Transaction Workloads Driving The Case For Big Data Analysis

Transaction based workloads are the priority data source for 32.3 percent of organisations that are looking to perform Big Data analysis, according to the IDC Australia Information Management Survey.

Mining data and information about a customer has moved from a way to gain competitive advantage to standard operating procedure for businesses. The next wave of competitive advantage is being driven by the depth of sentiment and behaviour analysis as well as autonomy of response. According to the survey, 16.9 percent of organisations in Australia have formalised processes to take advantage of big data opportunities through either an overarching organisation wide initiative or business unit lead initiatives.

“The opportunity for big data analysis is real. Gaining further insight into customer behaviour is now more than just a hot button topic in Australia, it is essential for any data-centric organisation.” Says Vanessa Thompson, Software Analyst, IDC Australia.

Transaction-based industries are driving the requirement for management of entire or segregated customer sets to monitor, capture, respond and target real-time customer activities. With the retail, government and resource industry verticals in Australia, leading the appetite for mixed workload database platforms.

“There are industry specific solutions emerging from the vendor community but with system extracts coming from a variety of sources, the data staging environment and supporting tools remain a critical part of the data management environment,” says Thompson.

Analytically intensive workloads are best supported by specialised analytic databases with certain shared data elements from an enterprise data warehouse environment. Including scenarios to manage both immediate and specialised business unit requirements as well as the overarching single customer view, will become increasingly complex and time-constrained but essential for organisations.

“The use of specialised software for various data warehouse use cases is becoming a way to meet immediate requirements but it doesn’t mean that a free-for-all deployment of independent data marts should be encouraged,” said Thompson.