IBM Z can help move analytics to the source of data to find deeper, faster wisdom
2/7/2018 12:00:40 AM |
By Steven Astorino
Part one of this two-part series discusses the impact that data is having on decisions and where to run and manage your analytics assets and why. The second article looks at at the impact and benefits of running some of the most advanced analytics on some of the world’s most valued data, and why the IBM Z platform offers unique differentiation.
I’ve heard people say data is the new oil (it also has been referred to as the world’s greatest natural resource) in that it can be refined in different ways and put to many uses. I would argue that data has far more value than oil because once oil has been refined and used, it’s gone. Data, even the same set of data, can be refined multiple times in different ways, and be reused, shared, replicated, federated, linked to other data sources, used to predict what might happen next and help optimize decisions
With so much data being created daily and growing exponentially it can take longer to move data than to process it where it is. For that and many other infrastructure considerations (e.g., security, resilience, high availability and latency concerns), analytics is moving to where the data is. Data is becoming the force that draws analytics applications to it—hence the term “data gravity.”
Figure 1: Analytics Where Data Is
IBM Z Role
Some of the world’s most valued data is stored on mainframes. The platform is capable of 110,000 million instructions per second
, which translates into a theoretical 9.5 trillion instructions per day. With such high-value data, some of which holds highly sensitive financial and personal information, the mainframe becomes a potential target for cyber criminals. Thankfully, the IBM Z platform is designed to be one the most securable platforms. Another key capability of the platform is the integrity of the z/OS system
and IBM’s commitment to resolve any integrity-related issues.
The cost of moving data off the platform is more than just financial labor costs, it also includes
the business risk of moving said data onto platforms that may not have the same levels of integrity and security.
So, if there is so much data and transaction processing in one place on one machine, it makes business and technical sense to allow your business applications; and descriptive, predictive and prescriptive analytics solutions to leverage the same qualities of service as the data they consume. The mainframe has, for as long as I can remember, been a high-powered transaction processing system. And Z clients are moving their analytics and machine learning to where their high-value data is. In essence, the mainframe has become a Hybrid Transaction/Analytics Processing (HTAP) workhorse capable of handling traditional and mobile transactions—and, machine learning and A.I. analytic workloads—that can scale to handle the unexpected.
Solutions For a Successful Organization
Below are some of the key solutions that clients are using around the world to help run business- and mission-critical workloads and extract deep meaningful insights for smarter business outcomes:
Deeper, Faster Wisdom
- DB2 for z/OS: An enterprise database for mission-critical data that provides integration for analytics, mobile and cloud
- DB2 tools: To help maximize database performance and availability, this is designed to reduce cost and help simplify data management
- Data Virtualization for z/OS: Enables transactional access to mainframe data for any application, and virtualizes it with other enterprise data sources in near real time
- DB2 Analytics Accelerator: This workload-optimized system integrates analytic insights into operational processes
- QMF: An enterprise visual analytics and visualization solution optimized for z/OS data sources
- Machine Learning for z/OS: A machine learning solution that enables fast model training, deployment and monitoring to help predict outcomes faster to speed return on investment
With this arsenal of advanced capabilities, organizations that have invested in the Z platform should be strongly positioned to create deeper, faster insights and wisdom to help stay ahead of their competitors.
In the second article, I will be looking at the above solution areas in more detail along with the benefits these capabilities can help bring to Z clients.
Until then, learn more about the power of IBM Z data and analytics needs
Steven Astorino is vice president of Development, Private Cloud Platform and IBM Z Analytics, IBM. Follow Steven on Twitter.