Hot Data Technologies for 2018 and How to Embrace Them

By on

Click to learn more about author Ravi Shankar.

One of the biggest problems today is not a lack of innovation or solutions, but rather how to settle on any technology. The key is to pick one and embrace it in a meaningful, productive way, without falling prey to debilitating “pause your business” problems that arise when incorporating new technology with your existing infrastructure.

Too Much Innovation?

It could be that, like kids in candy stores, we don’t know where to begin, or where to stop. Cloud technologies continue to explode, as banks and other enterprises dramatically reduce their data center footprints. As Cloud, Big Data, and mobile technologies continue to grow, new technologies are already taking root. The IoT was valued at $8.4 B in 2017, a 31 percent bump from 2016. BI and Analytics was valued at an impressive $18.3 B in 2017, up 7.3 percent from the previous year. And as Gartner’s Tom Bittman recently opined, the edge is poised to grow so large that it will dwarf all of the gains previously made by the cloud.

Innovations such as these show no sign of slowing down either. Blockchain, a technology for immutably linking parts of a secure online transaction, added $176 B of business value in 2015. The Artificial Intelligence market saw its share of explosive growth, gaining a whopping $200 B in new revenue while adding a million new jobs.

Change Hurts

The challenge is that any change in technology can result in significant downtime and over-all disruption to the business as IT teams need to pull critical systems offline in order to implement new ones. Change can also result in impaired functioning including due to delays in gaining access to data or insights, which can occur whenever systems are added, removed, or substantially changed.

The real question is does it have to be this way?

Change without Disruption

To successfully adopt new technology without disruption, companies need core abilities that transcend individual industries or use cases. They should include characteristics such as agility, quality, security, and intelligence and easily be incorporated into the existing landscape. One technical capability is data abstraction. Data abstraction is a layer of intelligence above the idiosyncrasies of individual data sources. The technology masks traditional complexity, and enables the easy exchange of technologies under its cover without affecting the business.

Data Virtualization platforms enable data abstraction, as they provide real-time, integrated views of data across the myriad of data sources beneath them. With a Data Virtualization platform in place, for example, companies can replace their old systems with new ones without business users even noticing. This is because the users get the data from the Data Virtualization platform, which abstracts the users from the complexities of where, and how, the data is physically stored.

New technologies will always enhance our lives while also threatening to cause disruption. But with data abstraction capabilities, companies will gain the core competencies needed for adopting any new technology with zero disruption.

We use technologies such as cookies to understand how you use our site and to provide a better user experience. This includes personalizing content, using analytics and improving site operations. We may share your information about your use of our site with third parties in accordance with our Privacy Policy. You can change your cookie settings as described here at any time, but parts of our site may not function correctly without them. By continuing to use our site, you agree that we can save cookies on your device, unless you have disabled cookies.
I Accept