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MIC Sector Forecast: Big Data

Big data is big business. We recently profiled The World’s Top 10 Most Innovative Companies of 2015 for Big Data and it got us thinking… how will big data and analytics change over the next five years? Here are some predictions from the industry’s top minds. LISA ARTHUR: CMO, TERADATA MARKETING APPLICATIONS

MIC Sector Forecast: Big Data
[Photo: Flickr user Sarah Le Clerc] [Photo: Flickr user Sarah Le Clerc]

Big data is big business. We recently profiled The World’s Top 10 Most Innovative Companies of 2015 for Big Data and it got us thinking… how will big data and analytics change over the next five years? Here are some predictions from the industry’s top minds.

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LISA ARTHUR: CMO, TERADATA MARKETING APPLICATIONS

Executives Will Use Analytics More: “Analytics will be the ‘glue’ the C Suite Needs. Marketers who make the most of analytics will prove to be the ones who gain support in the C Suite, because it will be marketers who are explaining not only what customers want, but why. Marketing organizations now collect an astounding amount of data about prospects and customers, and analytics are what can enable you to draw meaning from that avalanche. There will be more emphasis on advanced marketing applications that integrate marketing with the entire enterprise. Marketing teams will need to work together across regions and departments to unify and analyze the massive amounts of available data—to fuel innovation, customer value and better business.”

BILL BRIGGS: CTO, DELOITTE CONSULTING

Data and Analytics Will Be Part of Everyone’s Job: “Every company is becoming a technology company, and data is the currency upon which markets will compete – big or small, structured or unstructured, owned leased or discovered. Specialized centers of deep expertise in data science and advanced analytics techniques might be needed to help identify, experiment, and scale new information capabilities. But training will be needed to ready the broader workforce to be a data-driven organization–allowing rigor and insight to drive behavior and actions and developing the tools to improve,
innovate, and grow using disruptive technologies. This will lead to not just new skill-sets, operating models, delivery models, and productivity tools for employees… it will also revisit the very nature of ‘employment.’”

MICHELLE CHAMBERS: PRESIDENT AND COO, RAPIDMINER

Organizations Will Close the Analytics Skills Gap: “With the next generation of tools and technology, business analysts and business users will act like data scientists–and ‘real’ data scientists will be free to focus on heroics with big data instead of spending 90% of their time on data prep.”

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SCOTT GNAU: PRESIDENT, TERADATA LABS

Data Driven Decision Making: “In the next five years, most businesses that are becoming data-driven now will look to use smart systems to automate processes and operational decision-making, which will shine a critical spotlight on the global workforce, and the skillset of employees. Businesses that are thinking about this now, and training their employees to not only work in a more fluid way with data, but to learn how to do more strategic, complex and creative work using data, are ahead of the curve. Big data will need more creative types like skilled sociologists, psychologists, communicators, economists and leaders that understand how to elicit a response from fellow humans, not simply analyze data.”

JOHN GORDON: VP INNOVATIONS WATSON GROUP, IBM

We Will Search Video, Images, And Sound Like We Search Text: “An increasing amount of the data being created is video, graphics, and design images. While we have made substantial progress understanding languages and even speech, we will get dramatically better at leveraging cognitive systems to help us review and interpret video, graphics and visual images with the same level of deep understanding.”

COLIN GOUNDEN: CEO, VIA SCIENCE

Combining Genomic Data With Environmental Data for Agriculture: “It’s hard to believe that mapping the first human genome was only completed in April 2003. Now that we have relatively fast and cheap techniques to map and manipulate genomes, I think we will start to see analytics to combine genomic data (and other biological data) in plants with environmental data like weather, soil conditions, etc. to optimize the yield of crops (increase the bushels per acre of food). Imagine the self-driving tractor on a farm that plants a slightly different combination of seeds and nutrients at slightly different depths and distances apart from each other to make the most of an acre of land.”

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BRIAN HOPKINS: VP AND PRINCIPAL ANALYST, FORRESTER RESEARCH

More Hiring of In-House Data Scientists: “We’ve heard multiple times that, while a vendor may have a few stars or a crack team (for data talent), often the resources that actually show up are not much better than contractors available on Monster or Dice. Alternatively, we consistently hear from experienced firms like Zions Bank, Sears Brands, and MasterCard that the technology is not that difficult for firms willing to embrace open source and do a lot of their own development. Forrester expects firms to recognize the need to beef up their internal talent in 2015 and find ways to retain talent by embracing an open source culture.” (Via)

VIKTOR MAYER-SCHONBERGER, OXFORD UNIVERSITY/CO-AUTHOR, “BIG DATA”

The Auto Industry Will Be Transformed: “Self-driving cars will arrive much faster than car makers have thought even a year ago. Especially for trucks in Europe, big data-based automated driving on highways will become mandatory (for new trucks). Automated driving initially at least will have the biggest impact on trucks, as automated driving trucks on highways will lower fuel consumption, pollution, and traffic jams (by as much as 20 percent according to a European study).”

GURJEET SINGH: CEO, AYASDI

More Automation, Not Enough Jobs: “The talent shortage in data science will only get worse. This will create significant opportunities for automation, particularly around data transformation and analytics. This will mirror the rise of developer tools that follow the shortage in software developers. The acceleration of acceleration will impact the world of big data algorithms, enabling them to become self-replicating and self-propagating. While this will have a profound impact on enterprise efficiency, they will not be nearly as impactful as the frameworks and platforms that synthesize these rapidly growing algorithmic libraries. ”

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