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Some ASEAN sectors take up ‘Big Data’: Oracle

AvantiKumar | Dec. 4, 2012
During a visit to Malaysia, Oracle ASEAN’s enterprise director discusses the company's big data strategy.

Kaleem's picture modified

Photo - Kaleem Chaudhry, Senior Director of Oracle Enterprise Technology ASEAN.


In the next six months, ASEAN's banking telecom and government sectors are most likely to adopt Big Data, according to business solutions provider Oracle, which says that there is a burgeoning understanding of how big data analytics can help the bottom line.

During a visit to Kuala Lumpur recently, Oracle ASEAN's enterprise technology senior director Kaleem Chaudhry outlined the company's big data strategy. "For ASEAN countries, 'Big Data' will spark and reside in a couple of key sectors such as telecoms, banks and government in the immediate future."

"For telcos, especially in the prepaid segment, there is not a lot of loyalty and deep churn is prevalent," said Chaudhry. "By mining data from millions of call data records, a telco can pull information they need to selectively target customers and retain them. For instance of banking industry, bankers can leverage Big Data to build up more accurate risk profiles by mining lots of details of potential loaners."

"For government departments, such as managing homeland security and monitoring dengue fever, the assimilation of various data streams from different agencies is made possible with Big Data systems, which allows the discerning of unusual patterns in the data, pointing to potential risks," he said.
"Other early adopters of big data technology are companies in the manufacturing sector," said Chaudhry. "These companies need to cope with the sheer volume of data. In our discussions with customers, we realised that companies in more matured economies such as Singapore and Indonesia are now starting to seriously explore Big Data issues and their associated solutions."

"Emerging economies still lag behind," he said. "One of the barriers to adoption is the lack of proper understanding of Big Data. There many different definitions of Big Data today, similar to how cloud was loosely defined when it first emerged as a market trend. It was more important to address the challenge businesses face today and the challenge is there's a lot of talk and ideas, but how you turn these ideas into a structured way and how to establish the correlation between unstructured and structured data."

 Unstructured, structured data

"Businesses need to start to establish the correlations between unstructured and structured data, rather than focus only on how to capture unstructured data like social media," said Chaudhry.  "Today, only five percent of data is structured, while the other 95 percent is unstructured data drawn from such sources such as social media networks."

"Such data is being generated very quickly and most organisations are not collecting the data because of the sheer volume, the velocity or speed at which it is being generated, and variety. "If harnessed properly, Big Data can offer new and deeper insights for business leaders. According to a recent McKinsey study, Big Data can increase the value of the U.S. healthcare industry by US$300 billion per year and increase the retail industry's net margin by more than 60 percent. It can also decrease assembly costs in manufacturing by 50 percent."

Chaudhry cited the analyst firm Gartner, which said that through 2015, organisations integrating high-value, diverse, new information types and sources into a coherent information management infrastructure will outperform their industry peers financially by more than 20 percent.

"To be able to captalise on Big Data, organisations need to establish a link between unstructured and structured data and not simply identifying how to capture unstructured data," he said. "Not surprisingly, too much focus is being placed on how to capture and organise unstructured data, but this is only 20 percent of the problem."

"There's no point going through all of the Facebook feeds, LinkedIn connections or tweets if you cannot connect that to your list of frequent flyers---which is structured data--for instance, if you were an airline," said Chaudhry.

"Oracle recognises these realities and as such, the Oracle Big Data Appliance was created especially to ensure that customers get an optimally tuned machine capable of handling all the issues pertaining to Big Data with no complexities of having to install and configure it," he said "With Oracle, customers get a single point of support for hardware, software and customers have a wide choice of service channels."

Oracle's approach comprises four stages, he said. "First, to acquire Big Data, using such products as Oracle NoSQL Database and Oracle Database 11g; secondly, to organise the data before loading it into a data warehouse, using such solutions as Oracle Big Data appliance, and Oracle Big Data connectors and Integrator; thirdly, to analyse the data to extrapolate insights with tools for statistical and advanced analysis that complement Oracle Exadata, including Oracle Advanced Analytics, Oracle Exadata Database Machine, Oracle Data and Warehousing."

"The fourth step is of course to make decisions based on the insights," said Chaudhry. "Oracle Exalytics In-Memory Machine can analyse large amounts of business intelligence (BI) data quickly with a focus on yielding results that can drive both tactical and strategic business decisions."


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