When IBM announced innovations in information integration and governance for big data last fall, we IBMers believed we were on to something. Experience with clients worldwide suggested that automated integration, enabling self-service integration for big data repositories, would be a big deal. A
Are you confident in the analytic insights that drive your business? Do you trust big data? Can you protect it? IBM can help with new innovative information integration and governance (IIG) capabilities to build confidence in big data.
When an organization sets out to become more customer-centric, lots of changes have to happen. Employees—from senior executives to the frontline—must change and adopt new behaviors and mindsets. Processes and technologies must change to reflect the company’s customer-centric desires. Large-scale
Success with big data comes down to confidence. Without confidence in the underlying data, decision makers may not trust and act on analytic insight. Without confidence in your ability to deploy new big data technology and the skills to exploit it, you might defer on big data projects.
In today’s increasingly connected world, machine data analysis is becoming a business imperative. While managing it may be challenging, opportunities abound across multiple industries for those who can tackle this complex data.
"Don't we already have a data warehouse solution?"
"Is big data even relevant to our organization?"
"Why do we need it?"
"Isn't big data costly and hard to implement?"
There is an obvious disconnect between the C-Suite and big data initiatives. Given today’s competitive market it’s hard to
Children are such a glorious creation; being a parent of three (eight, seven and five) I’m allowed to pass judgments like these. They can bring so much joy and so much frustration at the same time. And they are absolutely amazing to observe. Take chores for example: asking them to clean their room
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
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
This is our seventh and final post in a series presenting the findings from the IBM Institute for Business Value and University of Oxford’s Big Data study and excerpts from the report, “Analytics: the real world use of big data in financial services.”
Analysis of the findings by my IBM colleagues
This is our sixth post in a series of seven presenting the findings from the IBM Institute for Business Value and University of Oxford’s Big Data study, “Analytics: the real world use of big data in financial services.”
Analysis of the findings by my IBM colleagues David Turner, Michael Schroeck
Banks face many challenges as they strive to return to pre-2008 profit margins including reduced interest rates, unstable financial markets, tighter regulations and lower performing assets. Fortunately, banks taking advantage of big data and analytics can generate new revenue streams. Watch this
This is our fifth post in a series of seven presenting the findings from the IBM Institute for Business Value and University of Oxford’s big data study, “Analytics: the real world use of big data in financial services.”
As part of this recently published global research study, my colleagues David