Big data, stupid term

Ben Kepes is on the money when he says: “Big data is a stupid term”.

It is stupid because it is ambiguous. The term could mean many things.

Big data is stupid because it is loosely defined even within its own little world. At what point does data become big? Is there a point beyond big?

How about enormous data? What do you call bigger data? Is data ever really that big in a little country like New Zealand?

The term is stupid because on its own, big data doesn’t mean anything until the data is used. Then it becomes something else, like Useful Data. Or machine learn ing. Used well, it might even become Information.

Kepes goes on to talk about SAP’s HANA which deals with real-time in-memory data. That’s exciting. Far more exciting.

SAP Business Suite on HANA, Because Big Data is a Stupid Term | The Diversity Blog.

Big data projects hampered by poor skills

Businesses in Australia and New Zealand are not getting the results they hoped for from big data projects.

Less than one in eight report success with their strategies.

Among other issues, they have trouble finding people with the skills needed to make sense of the technology. They also struggle as poor communications mean company departments are unable to co-operate on the level needed to gather data for analysis.

The problems come to light in an Economist Intelligence Unit research paper sponsored by Hitachi Data Systems. The EIU reports a lack of in-house skills is the biggest barrier to adopting big data in Australia and New Zealand.

Companies also say a lack of suitable software and issues with over-complicated reports are problems.

The survey found nearly 40 percent of organisations don’t have a big data strategy because they can’t see a path around the skills and communications challenges.

Big data expectations

Despite the drawbacks, respondents think big data can improve their businesses.

The report says 92 percent of businesses rely on internal data, while 53 percent take data from third-party providers, 37 percent use social media sources for data insight.

Machine generated data is on the rise with 20 percent of companies using sensors, smart grid, RFID, network logs and telematics.