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IIIS: The 'four Vs' of Big Data

IIIS: The 'four Vs' of Big Data

Storage vice-president says volume, variety, velocity and value key

The four Vs of Big Data are something every storage manager should be looking at, according to Benjamin Woo. The IDC US storage program vice-president said that these are volume, variety, velocity and value.

Woo was speaking at the Implementing Information Infrastructure Symposium (IIIS), which was co-hosted by Computerworld Australia and the Storage Networking Industry Association A/NZ.

IDC defines Big Data technologies as a new generation of tools and architectures that are designed to extract value from very large volumes of data, by enabling high velocity capture, discovery and/or analysis.

"In terms of value, how can my company derive some value to create an advantage over someone else?" Woo said. "Big Data is multi-dimensional and complex…"

Part of the value proposition of Big Data includes data organisation and management, infrastructure, decision support and automation interface and analytics.

Read Big Data - Part 1.

"In terms of Big Data users, we have a big problem around the world because no-one knows what to do with it," Woo said.

"There are companies out there that talk about data scientists, so you need a PhD in data to work this stuff out. They will come and help you out for a fee but until you know what to do with the data, you can't use it."

Turning to the issues of variety and volume, he said that the amount of data generated by Big Data was hard to handle.

"For example, I can suggest you go to the National Library in Canberra and look at all the books but if you don't know what you are learning then what is the point [of looking at that data]?"

However, by implementing the four Vs, local enterprises can gain an advantage over North American and European organisations because of the strong market conditions and opportunity for growth.

Woo warned that Big Data is not something storage managers can take to their chief financial officer and say, "I would like to put $3 million into this and your pay back is going to be $100 million."

"You don't know and this is why Big Data becomes a challenge, because you are making investments in an area to which the payback is unknown."

However, if IT staff looked at data analytics, Woo said they could start bringing those into the organisation and make them part of the process of IT.

"Big Data is all about supporting decisions, so when you are looking at decisions that can have billions of dollars worth of impact, you are going to want as much information as possible to support your case," he said.

Follow Hamish Barwick on Twitter: @HamishBarwick

Follow Computerworld Australia on Twitter: @ComputerworldAU

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