According to a new report authored by Ovum, a research, analysis and technology consulting firm, machine learning capabilities will play a key role in disrupting the Big Data Analytics market in 2017. The recently published 2017 Trends to Watch: Big Data study provides insights into what lies ahead for Big Data software providers, solutions, and the software market as a whole.
The firm explains: “Big data was once the shiny new thing; machine learning (a form of artificial intelligence) has taken its place. If your organization plans to recruit, or already has data scientists on staff, your challenge is to ensure that their work will not get bottled up on their laptop; collaboration will become the order of the day in 2017.” Ovum’s expectation is that enterprise organizations will make data science a “team sport” next year.
Big Data remains a popular buzzword, but Ovum’s a step ahead, and argue that fast data will be the breakout use case to look out for in 2017. Many enterprise companies have turned away from legacy storage and collection technologies in favor of more agile, open source frameworks, like Hadoop, Spark and those developed by the Apache Software Foundation. Fast data provides the modern digital enterprise with a unique opportunity to analyze data on the fly while its ingested. The speed at which data moves is a necessary consideration for modern data-driven organizations.
Ovum hit the nail on the head last year in their annual trends report, claiming that 2016 would show considerable Hadoop deployment and the emergence of alternative paths to Big Data. Considering the accuracy with which Ovum has showcased in the past, this report has become an important, and perhaps vital read for stakeholders and Data Analytics leaders.
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