This is the first in a sequence of blogs that takes a peek at what is driving analytics onto the cloud, what are the challenges that will need to be overcome over the next 5 years and how they will be tackled.
In cognitive computing era, new revenue generation stream has emerged with data at center of the modern digital business model. One of the key capabilities cognitive computing enables for an organization is the ability to generate additional revenue streams by using data effectively. In the big
It is said that more data has been created in the past two years than in the entire preceding history of mankind. It would be interesting to find out how much of this data has been analyzed and put to good use. Analyzing and harnessing big data is undoubtedly the major challenge of the day for all
The unprecedented evolution of social media data’s influence on business can have tremendous impact on how customers are integrated into organizational goals and practices. See why more organizations than ever are using social media data to take a customer-centric approach to evolving their
This podcast discusses how embracing the concept of the new killer apps involves people and roles in an organization that need to coalesce around a rational set of business goals in working with data. New teams of people are forming that are data hungry.
Large companies that want to prevent being outflanked by more agile, smaller firms can adopt a new organizational and strategic lifestyle. Listen to a general discussion of Chunka Mui’s book, The New Killer Apps: How Large Companies Can Out-Innovate Start-Ups (Cornerloft Press, December 2013) in
In his book, The New Killer Apps, Chunka Mui, innovation and business strategy consultant, asserts that the conventional wisdom about start-ups being destined to out-innovate big, established businesses isn't true. Read this excerpt to learn how large companies can disrupt too by thinking big,
In a recent CrowdChat discussion, a group of Hadoop and Spark subject matter experts from the IBM Analytics group discussed using cloud-based Hadoop and Spark services as a lever for business agility. From their contributions we drew ten hot topics and themes for experts in all areas of the big
Some organizations misunderstand the optimized way to use Hadoop and Spark together, primarily because of their complexity. But investing in both technologies enables a broad set of big data analytics and application development use cases. See what Niru Anisetti and Rohan Vaidyanathan have to say
IBM has identified a number of common problems that many businesses find themselves facing in their various stages of Apache Hadoop and Apache Spark adoption. As a result, IBM has developed a set of support services to help customers accelerate time-to-value outcomes and reduce risk when building
Without question, our lives are very different from only a couple decades ago, thanks in part to some pretty amazing technology advances including smartphones and other devices, mobile apps, an ever-growing array of social channels and more. Take a look at how one telecommunications organization
At the core of many big data architectures is Apache Hadoop and Apache Spark. Organizations adopting these technologies for their big data journey are nevertheless at different levels of maturity. Hear what Prasad Pandit had to say in an interview with Andrea Braida about how IBM is evolving its
Businesses have come to expect that smart rivals wielding digital technologies will disrupt their competitive landscapes. How ready is your organization to be a digital disruptor? Take a look at detailed criteria for assessing your organization’s readiness and the strategic steps you can take to
Many forward-thinking organizations want to investigate how big data analytics helps them outthink and outperform the competition. However, many also are challenged with finding the right talent to run the operations, keep the data secure and figure out how to leverage the myriad tools at their