Successful organizations strike a balance between control and speed, moving quickly to explore and analyze big data, but also applying enough controls to avoid missteps with agile integration and governance. Are you confident in the analytic insights that drive your business?
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.
Denihan Hospitality Group and the Cincinnati Zoo and Botanical Gardens use IBM Big Data & Analytics to help acquire, grow and retain customers. They are able to create a 360 degree view of the customer and understand what is most important to their most valuable customers: driving increased
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
Since the IBM PureSystems family of expert integrated systems debuted in 2012, IBM has shipped more than 10,000 systems. To mark that milestone, we are presenting a series of stories about clients whose operations were transformed by IBM PureSystems.
Visit the Expert Integrated Systems Blog to read
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.
Sean Murphy, senior scientist, Johns Hopkins University Applied Physics Laboratory, is this week's Big Data & Analytics Hero. This recognition program was created by IBM to acknowledge and highlight big data and analytics industry thought leaders.
How have big data and analytics impacted how
The amount of data created is growing rapidly and it is expected that in 2020 we will create a minimum of 40 trillion gigabytes; 40 percent of all this data is expected to come from sensors or machine-to-machine data. All of this data will significantly impact global industries, from creating
What is the "connected car"? How will we, as everyday drivers, benefit from it? How are trucking companies, fleet managers and insurance companies using the data from connected cars to save money and improve efficiency? Kimberly Madia, product marketing manager for IBM big data, explains all of
By now you have, no doubt, read countless New Year’s big data prediction posts. I’m sure many of them gave you a well-informed look ahead to this year’s applications of advanced analytics and cognitive computing to help companies acquire, grow and retain customers.
I’d like to make a prediction
"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
IBM has unveiled the new IBM Watson Group via a live broadcast event from New York City. IBM Watson Group will accelerate the development and adoption of a new class of software with cognitive intelligence.
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