May 18, 2016
The power of Big Data was originally only available to the world’s largest companies and massive projects like genome sequencing. Now that Big Data has matured, the tech industry is able to harness the wealth of information to provide valuable and affordable business intelligence (BI) solutions to organizations of every type and size.
While analyzing historical data can certainly be useful, more and more companies are turning to BI to track processes as they are happening, allowing leaders to take action within the normal flow of business.
Data analysis systems with real-time or near real-time capabilities enable a more actionable form of operational business intelligence by allowing users to access and analyze data from disparate systems and delivering a picture of the business’s current state, which decision-makers can then act upon.
While historical data analysis can tell you how you might have been able to upsell to a customer yesterday – giving you the insights you need to adjust your long-term strategy – operational BI tells you what else you can sell to the customers who are closing deals with you today. In this sense, operational BI is the key to short-term revenue boosts.
Insights That Drive Impact
A study by Accenture and GE found that over 90 percent of executives were satisfied with their big data investments. BI was considered “very” or “extremely” important by 89 percent of all executives, and a similar share of those with active Big Data analysis initiatives said they view BI as a way to revolutionize business operations.
When asked specifically what they use Big Data for, 94 percent said identifying new sources of revenue, 90 percent said customer acquisition and retention, and 89 percent said to develop new products and services.
Operational BI is already providing most leading companies with a competitive edge, including those which operate in traditional industries, as well as technology giants such as eBay and Samsung. Those companies have moved on from in-house data analysis by highly skilled (and therefore rightfully expensive) IT departments, to specialized operational BI.
Sisense, an up-and-coming provider of business intelligence software, works with proprietary, high-performance data storage units called Elasticubes. The Elasticube technology allows BI users to easily consolidate data from distributed, complex and diverse sources, automatically updating records at regular intervals on the fly.
This data can then be analyzed by business users who don’t have technical know-how, who can use it to reveal insights and patterns in diverse datasets. This allows for faster and more queries, and it enables businesses to use operational BI with maximum impact.
Reduced Latency for Taking Faster Action
Sisense’s “in-chip analytics” technology speeds up the delivery of insights to enable on-time operational BI. It is essentially a series of algorithms and optimizations that enable Sisense’s software to perform analytical calculations within the server’s chip-set, while making more efficient use of its RAM and disk resources.
The reduced latency that results from this allows Sisense to ingest and process much larger quantities of data, which traditionally would require largescale hardware infrastructure or IT work. This gives Sisense’s end users data analysis and reporting capabilities which would previously have only been accessible only by data scientists or specialized technical teams.
Operational business intelligence can be used for in-depth comparisons between today’s sales and past day’s sales. So if Monday is usually your busiest day but this Monday was slow, you need to know why, and operational business intelligence can help you find out.
These kinds of insights are valuable, but the possibilities enabled by the immediacy of operational BI are in a whole new class. Data returned to a system shortly after an interaction and run through a fast rules engine can improve that very same interaction.
That is why exactly why operational BI is sometimes called “fast data” and, while it still cannot read the customer’s mind, it is as close to that as you can get.
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