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IBM TM1 has been replaced by IBM Planning Analytics.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.
Do you find yourself increasingly having to make decisions amid uncertain conditions? The advanced capabilities offered by IBM SPSS Statistics aim to make Monte Carlo simulation a part of your risk analysis by bringing these two worlds together in a single software solution.
Spreadsheets are excellent tools as far as they go—but how far can they truly go? If you’re pushing your spreadsheet-based solutions beyond their viable limits, then they might be doing more harm than good. Discover what considerations you shouldn’t ignore when using spreadsheets for statistical
Look for IBM to launch the on-premises version of its enterprise performance management solution, IBM Planning Analytics, at for IBM Insight at World of Watson 2016. Check out the new features and business benefits of this new release of a leading-edge financial and operational performance
Data analytics is no longer an either/or choice. With the integration of IBM SPSS Statistics and R, you can bring together the statistical analysis and data management capabilities that have helped so many data scientists gain insight after insight from their data.
The combination of Jupyter Notebooks, Apache Hadoop and Apache Spark has become a killer app for data practitioners. It unlocks the ability to explore, visualize and experiment with both structured and unstructured data sets with great ease and efficiency. We spoke recently with Chris Snow at IBM
Apache Spark, sometimes called the “analytics operating system,” is empowering organizations of all kinds through machine learning by helping them create unprecedented value from their data. Discover eight ways that Apache Spark’s machine learning capabilities are driving the modern business.
IBM extended Big SQL, which was formerly exclusive to the IBM Open Platform (IOP), to the Hortonworks Data Platform (HDP) in September 2016. I recently spoke with Berni Schiefer, an IBM fellow in the IBM Analytics group, to learn more about the offering and the ongoing IBM focus on SQL.
The movie Deepwater Horizon that depicts the oil spill disaster of the same name serves as an example of how government agencies and corporations need to collect a lot of data and disseminate information immediately as events quickly unfold. Not only are all parties involved asked for a tremendous
Although formerly exclusive to the IBM Hadoop Platform, the extension of Big SQL to the Hortonworks Data Platform (HDP) meets the challenge of complex data warehousing queries on Hadoop. See what Paul Yip, worldwide product strategy for Hadoop and Spark at IBM, has to say about what this transition