This report provides analysis and guidance about the benefits of adopting a real-time analytics strategy, and the essential components to execute on such a strategy. The main conclusions and key takeaways are as follows:
If a company has deployed a Big Data and analytics system, accessing, managing, and distributing analytic insights to the organization, that is laudable. It is also not enough. The game has (already) changed. Companies must deliver analytic insights when needed; and the answer to the question “when?” is becoming: “in real time.”
Seventy-five percent of the respondents to Stratecast’s 2014 Big Data and Analytics Survey either have already deployed a real-time analytics solution ( %), or are planning to do so ( %).1 Many respondents experienced smooth deployments and are obtaining positive ROI. A sizable group of respondents, however, are disappointed in the results thus far from their real-time analytics deployments. This group clearly feels it was poorly served by the vendors it worked with on its deployments: respondents cited poor training and a lack of maturity on the part of both the product and the vendor as factors in their disappointment.
Clear definitions and a blueprint for a successful real-time analytics deployment are needed—and this report offers both. Stratecast’s definition of real-time analytics centers on providing users with immediate insights before placing data into storage. The ingredients to achieve this include stream processing of data; in-memory computing; Big Data-supporting infrastructure, including shared-nothing processing and fault tolerance; and a number of ongoing open source initiatives at the Apache Software Foundation.
Real-time analytics can benefit any organization in any sector. It is also essential to artificial intelligence (AI). Empowering machines to learn and to exhibit other human-like behaviors means enabling a multitude of intricate, ultra-high-speed maneuvers; and real-time analytics is needed to provide data feeds every robotic step of the way.
Deploying real-time analytics adds cost and complexity to existing IT processes, and can overwhelm an organization with a tidal wave of new data. Yet, companies must adapt to the new real-time paradigm. Stratecast believes that sometime in 2015, real-time analytics will become a standard requirement of all data management systems.
About this report
This report provides analysis and guidance about the benefits of adopting a real-time analytics strategy, and the essential components to execute on such a strategy.
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