Companies want to maximize the data they collect—whether it’s to better understand past events, predict future events, or find answers to questions not previously considered.
Big data analytics allows drawing these outcomes from data, turning it from a simple operational byproduct into an asset that can help reduce cost, grow revenue, enhance customer experience, and gain a competitive edge, said IBM’s Robert Catterall in a recent SHARE presentation.
That’s why the already-massive market for big data and business analytics solutions continues to grow rapidly. Research firm IDC predicts a big data analytics revenues increase of 12.4 percent in 2017, to $150 billion, with businesses in banking, manufacturing, government, and professional services industries expected to also spend $72 billion on related solutions.
However, Catterall says that when they evaluate platforms to support analytics programs, many executives at those businesses will likely overlook a system ideally suited for this work – z/OS.
Most IT professionals view z/OS solely as an operational workhorse, not realizing its potential to improve the efficiency, availability, and scalability of analytics initiatives. In his presentation, Catterall offered a few reasons why IT professionals should take a harder look at Z for analytics.
The Most Valuable Data is Often Already on z/OS
Most organizations already keep their most sensitive and mission-critical data on z/OS. Analyzing the data on the same platform allows companies to combine highly structured transactional data with unstructured data (e.g., clickstreams, geospatial information). Doing so satisfies a major goal of many corporate analytics programs, which strive to find correlations between disparate data sources.
As an added benefit, analytics can be infused into z/OS-based operational applications to enhance their capabilities. Analyzing unstructured SMF data or SYSLOG data provides a real-time view of what’s going on with a z/OS system, said Catterall.
And the fact that z/OS is such a highly scalable platform – a system can handle both high-volume transactions and analytical capabilities simultaneously – means it is ideally suited for analytics consolidation. In other words, you can draw data from other platforms into z/OS for analysis, which improves the efficiency and economics of your entire program.
z/OS is Reliable, Scalable, Available, and Secure
Why does a company keep its most mission-critical data on Z? Because of its reliability, scalability, availability, and security.
All of those are important qualities for analytics, which has increasingly become mission-critical, said Catterall. IBM continues to develop z/OS to meet high expectations for quality of service, which means enterprises can trust in its ability to support tier-1 analytics programs.
New Technologies Make Analytics on z/OS More Economical
A number of emerging technologies – including Linux on IBM Z, open source on z/OS, zIIP engines, and the DB2 Analytics Accelerator – have “fundamentally altered the economics of doing analytics on Z,” said Catterall.
In particular, the DB2 Analytics Accelerator offers many capabilities that save storage space and improve performance for complex or data-intensive queries, without fundamentally altering analytics-centric database design. Ultimately, these features add up to a much more cost-effective analytics program running on z/OS. We’ll dive into other benefits of the DB2 Analytics Accelerator in a future post.
To learn more about the analytics capabilities available on z/OS, watch the full video from Robert Catterall’s presentation in the SHARE Content Center.