NEW YORK, NY-(Marketwire - Oct 22, 2012) - OPTIER, the leader in Application Performance Management(APM) and providing end-to-end Contextual Transaction Data, analyzing billions of transactions per day, today announced key findings from its newly released Big Data Analytics research study. The research shows that amid all the hype, few companies are able to apply Analytics to Big Data for competitive advantage, because of the time and costs associated with traditional approaches to Analytics.
To better understand how companies are currently analyzing Big Data, what they are lacking, and how they can better take advantage of Big Data, Jacques Takou Tuh, an MBA student at the Kellogg School of Management and Adam Kanouse, CIO of OpTier, conducted primary research with business executives at Global 250 companies. Based on one-on-one interviews and focus groups spanning industries including Financial Services, Healthcare, Media & Entertainment, Retail and Telecommunications, these findings are summarized in a research paper titled "Making Big Data Analytics Fast and Easy."
Despite all the hype about social media, the majority of Big Data resides within the four walls of a company's data center.
Companies are not gaining a business advantage from their Big Data because it is distributed across many silos and lacks the context and uniformity necessary to allow analysts to quickly leverage it.
A huge bottleneck to Analytics is the Data Preparation phase, which accounts for 30-60% of the time spent in analytics, because data is saved without context.
The companies surveyed that have a Big Data Analytics solution in place spent 2-3 years setting up their data warehouses, and spend a minimum of 2-3 months each time a new data set is incorporated.
There are three alternatives companies use today to perform analytics: 1) Traditional statistical modeling of data relationships; 2) Re-writing applications and re-building from the ground up; 3) Capturing transaction in context at the time of execution. The first two are time-consuming and cost-prohibitive (only the largest enterprises can afford these).
Companies surveyed agree that context would dramatically accelerate Analytics because they would be able to reduce the time and cost spent on analytics by 50-90%.
Companies reported that the ability to understand the value and/or cost of servicing each individual customer would be extremely valuable.
"Analytics have emerged as the fastest growing segment of IT budgets, but what's missing today from Big Data analytics? In a word, it's context!" said Andy Wild, president of OpTier. "Today's leading companies are struggling to take advantage of the volume and variety of data available within the four walls of the enterprise. By rethinking the way they analyze Big Data and capturing transactions that are already in context, CIOs can fundamentally change the economics and process of analyzing Big Data - saving 50% of time spent and cost."
"Companies worldwide are anticipating the value in analyzing their Big Data, but many do not have an efficient process in place to effectively take advantage of the data," said Professor Russell Walker at the Kellogg School of Management. "Based on the research conducted, a common theme that emerged was the need for a faster way to get meaningful business value - such as the interrelationships between various data sets - out of their Big Data. Contextual data is key to drive business growth."
To download a copy of the research paper titled "Making Big Data Analytics Fast and Easy," click here.
OpTier, headquartered in New York, is the leader in APM and Big Data Analytics, analyzing billions of business transactions per day. With transactions in its DNA, OpTier has given the market an award-winning Application Performance Management solution, an industry-leading Big Data Analytics platform, and creates contextual big data that drives transformational initiatives like business impact analysis, CIO prioritization, data center consolidation and virtual and cloud migrations. This actionable intelligence provides global 1000 customers such as Deutsche Bank, Frontier Communications, Morgan Stanley and O2, insights that drive business growth, operational productivity and customer satisfaction.