Over the last couple of years, data analytics has been touted as one of the most important technological trends in enterprise IT. But how much data do enterprises actually analyze? Very little, if vendors of analytics solutions are to be believed.
According to Sunil Jose, MD of Teradata India, most organizations across sectors fail to analyze 80 percent of data generated by them, which as a result lies unattended. This data that is generated by firms but left untouched is defined as buried data. Jose explains that the problems of having such high volumes of unstructured data varies across industries. A telecom company, for instance, has a higher ratio of data that could be buried without risking its operations, unlike say a traditional manufacturing or a logistics firm.
Sridhar Iyengar, VP of ManageEngine, defines buried data as “data which doesn't necessarily talk to each other, and reside in silos.” He stresses upon the importance of critical insights that can be obtained from this data to gain visibility into an organization’s performance and possibly improve efficiency. Unused data can lead to inefficiencies, resulting in loss of revenues and even customers, he says.
If all this data is so valuable, why are organizations letting so much data remain buried? Ram Yeleswarapu, president and CEO of TAKE Solutions, explains that analytics initially focused on answering selective questions resulting in selecting sets of data which answered only a specific query, thereby leaving a large quantity of data buried in source systems. Additionally, for many organizations employing legacy applications modelled on older technologies, data storage and processing proved to be quite an expenditure, resulting in data getting buried.
Jose emphasizes on how unstructured and unused data can help the information provided by structured data by creating greater value for core business applications. “Packaged enterprise applications such as customer relationship management (CRM) systems and enterprise resource planning (ERP) systems have not realized their full potential today because important data maintained in unstructured repositories is often too expensive to integrate,” he says. This buried data can provide information to improve processes such as IT service delivery, customer satisfaction and inefficiencies in IT, and eliminate the risk of stagnating at existing levels of performance.
While Iyengar believes that the size of buried data is insignificant, he stresses upon its potential and insists on how the correct utilization of this data will help organizations flourish.
Yeleswarapu says that the identification and processing of lower granularity of data took place when CFOs were held accountable for the financial crisis in their companies and were asked for more information. This proved to be a wake-up call for organizations to process and ‘unbury’ more data from the transactional systems for downstream usage.
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“As the role of CFOs changed from being operational to driving organizational strategy and growth, the need for more granular data that would otherwise be buried, became significant,” he says.
How have times changed? Are organizations still in the dark about the data they buried or are newer analytics tools and solutions helping organizations overcome this loss? “The technology revolution has led to lower storage and processing costs. This has helped organizations look into unearthing data buried within their organization boundaries,” Yeleswarapu says.
The analysis of buried data is crucial for customer experience management, inventory management and employee satisfaction. “Buried data is to be exploited and leveraged for competitive advantages,” says Jose. However, he says that this analysis should not be performed in isolation but in integration with certain amount of structured data using techniques that are now available in the market.
Iyengar advises companies to use analytics tools which are “easy enough to be used by a non-expert” but also smart enough to be “able to slice and dice the data to run and visually interact” with possible scenarios.
With every company deriving vast amounts of unstructured data from a variety of sources, will organizations be able to make sense of their buried data? Only time and analysis will tell.