential of IoT cannot be actualized. To be valuable, IoT data needs to be processed, analyzed and shared, not only between devices but also with other systems and people. This is why I think that 2016 will not only be about connecting things to the Internet, but also the year we ask if everything is connected.

What say you?

Where do you see your data management efforts focused in 2016? Please share your perspectives by posting a comment below.

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About Author

Jim Harris

Blogger-in-Chief at Obsessive-Compulsive Data Quality (OCDQ)

Jim Harris is a recognized data quality thought leader with 25 years of enterprise data management industry experience. Jim is an independent consultant, speaker, and freelance writer. Jim is the Blogger-in-Chief at Obsessive-Compulsive Data Quality, an independent blog offering a vendor-neutral perspective on data quality and its related disciplines, including data governance, master data management, and business intelligence.

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