Real time analytics

Compete by driving real-time high quality insights

Why locate analytics exactly where your data resides?

Your competition is the last, best experience your client had. To differentiate yourself you must know how each individual has been interacting with you in real-time - right down to the split second. Generating instantaneous business insights requires co-location of analysis and operations, transforming your systems of record into systems of insight.

IBM z Systems, optimized for real-time analytics, is a platform designed for availability, tuned for flexibility and engineered for the highest levels of security - when both operations and analytics are mission-critical.

Looking to transform operational systems to decision management systems?

IBM z Systems in the Cognitive Era

How can real-time analysis of transactional data give you top-line competitive advantage and reduce bottom-line expense?

New! IBM DB2 Analytics Accelerator V5.1 (US)

Next-generation in-database transformation and modeling optimization provides significant performance improvements in support of real-time, in-transaction predictive analytics by eliminating the requirement to move data off of z Systems for analysis.

New! Zementis for z Systems

Enables truly real-time, in-transaction predictive analysis for a wide variety of use cases by employing the Predictive Model Markup Language (PMML) standard to import and deploy predictive models from most popular tools (SPSS, SAS, R, KNIME, Python, and so on) directly into z/OS transactional applications.

How can you gain deep customer insights by analyzing all of your enterprise data along with social media and other channels?

New! Apache Spark on z Systems

Apache Spark – the “operating system for analytics” – greatly simplifies the programming of analytics and de-couples advanced analytics from a specific underlying data store. Available for Linux on z Systems now and on z/OS by year-end 2015, Spark ensures that z Systems data sources can be accessed and analyzed by data scientists in-place using their favorite languages and tools.

New! Rocket Mainframe Data Service for Apache Spark on z/OS

Rocket Software extends the Apache Spark on z/OS environment with Rocket’s Data Virtualization solution – making a variety of z/OS structured and semi-structured data sources available for direct analysis via Spark.

How can you dramatically improve time-to-value and accuracy of business-critical reports and ad-hoc queries, at a low-cost point?

New! IBM DB2 Analytics Accelerator V5.1 (US)

This high-performance appliance provides extremely fast results for complex and data-intensive queries for data warehousing, business intelligence and analytic workloads. V5.1 also delivers a number of functional enhancements.

New! IBM DB2 Analytics Accelerator Loader for z/OS (US)

Provides capabilities and options for loading data into the IBM DB2 Analytics Accelerator. The solution can increase application availability, reduce overhead and simplify the load process—to deliver increased savings and enhanced business analytics. This latest release adds support for loading a number of non-DB2 data sources.

What if you could use analytics to improve the efficiency of IT operations (e.g. capacity management, outage repair and avoidance) and deliver superior service?

New! Capacity Management Analytics V2.1 (US)

Simplifies the management of applications across the data center and optimizes resource sharing. This latest release offers a variety of new reports, additional analytics, and simplified installation.

New! IBM Operations Analytics for z Systems V2.2 (US)

Formerly IBM SmartCloud Analytics – Log Analysis, this solution provides end-to-end analysis of log data from your enterprise workload, providing insights to diagnose and resolve problems more quickly. V2.2 extends search and analysis capabilities and includes alert notifications, support for Hadoop and role-based access control.

Hear from customers and analysts

Barclays accelerates channel analysis by 60% for better IT decisions making

The analytics implementations of 7 real customers across 4 industries

The ETL problem: The costs of transferring data from one system to another

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