Thinking of big data? Think business first, says HDS
By Edwin Yapp December 16, 2013
- Big data is not an IT but a business paradigm, goal is to help businesses gain better insights
- Advanced bio-sciences leading the way, including in cancer and schizophrenia research
ONE of the technology trends that have dominated this year is big data – a term that is ambiguous because it means different things to different people. For instance, a recent New Yorker article said that the reason why scarcely anybody talked about big data until very recently was that it didn’t exist.
“Most data had been, by current standards, small potatoes. Now, big data is mainly measured in terabytes (trillions) and petabytes (quadrillions); within a decade, even those numbers may seem quaint,” the article read.
Indeed, the term big data has a number of definitions. According to Wikipedia, it is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.
Business analytics firm SAS Institute defines it as a popular term used to describe the exponential growth and availability of data, both structured and unstructured.
Earlier this year, Digital News Asia (DNA) reported that the take up of big data systems, solutions and consulting services remains sporadic across the Asia Pacific region.
The report, based on a Forrester Research study, noted that big data adoption and investment intentions at most organisations reflect their ongoing confusion over both the definition and value of big data.
For Japanese storage and software player Hitachi Data Systems (HDS) however, the term big data isn’t about technology as much as it is about business.
Speaking to reporters at a recently concluded media briefing in Sydney, HDS Asia Pacific chief technology officer Adrian De Luca (pic) said that big data should be viewed as a business initiative and not an IT function.
Saying that while big data is about insights into the data collected by a business and how it is able to make use of that data intelligibly for its advantage, De Luca conceded that this is not how many businesses see it however.
“Today, there aren’t a lot of management folks that are treating their data as their greatest capital assets. They are amassing data in their businesses but they do not understand its impact. Big data is really a business initiative, not an IT one. There is change of mindset needed,” he said.
De Luca's argument that many businesses are not treating their data as assets has been validated by a survey conducted by the Economist Intelligence Unit (EIU).
The study, commissioned by HDS, revealed that only a third of the 500 senior executives who responded say that they are in an advanced stage of implementation, with more than half saying they have made little or no progress in their big data efforts.
De Luca believes this mindset challenge is due in part to the fact that there is a lack of alignment in many organisations' internal departments, a challenge that will inevitably lead to the problem of ‘siloed’ information – where information within a company is fragmented and independent.
This situation arises because a lot of big data projects undertaken today are driven by the marketing and/ or supply chain departments within organisations, he said. This is where a company’s first big data project could start, he added.
“In many cases, a company must prepare the data it possesses so that a big data project can begin. For instance, a media and entertainment business has a lot of historical assets sitting in analogue formats. A big data facial recognition project cannot take off unless this data is digitised.
“This is where you need to take the data source and put it into object stores, like a content platform, so that you can attach metadata to the data and prepare for a big data project. This process can help [organisations] ensure that their data is in a state that can be analysed in the future, even if a company is not ready to adopt big data today,” he said.
Why HDS big data
When asked what HDS can bring to the table where big data is concerned, De Luca claimed that the Japanese storage player is in a unique position as its expertise extends not only to IT, but also to other industrial areas, courtesy of being a wholly-owned subsidiary of industrial giant Hitachi Ltd.
According to De Luca, Hitachi manufactures the devices that create big data, such as energy, transportation and healthcare devices and systems, giving it the unique advantage of having back-to-back domain knowledge.
He also believes another way HDS can contribute is to provide expertise on the human resources end. Noting that there aren’t many universities today that offer specific degrees in data science, De Luca said the data scientist role is still very nascent and has not been fully defined yet.
“If we accept that this skill is going to be scarce over the next 10 years, we’d prefer to lead the way rather than to leave our customer to find those skills and to do the integration between big data analytics and the systems that manage them.
“Our strategy around big data is to bring specific vertical big data use cases to customers. If we can combine this together to actually deliver holistic solutions, there will be less need for customers to hire their own data scientists.”
HDS customers can then use its data scientists and they will have the partnerships that will be able to deliver more repeatable solutions across a wider geography more quickly, he added.
Examples of big data in use
According to Dr Ian Gibson (pic), chief executive of Intersect, big data methods are used in researching complex problems faced by humanity, such as cancer genomics, particle physics, astronomy, as well as new sciences such as environmental monitoring.
Intersect is Australia's largest full-service e-research support agency and works closely with the research sector in New South Wales, comprising universities and relevant public and private sector agencies and their collaborating partners.
Speaking at a media tour of Intersect's data centre recently, Gibson noted that university researchers deal with hundreds of big data collections, and thousands of research projects, many of which present different big data problems, and with all requiring deep understanding of their respective research areas.
“There is a new dominant paradigm for science and research as researchers are now able to visualise ways to solve many of humanity’s difficult problems, via the the Research Data Storage Infrastructure project (RDSI) -- all of this would not possible without the use of big data methods We have found HDS platforms to be ideal to support the new world of big data driven science,” he claimed.
The Intersect RDSI node is part of the federally-funded Research Data Storage Infrastructure project and is hosted in Macquarie Telecom’s Intellicentre 2 data centre; powered by HSD technology. Its purpose is to provide free cloud storage for nationally significant data sets, enabling researchers to secure, access and collaborate on these collections.
Gibson said one of the upcoming projects is to understand the complex nature of diseases like schizophrenia, undertaken by the Australian Schizophrenia Research Bank.
“This Australian national project is aimed at discovering the cause of schizophrenia. As the disease seems to be a complex interaction of many genes, often triggered by environmental factors, it would need complex big data analysis.
“The project will comprise the study of 1,500 sufferers and 1,500 control subjects. It will utilise data mining that would involve MRI (magnetic resonance imaging), genome studies, and both clinical, and environmental trials.”
Edwin Yapp reporting from Sydney, Australia at the invitation of Hitachi Data Systems.
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