This is part six of our series on the findings and text from IBM Institute for Business Value’s latest study and paper: “Analytics: A blueprint for value - Converting big data and analytics insights into results,” from my colleagues Fred Balboni, Glenn Finch, Cathy Rodenbeck Reese and Rebecca
This is part five of our series on the findings and text from IBM Institute for Business Value’s latest study and paper: “Analytics: A blueprint for value - Converting big data and analytics insights into results."
Whether you call it stream computing, data in motion or real-time data, there’s no doubt that one of the most important aspects of big data is being able to capture, process and analyze data as it is happening. This is the velocity component of anybody’s definition of big data.
Unlike data that’s
Some companies in the media and entertainment industry are monitoring social media and integrating social data with other data to form elaborate predictive analytics models. Graeme Noseworthy (Twitter: @graemeknows) describes how they are doing this and what they've learned along the way, including
In my last post, we explored how audience data sources from inside and outside of the media organization can be “unified and utilized” for game-changing applications such as demand forecasting for Opening Weekend Box Office (OWBO) using big data analytics.
Our results showed that IBM achieved high
In my first post I introduced the idea that most “big data” isn’t really big at all, and doesn’t conform to Gartner’s 3V’s. Instead, I've suggested that there’s benefit in focussing on “broad data”, or the use of many different sources of data to give us richer information. We put forward 4O’s of
It seems like a “Back to the Future” moment. Here we are with the IBM InfoSphere Streams v3.2 announcement, the latest version of our product for handling stream computing and complex event processing. Yet 5 years ago this month, we had IBM System S v3.2. Looking back, we had three manuals for
At the start of this year, I had discussed in my blog post “Is Customer the King? In Retail, Analytics Say ‘Yes’,” about how the retail industry can leverage big data insights to optimize and personalize customer interactions, improve customer lifetime value, improve customer retention and
To serve a growing customer base and better manage the client experience across all customer touch points, organisations are moving away from siloed transaction-oriented systems – such as enterprise resource planning (ERP), customer relationship management (CRM) and dealer management systems – in
Customers, prospects, employees, suppliers and competitiors all seem to have plenty to say about you - and plenty of places to say it. Understanding what people think now is great. But in today's fast-paced world, being able to see what they're likely to think and do next can be even more important
Businesses are plunging headlong into the age of social listening analytics without fully thinking through the many issues surrounding the quality of this intelligence. There is plenty of valuable customer intelligence to be had from filtering the social firehose. However, the overwhelming volume,
Do you follow Kristen Stewart or Kate Middleton? Their wardrobe has something in common with Obama’s re-election. It is called social analytics – a field related to analyzing vast amounts of data on people’s behavior, sentiments and patterns. Many factories, from China to Korea, Taiwan, India and a
As of Wednesday Facebook begun rolling out hashtags to selected users (with all users getting the feature within the next couple of weeks). We wanted to try and get behind the curtains and talk about what this feature means for the users and for Facebook’s business model. So we sat down with two
Big data means different things for different industries. The definition also differs within an organization, across departments and management layers within IT and business. Within IBM, big data spans four dimensions: volume, velocity, variety and veracity. At The Big Data Institute (TBDI), big