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Data in 2016: 10 Shocking & Surprising Takes

Data in 2016: 10 Shocking & Surprising Takes Fotolia Data in 2016: 10 Shocking & Surprising Takes

This slideshow contains predictions of a frank and bold nature, which are intended for a mature data science audience.

They Predict What!? Fotolia They Predict What!?

What lies in store for data analytics and business intelligence in 2016? The answers may surprise and even astound you. Data scientists certainly have plenty of thoughts. So do the people that employ them. As evidence, consider the following predictions from several CEOs and senior execs at leading analytics and technology firms.

The Wows and Woes of Internet of Things Data Fotolia The Wows and Woes of Internet of Things Data

"The deluge of Internet of Things data represents an opportunity, but also a burden for organizations that must find ways to generate actionable information from (mostly) unstructured data. Organizations will be seeking database solutions that are optimized for the different types of IoT data and multi-model approaches that make managing the mix of data types less operationally complex.”

Adam Wray, CEO, Basho Technologies

Data Management Systems Get a Make-over Fotolia Data Management Systems Get a Make-over

“Businesses are no longer simply experimenting with NoSQL, they are now re-platforming their entire infrastructure around it to support their Web, mobile and IoT applications. In 2016, we’ll see more enterprises re-platform their data management systems using NoSQL to overcome the limits of their 30-year old legacy relational systems.”

Bob Wiederhold, CEO, Couchbase

Data Science Teams Become Clean-up Crews Fotolia Data Science Teams Become Clean-up Crews

"In 2016 'data scientists' will continue to have trouble doing their jobs and analyzing data because they will spend so much time trying to manage and cleanse it."

Kon Leong, CEO and Founder of ZL Technologies

Open Source Opens Up the Enterprise Fotolia Open Source Opens Up the Enterprise

“In 2016, technologies like Apache Spark, Kafka and System ML will make a real impact in the enterprise. Open source technologies allow enterprises to innovate faster and move quickly to stay relevant, without needing to build key infrastructure from scratch. Notably, with Apache Spark and Kafka, businesses will be able to tap the 80 percent of unstructured information stored across their databases that remains untouched – unlocking untold potential.”

Derek Schoettle, general manager of Cloud Data Services, IBM

Data Governance Gets Bureaucratic Fotolia Data Governance Gets Bureaucratic

"Information governance requirements will become very complicated for US-based companies operating in the EU."

Kon Leong, CEO and Founder of ZL Technologies

Better Stacks Will Mean Better Data Fotolia Better Stacks Will Mean Better Data

"Big Data means Big Challenges when it comes to building the right technology stack to leverage this data for real-time insights to deliver real customer value. In 2016, I predict that we'll see big advances in delivering technology stacks that integrate key components of the distributed data tier. These stacks will take away much of the technology complexity making it more consumable in the enterprise and bring operational simplicity to solving this challenge."

Adam Wray, CEO, Basho Technologies

Open Enterprises Need Open-Minded CIOs Fotolia Open Enterprises Need Open-Minded CIOs

“The year of open source means that CIOs will need to better understand the open technologies that can grow the business. We’re already witnessing CIOs of major brands attending Apache meet-ups to get a better feel for the technologies, but the net result is developers gaining more clout in the enterprise: Developers are the influencers on the front lines, building and connecting core infrastructure. Because of this, they’re impacting directly the technologies an enterprise will adopt. The CIO will soon be working hand-in-hand with their developer team, understanding tools – and what’s possible with them – in a way that they never have before.”

Derek Schoettle, general manager of Cloud Data Services, IBM

Data and Knowledge Drive Artificial Intelligence Fotolia Data and Knowledge Drive Artificial Intelligence

“Both pure data-driven and knowledge-driven AI automation will continue to spread. Pure data-driven tasks will more often be associated with AI, whereas the knowledge-driven tasks will be more associated with “automation” rather than with “AI.” Artificial Intelligence has seen this movie before, during the expert-systems craze of the 1980s and 90s. Companies will realize that to get something they need to give, with regards to sharing data to make improvements to their business. Just like consumers have learned and demanded something in return for giving up rights to their data, so will enterprises.”

Raul Valdes Perez, co-founder and CEO of OnlyBoth

Everybody Finally Takes a Peek at Data Privacy Fotolia Everybody Finally Takes a Peek at Data Privacy

"Privacy issues will rise to the forefront of analytics efforts ... even if those efforts are using data generated purely from the business environment."

Kon Leong, CEO and Founder of ZL Technologies

Open Source Helps Close the Data Skill Gaps Fotolia Open Source Helps Close the Data Skill Gaps

“Open source will help address the looming skills gap. Data scientists trained to write complex SQL queries are dwindling, while DBAs and developers used to building core infrastructure from the ground up are becoming increasingly rare. In the future, data analytics will move from input and maintenance to a true business intelligence function. Open source will enable the next generation of IT to draw from a community of research for basic tasks, allowing them to spend more time on truly value-generating activities.”

Derek Schoettle, general manager of Cloud Data Services, IBM

This slideshow contains predictions of a frank and bold nature, which are intended for a mature data science audience.

 

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