Big Data Info


As the world grapples with understanding the technology that deciphers large volumes of structured and unstructured data, this section will keep our readers abreast of the key developments in the Big Data domain.


We have been quoted in Australia's BRW magazine

BRW, a highly respectable magazine published by the Australian Financial Review Group, has quoted Raj Dalal extensively, and reported on some of the key findings of the BigInsights BigData Survey 2013 in a report on the role of Big Data in the retail industry. We bring you the excerpts from the BRW story:

Raj Dalal, the founder and chief executive of big data research firm BigInsights, says corporate Australia is slowly starting to understand that data is the future for commerce. “There is a growing realisation that the next wave of competition in the retail sector is going to be the battle for the customer, in the sense that they will be using all that data there is at the company’s disposal,” he said. Big data means large pools of data that can be captured, communicated, aggregated, stored and analysed, according to McKinsey Global Institute (MGI), the research and economic research arm of McKinsey & Company.

The key thing about big data is that it is a “one-to-one personalisation story,” says Dalal. All of that information is narrowed down to creating a better and more personalised experience for a shopper. Big data excels at this. But, as Dalal says, most companies don’t get that marketing and, by extension, big data, has to be aimed at the individual. It may be dubbed big data but it just means companies should have even smaller targets. Research into the marketing sector supports this.

Click on the link below to read the entire story.

BRW - Coles, Woolies and the big data arms race

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 Glimmerglass announces insight analytics for Big Data flows

Glimmerglass Optical Cyber Solutions, the solutions developer and marketer for a safer and more reliable cyberspace, has announced CyberSweep Sapience, a data insight analytics solution that instantly delivers actionable information from Big Data flows. CyberSweep Sapience instantly discovers the source and identifies entity relationships from raw data.

To read up on the rest of the article, click here

IBM Rides Analytics, Big Data to Banking Wins

IBM continues its push to secure more customers in the banking industry and is leveraging its strength in big data and analytics to do so. Big Blue announced new banking wins in South Africa and China. The company said Nedbank Ltd., a financial services provider throughout Southern Africa, is using IBM's predictive analytics solutions to improve the customer experience and provide more responsive real-time services.

Check out the story in eweek.

Microsoft: Enterprise Social, Big Data Among Top IT Trends for 2014

In the new year, enterprise social networks will grow up, and businesses will find themselves challenged by managing a deluge of data caused by the Internet of things. New challenges and opportunities await the IT industry in 2014, according to Susan Hauser, corporate vice president of Microsoft's Worldwide Enterprise and Partner Group. And in her interactions with customers, she has identified some areas the company expects to have a big impact on how enterprises devote IT resources in the coming year.

Check out this report in eweek

Big data startups pull in big money in 2013

Investors have pumped $3.6 billion into startups focused on big data this year. Not too shabby: It’s almost three quarters of all the money that’s gone into such companies from 2008 to 2012, according to a new infographic out today from burgeoning site Big Data Startups.

Check out this infographic in VentureBeat

IBM, Cloudera Partner on Big Data Offerings

Big data Relevant Products/Services company Cloudera and IBM’s SoftLayer are getting in on the turnkey data center Relevant Products/Services software Relevant Products/Services action. The companies just announced multi-layer SoftLayer infrastructure Relevant Products/Services solutions running the Cloudera platform. The on-demand solutions are built on bare metal servers engineered for Cloudera best practices and designed and deployed through SoftLayer’s solution designer tool.

For the whole story in CIO-Today, click here

 Why Big Data Is Mostly A Matter Of Science

This is not a new idea, being several hundred years old. The key advance of the scientific revolution (and associated industrial revolution) was in order to understand something you had to measure it – that is gather the data.

The modern hoopla about “big data” is simply the scientific method applied to a wider range of problems. Doing this cheaply enough is the challenge.

While the idea of collecting the data is the most fundamental, it is not sufficient. Analysts need to make sense of the data. The field of statistics was developed well over a century ago to help do so, originally for kings so they could know how much tax they could raise (the word “statistics” shares etymology with “state”).

Statistical thinking involves computing functions of data. Until recently the ability to do these computations was a major bottleneck. The many orders of magnitude in reduction of cost per byte stored or computation done that we have seen in the last couple of decades (driven by technological advances in chip fabrication and disk drive manufacture) has removed the old bottlenecks. It is this reduction in cost that has enabled the “big data revolution”.

For the whole story in, click here

 Five tips for marketers to get the most from their big data projects

Marketers were among the first business groups to see internal (and external) data resources as a goldmine waiting to be exploited rather than a difficult-to-manage constraint. They have been quick to understand the value of getting immediate insight into customer behaviour as and when required to be able to influence how consumers act at the point-of-sale. At the same time, they want to analyse vast volumes of data quickly to drive the analysis and segmentation of different groups and achieve more accurate targeting of customers and prospects.

For the whole story in The Guardian, click here

Seeq Announces $6M in Series A Funding to Bring Big Data to Industrial Process Data

Seeq™ Corporation ( today announced a $6 million Series A funding led by Second Avenue Partners with participation from Madrona Venture Group, Clear Fir Partners, Gaylord Kellogg, John Meisenbach, and others. Seeq software and services transform industrial process data from sensors and instrument systems into useful information and actionable intelligence.

Seeq is led by Steve Sliwa, former CEO of Insitu, an unmanned aircraft systems developer that was acquired by Boeing in 2008. Sliwa launched Seeq in May 2013 with an experienced founding team that includes executives, engineers, and data scientists formerly with OSIsoft, Honeywell, Microsoft, and Insitu. The company is headquartered in Seattle and has satellite offices in the western United States and Canada.

Here's the whole story


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