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Independent Research Finds Traditional Analytical Platforms Struggle to Quickly Deliver Data Insight
[November 07, 2018]

Independent Research Finds Traditional Analytical Platforms Struggle to Quickly Deliver Data Insight


A new study from Forrester (News - Alert) Consulting, commissioned by Kinetica, reveals that more than 90% of enterprise decision-makers across the United States are dissatisfied with traditional analytics platforms for managing extreme data, finding that growing data volumes and complexity make it increasingly difficult for businesses to achieve actionable, real-time insights.

Based on a survey of 105 analytical database and data platform decision-makers, the Forrester Consulting study outlines the struggle enterprises face in keeping up with the growing volume and speed of data, which creates new challenges in integration, security, performance, management, and governance. The study found that in the last two years alone, most respondents saw their data volume increase by over 50 percent year over year. A trend that shows no sign of slowing down, nearly a quarter of businesses witnessed their data volumes more than double annually.

"Enterprises are quickly moving beyond passive analytics and static dashboards," said Paul Appleby, CEO at Kinetica. "Today's organizations need smart analytical applications that allow business stakeholders to interact with both streaming and historical data in real-time. Forrester's extreme data survey shows us that organizations are moving beyond traditional data approaches and embracing new strategies to channel extreme data into business insight."

The Forrester survey found that four in ten of the surveyed decision-makers struggle to manage the increasing volume of data as data management costs continue to climb. The report additionally found that 31 percent of decision-makers have difficulty supporting complex analysis in order to turn extreme data into actionable, real-time insights, and roughly 33 percent of decision-makers believe these challenges stem from legacy technologies.

"Dealing with extreme data often requires large and complex platforms," according to the Forrester Consulting study. "[The] study reveals a critical business opportunity and demand for GPU-based data platforms that process data faste and more intelligently. This drives real-time actionable insights that lead to business growth and innovation. Organizations that implement a GPU-based data platform are more likely to accelerate time-to-action data insights to achieve competitive advantage."



Looking ahead, the study shows that achieving actionable insights from data (53 percent) and supporting real-time analytics initiatives (49 percent) will be among the top priorities that decision-makers will have to address in 2019. Organizations will leverage machine learning, distributed computing, and new architectures to combat data issues. Fifty-seven percent of respondents aim to augment their traditional analytics with machine learning (ML), while 54 percent will invest in distributed computing technologies, and 42 percent will move to new accelerated computing architectures.

GPUs are not only for gaming


Organizations must invest in platforms that allow them to deliver extreme data insights. In the coming years, organizations plan to allocate budget towards cloud, artificial intelligence (AI), and machine learning, as well as big data platforms, with 64 percent investing in advanced analytical platforms that enable AI and/or machine learning over the next two years.

Today, organizations are starting to leverage Graphical Processing Unit (GPU)-powered databases for deeper data analysis, to enable dynamic correlation, and deliver predictive outcomes fast and at scale. The study found that GPU-enabled technology has strong momentum across enterprises, with 70% of respondents using or implementing GPU-powered databases for advanced analytical needs. Companies believe that GPU-powered data platforms offer several benefits, including the ability to process large data sets (38 percent) and reduce latency for real-time insights (33 percent).

Read the Forrester study: Turn Extreme Data Into Insights with GPU Data Platforms
Register for webinar: Forrester Research Turn Extreme Data Into Insights With GPU Data Platforms

About Kinetica

Kinetica is the insight engine for the Extreme Data Economy. The Kinetica engine combines artificial intelligence and machine learning, data visualization and location-based analytics, and the accelerated computing power of a GPU database across healthcare, energy, telecommunications, retail, and financial services. Kinetica has a rich partner ecosystem, including NVIDIA, Dell (News - Alert), HP, and IBM, and is privately held, backed by leading global venture capital firms Canvas Ventures, Citi Ventures, GreatPoint Ventures, and Meritech Capital Partners. For more information and trial downloads, visit kinetica.com or follow us on LinkedIn and Twitter.


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