Why Data Services Are Key to Supporting New Tech Trends

The Challenges of Gaining Useful Insight into Data

This month, I’m looking at trends that are changing data integration. Last week, I discussed how new data types are changing data infrastructure while cloud infrastructure requires a more service-oriented approach to integration.

That’s only part of the services story, though. Trends such as mobile and Big Data analytics are forcing organizations to service-enable data. Informatica CEO Sohaib Abbasi calls this disruptive trend the “perimeter-less world of pervasive computing.” That’s changing the security infrastructure, he argues, but this perimeter-less world also requires us to rethink data.

Put simply, pervasive computing means data is no longer confined to internal systems or a relational database. Data is more fluid now, flowing into the enterprise from cloud applications, social media, sensors and open or acquired data sets. It’s also flowing out of the network, whether that means porting data to a SaaS application, accessing data from mobile devices or extracting data from data lakes to use in analytics tools.

Why It Matters

A service approach to data is a key component of a modern technology infrastructure, but data services will require new approaches to data integration, David Linthicum writes in “The Death of Traditional Data Integration.” Linthicum, an IT consultant and writer, sees the rise of data services and data microservices as one of several game-changing trends.

“The rise of services, and, now, microservices, changes the game, in terms of how we leverage and manage data,” Linthicum states. “Data services are services married with data, and they will be the most common mechanism for accessing data as we move forward.”

But as you’ve probably guessed, data services require a more flexible approach to data integration. According to Linthicum, that means data integration technology must layer in:

• Service directories
• Service governance
• Service identity-based security

“As data services and the use of data become a larger part of enterprise systems, data integration technology will need to adapt,” he adds. “While most data integration approaches and technologies available today can certainly process data services as a point of access to data, the emerging use cases will require a much wider degree of integration patterns that define access to data inside or outside of the enterprise.”

Building a data service generally requires a virtualization solution to abstract data from the source without actually moving or changing it. The virtualized data can be “served” via an API or more traditional SOA service.

For more on data microservices, check out Martin Fowler’s lengthy discussion on microservices architecture, particularly the section on decentralized data management.

Loraine Lawson is a veteran technology reporter and blogger. She currently writes the Integration blog for IT Business Edge, which covers all aspects of integration technology, including data governance and best practices. She has also covered IT/Business Alignment and IT Security for IT Business Edge. Before becoming a freelance writer, Lawson worked at TechRepublic as a site editor and writer, covering mobile, IT management, IT security and other technology trends. Previously, she was a webmaster at the Kentucky Transportation Cabinet and a newspaper journalist. Follow Lawson at Google+ and on Twitter.