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
Holiday operations can be quite demanding for any organization, but if you operate from the North Pole and work against the clock all year to meet your late December deadline, then you need big data and analytics. Hear what big data and advanced analytics expert Tripp Braden had to say about this
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
To serve citizens effectively and efficiently, public entities can draw from the private sector’s 360-degree view of the customer and apply analytics, big data, Hadoop, machine learning and Spark to create a single or 360-degree view of the citizen. See how this methodology can empower public
In this episode of the Finance in Focus podcast, listen as fintech experts Brett King, Matt Kinney and Bill Sullivan discuss the unique position fintech firms are in to drive the adoption of cognitive in the financial services industry.
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
Learn how IBM SPSS Statistics can enhance the value that statistical analysis adds to a business, and find out how you can tap into the power of high-performance statistical modeling in your own organization.
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
Censuses have long provided governing authorities with data that helps them make decisions affecting the lives and livelihoods of people everywhere. In modern times, however, companies look for more than just a name when doing business—and that’s where master data comes in. Find out how your
Get a head start on the planning and analysis process, and transform the experience with a solution that’s available on premises and in the cloud. Plus, take advantage of a free trial to see how easy performing an in-depth analysis can be.
Essentially, Monte Carlo simulations predict an outcome not from the actual values of input data (which aren’t known) but from the likely (aka “simulated”) values of that data (based on their probability distributions). These simulations can prove invaluable for assessing risks in many real-world
Although spreadsheets offer a stable, attractive option when working with numbers, they can fall far short when they are applied to enterprise-scale statistical analytics. Weigh the limitations of spreadsheets against the benefits of a sophisticated, enterprise-grade statistical analysis tool for
IBM TM1 has been replaced by IBM Planning Analytics. See the new features in this release—soon available on-premises and in the cloud—and why this solution can transform planning, budgeting and forecasting for finance professionals worldwide.
Some financial organizations may have been waiting to make a move to adopt an enterprise-scale planning analytics solution for planning, budgeting and forecasting. Now, the anticipated release of an on-premises and cloud-based version of IBM Planning Analytics just may be the tipping point for
Open source tools continue to foster non-stop innovation throughout the Insight Economy. So it’s no surprise that open-source languages—most notably, R--have moved to the center of enterprise statistical analytics and data management.