Conventional analytics can coexist with big data: Teradata
By Edwin Yapp April 7, 2015
- Traditional analytics still relevant, has a place in today’s big data world
- Disconnect between marketing and tech pros on what big data can do
ENTERPRISES embracing the new world of big data do not have to discard the experience they’ve garnered over the years on information management and analytics, according to industry player Teradata Corp.
Speaking to the media in Kuala Lumpur recently, Martin Wilcox (pic), director of product and solutions marketing for Teradata, noted that there is a lot of hype surrounding big data today, some of which may be justified while other aspects are not.
Because of this hype, there is a tendency for a lot of enterprises to think that with the advent of big data, all paradigms about traditional data analytics go out of the window, he argued.
“Some of the hype would lead people to think that everything we’ve learnt about information management and analytics over the last 20 years is obsolete, irrelevant, redundant, and can be thrown away.
“To be clear, this is not Teradata’s position. We believe that for more structured data assets that we know that are likely to be frequently reused, accessed, recombined and/ or shared across departments and across product lines, the best practice is still to centralise and integrate that data in one place so that it can be meaningfully compared across the organisation.”
As an example, Wilcox said a company still needed to look at sales data to understand product performance; order data to determine supply management; and inventory data, as that’s how a company understands its warehouse and distribution model.
Traditional methods dictate that if you bring those three data sets together, a company can then do demand-driving supply chain management and forecasting, he added.
“The value of the data sets in combination far exceeds the value of those data sets when looked at in isolation,” he argued.
“Thus, a lot of best practices over the past 20 years is still current, particularly when we’re talking about structured data, which needs to be shared and reused,” he added.
Quizzed as to where new big data methods can be used in combination with traditional analytical methods, Wilcox explained that there are still a lot of data out there – particularly outside data such as Twitter and other social media feeds – that could be mined.
“That bit comprises all the data that doesn’t fit that the traditional model. What’s new and different is thinking about how to leverage that data to enhance the analytics and business processes, or to generate entirely new business processes to help companies gain the advantage,” he said.
When asked how enterprise should approach big data then, Wilcox stressed that while technology is important and has a vital role to play, enterprises should go back to the fundamentals before focusing on just the technology.
“For me, it’s about the information management strategy and knowing how to manage that structure that is important,” he explained.
“It also key to start with a business problem or opportunity, and make sure your big data problems and opportunities are aligned with the organisation’s strategic priorities.”
Struggling to tap value
The hype surrounding the use of big data in enterprises has been mounting for some years now. In 2013, Forrester Research argued that Asian organisations are still trying to comprehend what big data really is.
The research firm said that companies must clearly define big data as business projects with technology support, rather than the other way round.
Last year, Forrester also noted in a report entitled Big Data’s Big Meaning For Marketing (subscription required) that big data has the potential to provide new sources of customer insights, allow firms to engage their customers in a novel way, create adjacent business opportunities, and enable digital disruption.
However, most companies still struggle to exploit available data, it added.
Among other things, the authors of the report alluded to the fact that many organisations are still treating data as a tactical tool as opposed to a strategic one, and that there was still a disconnect between marketing and technology professionals as to what big data is and what it can do.
In one of its related surveys, Forrester said that 16% of technology decision-makers plan to implement big data technologies and solutions in the next 12 months, but only 9% of their business counterparts plan to.
“Why the disparity? Because many marketers don’t really understand what big data is and still believe that big data is a lot of hype and that the CIO’s (chief information officer’s) big data initiatives are just a distraction from optimising customer insights or delivering better customer experiences,” it said.
The research firm also noted that for enterprises to really take advantage of big data, they would not only need to have more and different data, but also ‘bigger thinking’ on how to use data, and bigger capabilities to help put all available data to use.
For example, organisations that embrace big data should be able to marry their historical customer, product, and operational data, with real-time behaviours and insights. This would let them hone their predictive analytics capabilities to a fine point, it argued.
“Using a combination of contextual data and predictive analytics, firms should be able to deliver the right content and communication for every customer at his or her exact moment of need, and thus deliver highly personalised customer experiences.
“They should be able to continuously optimise their analytics and insight practices and strike a balance between qualitative and quantitative tools,” it said.
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