Value of big data analytics largely untapped
SINGAPORE--The current hype around big data analytics is essentially missing the fundamental proposition, which is really about what value businesses get from the analyses and how these can be monetized or churn higher returns on investment.
Scott Gnau, president of Teradata Labs, said no company has the appetite to store all their big data and then analyze this unless it is of any value to the business, and they can learn something from that information. Gnau, who is based in San Diego, United States, was speaking at a media roundtable held here Tuesday during the Teradata Universe event.
Just as a storage vendor would only want to talk about data deluge in terms of the sheer volume of data, he noted that the "emotions" from people "feeding the hype" have so far been about how to manage and analyze big data, but "nobody talks about what it's worth"--much less how to monetize that value.
Data, in all its forms, is increasingly a competitive advantage for enterprises which should explore big data analytics to "unlock" insights from the data, and make better business maneuvers and decisions, Gnau said. But these efforts would all be just "an interesting science project" that will eventually die out, unless companies gain value from the investment.
"There's [certainly] value, but I don't believe many have found it yet," he noted.
He added that getting value is not always about direct monetary gains. It is also about an organization's ability to tap analytical content to drive business goals, such as customer loyalty or profitability.
For example, Gnau said, big data analytics can help a bank discover and understand the path customers take before they finally decide to close their bank account. That information is valuable when it is combined with analytics of other customer data types such as user profiles or deposit and withdrawal histories.
So when the bank notices a particular user is already halfway through the churn path, it can decide whether that customer is profitable, or should not be retained, and act on the appropriate response, he said.
Pushing cloud limits for data warehousing
Gnau also talked about the limitations of cloud in data warehousing, pointing to common perceptions about security and privacy.
He said most enterprises were protective of what they regarded as their most valuable and proprietary data--housed in data warehouses--and hence, would not take risks with cloud.
Other enterprises, such as those in banking and healthcare, were prohibited to implement cloud services for their data warehousing needs due to industry regulations, he added.
He also highlighted economics as a barrier because, due to their sheer volume, operating data warehouse workloads via an external, public cloud was taxing on performance levels as well as network and bandwidth costs.
Organizations want to keep all their important data internally within the company, but they also want to enjoy the benefits of cloud computing technology, Gnau said, adding this was where the storage vendor hopes to address with its Teradata Active Data Warehouse Private Cloud. The product was launched in Southeast Asia today at the Teradata Universe event, expanding its availability beyond North America, Europe and Asia-Pacific.