Big Data Asset, Liability and Fourth Factor of Production

“Just collecting and storing big data doesn’t drive a cent of value to an organisation’s bottom line,” says Stephen Brobst, chief technology officer at Teradata, the analytics company.

So while many businesses are already capturing big data from sources such as web logs, machine data and text, and inexpensively storing it in open source “Hadoop” systems, complexity and incompatibility issues often make it difficult for them to use standard business intelligence applications and tools to access and analyse the many types of data.

“Business users are clamouring for more access to big data analytics,” says Scott Gnau, president of Teradata Labs, which recently rolled out new software called Aster SQL-H, which is designed to make it easier for business analysts to use raw, multi-structured data in Hadoop files to develop new insights for competitive advantage.

Jim Hagemann Snabe, SAP’s co-chief executive, believes that transforming information into intelligence in real time is increasingly critical for the future of every company. Similarly Informatica’s Mr Abbasi suggests that the wealth of new data now available to companies can bring unprecedented business opportunity.

Whether big data becomes an organisation’s greatest asset or one of its gravest liabilities depends on the strategies and solutions it puts in place to deal with the epic growth in data volumes, complexity, diversity and velocity.

This message seems to be getting through. In a global survey of 600 executives this month by Capgemini and the Economist Intelligence Unit, nine out of 10 respondents identified data as being the fourth factor of production – as fundamental to business as land, labour and capital.

Among the survey’s other findings, respondents said the use of big data has improved businesses’ performance, on average, by 26 per cent and that the impact will grow to 41 per cent over the next three years.

Almost 60 per cent of companies said they planned to make a bigger investment in big data over the next three years, suggesting that the era of big data and big data analytics has already arrived.

Reference