12 top data and IT trends to expect in 2017

Professionals foresee advances in analytics, machine learning and the Internet of Things.


12 top data and IT trends to expect in 2017

This year has seen tremendous changes in the areas of analytics, machine learning and the Internet of Things. Experts predict further advances in these uses of information technology in 2017, according to these experts. This presentation is courtesy of HDM's sister publication, Information Management.



Organizations learn to trust the data lake

"2017 will be the year organizations begin to rekindle trust in their data lakes. The ‘dump it in the data lake’ mentality compromises analysis and sows distrust in the data. With so many new and evolving data sources like sensors and connected devices, organizations must be vigilant about the integrity of their data and expect and plan for regular, unanticipated changes to the format of their incoming data.

"Next year, organizations will begin to change their mindset and look for ways to constantly monitor and sanitize data as it arrives, before it reaches its destination."

- Girish Pancha, chief executive officer and founder, StreamSets



The IoT market will see greater consolidation

“As technology and processes improve - much like natural selection - the strongest ones will survive while the smaller players are gobbled up to build out more robust portfolios.

"Look at SAP, for example. They just acquired an enterprise-grade IoT solution last month and Cisco made waves in February when it purchased Jasper. The rate at which these tech giants purchase startups will only increase as they continue to thirst for the innovation so many of these young companies are born from.”

- Zach Supalla, chief executive officer, Particle



IoT architect becomes the top job role

“The Internet of Things architect role will eclipse the data scientist as the most valuable unicorn for HR departments. The surge in IoT will produce a surge in edge computing and IoT operational design. Thousands of resumes will be updated overnight. Additionally, fewer than 10 percent of companies realize they need an IoT analytics architect, a distinct species from IoT system architect. Software architects who can design both distributed and central analytics for IoT will soar in value.”

- Dan Graham, Internet of Things technical marketing specialist, Teradata



Need for speed becomes top data focus

“The ability to move data quickly and cost efficiently will become a top priority as multi-cloud deployments become more common and data sovereignty laws require data repatriation.”

- Varun Mehta, vice president of product operations, Nimble Storage



Consumers will gain control of their own data

“The emergence of Blockchain, coupled with advances in consumer technology devices, cloud computing and security measures will alter the current data ownership paradigm from centralized to decentralized. Early efforts include projects in healthcare and social media. In a project known as Solid, Tim Berners-Lee and his MIT cohorts are working to return ownership of social media data to the users that create them.

"In healthcare there is a growing desire for patients to control their own medical records based on the view from medical practitioners that patient care and quality of life is directly influenced by the ability of patients to access and utilize their data. This view is core to the Precision Medicine Initiative which envisions that patients, along with medical and insurance providers, should be able to access and share their lab results, x-rays, genetic and medical history data according to their own terms.”

- Jans Aasman, chief executive officer, Franz Inc.



Mobile, IoT and cloud become essential

“Mobile, IoT and cloud will be a necessity. These three elements grant facilities maintenance total cost savings by predicting problems and having all the information available for the technician with unprecedented immediacy, all while supported by seamless infrastructure. Having the most cost effective and efficient technology is just as important to the requester as the responder.”

- Tim McLean, associate vice president, strategic accounts, Accruent



Traditional network security becomes irrelevant

“We will continue to see legacy threat barriers such as traditional network security become irrelevant as users carry devices from network to network without boundaries.

"The devices connect to networks transparently, and while we might have strong security at home or at our place of work, carrying a laptop or mobile device to a hotel or coffee shop network and connecting may be all it takes for malware to get a toehold into our networks. Once a single device is compromised and brought back into a trusted network, malware can propagate east and west to other targets.”

- Hal Lonas, chief technology officer, Webroot Network



Big data or bust in 2017?

“Big data is an example of something that didn’t get as far along as people predicted. Of course, it wasn’t stagnant. But nearly everyone involved in the enterprise sector would like it to move faster. The problem is that companies struggle, in general, to make sense of big data because of its sheer volume, the speed in which it is collected and the great variety of content it encompasses.

"Looking ahead, we can expect to see newer tools and procedures that will help companies house and examine these massive amounts of data and help them move toward truly making data-driven decisions.”

- Doug Rybacki, vice president of product management, Conga



Hackers hijack connected cars

“Connected cars will be taken for ransom. As cars start to have connected capabilities, it is only a matter of time until we see an automobile hack on a large scale. This could include cars being held for ransom, self-driving cars being hacked to obtain their location for hijacking, unauthorized surveillance and intelligence gathering, or other automobile-focused threats.”

- Brian Kenyon, chief strategy officer, Symantec



Data management becomes the final frontier

"Data is the final frontier in the quest for continuous IT operations. In 2017, we’ll start to see organizations manage data topologies in the same way they have taken to managing modern applications, networks and IT security: as a living breathing operation that must run reliably and automatically on a continuous basis.

"But to fulfill that quest, businesses will need to look hard at what changes they need to make to their processes, tooling and even organization to ensure the availability and accuracy of their data in motion."

- Girish Pancha, chief executive officer and founder, StreamSets



Deep learning emerges as a true strategy

“Deep Learning will move out of the hype zone and into reality. Deep learning is getting massive buzz recently. Unfortunately, many people are once again making the mistake of thinking that deep learning is a magic, cure-all bullet for all things analytics. The fact is that deep learning is amazingly powerful for some areas such as image recognition.

"However, that doesn’t mean it can apply everywhere. While deep learning will be in place at a large number of companies in the coming year, the market will start to recognize where it really makes sense and where it does not. By better defining where deep learning plays, it will increase focus on the right areas and speed the delivery of value.”

- Bill Franks, chief analytics officer, Teredata



Predictive analytics and AI become differentiators

“Feeds and speeds are no longer enough. Predictive analytics and artificial intelligence will emerge as the primary differentiator for storage companies.”

- Varun Mehta, vice president of product operations, Nimble Storage



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