Ovum: Machine learning to disrupt big data analytics in 2017

06 Dec 2016

While streaming is expected to become the breakout use case for big data in 2017, machine learning will be the biggest disruptor for big data analytics next year, according to a new report by Ovum.

The research firm says in stealth mode, machine learning is already becoming ubiquitous as it is embedded in many online services - from shopping at Amazon to searching Google and watching entertainment from sites like Netflix - that consumers take for granted.

Increasingly, machine learning is becoming embedded in enterprise software and tooling for integrating and preparing data. And it is placing a stress on enterprises to make data science a team sport; a big area for growth in 2017 will be solutions that spur collaboration, so the models and hypotheses that data scientists develop do not get bottled up on their desktops, Ovum predicts.

Other key trends from Ovum’s “2017 Trends to Watch: Big Data” report include:

  • IoT use cases will push real-time streaming analytics to the front burner.
  • The cloud will sharpen Hadoop-Spark “co-opetition.”
  • Security and data preparation will drive data lake governance.

While machine learning continues to grab the headlines, real-time streaming will become the fastest-growing use case.

A perfect storm has transformed real-time streaming from a niche technology to one with broad, cross-industry appeal. Open source technology has lowered barriers to entry for both technology providers and customers, while scalable commodity infrastructure has made the processing of large torrents of real-time data in motion economically and technically feasible.

The explosion in bandwidth and smart-sensor technology has opened up use cases ranging from location-based marketing to health and safety, intrusion detection, and predictive maintenance, appealing to a broad cross section of industries.

Underscoring and enabling the growth of big data is the growing predominance of cloud computing as the default path to deployment.

Within the next 24 months, Ovum expects that the cloud will pass the halfway mark to dominate new big data deployments.

“Big data has emerged from its infancy to transition from buzzword to urgency for enterprises across all major sectors,” said Tony Baer, principal analyst for information management at Ovum.

“The growing pains are being abetted by machine learning, which will lower barriers to adoption of big data-enabled analytics and solutions, and the growing dominance of the cloud, which will ease deployment hurdles.”

That said, big data continues to be the fastest-growing segment of the information management software market, growing from $1.7 billion in 2016 to $9.4 billion by 2020, comprising 10% of the overall market for information management tools.

Meanwhile, ABI Research, says that machine learning technologies will lead mobile operators to profoundly change how they manage the telecoms business.

The research firm predicts that mobile operators worldwide will devote more than $50 billion to big data and machine learning analytics through 2021.

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