By Vikas Sinha, SVP of Mainframe Business Unit, CA Technologies
What do your DBAs and SysProgs think about data? Do they see themselves as custodians of a treasure trove of untapped business value and potential innovation? I would go out on a limb and say most don’t. Here are three opportunities for data stewards and custodians to work with data scientists, line of business and analytics teams to reduce the time taken to develop insights.
Opportunity 1. Support algorithms and machine learning
Gartner predicts that “by 2020, algorithms will positively alter the behavior of over 1 billion global workers.” Mainframers can actively improve machine learning by offering high-volume mainframe data to refine and train algorithms. This approach is already in play in IT operations management. Machine learning is used in predictive analytics that takes log data to dynamically determine thresholds and predict outages. This is a great example of how data can significantly improve mainframe performance and enhance your customer’s experience.
Opportunity 2. Get better results from Big Data tools like Spark and Hadoop
Hadoop remains the most economical all-round choice for processing vast amounts of structured and unstructured Big Data. But with Spark, a newer computing framework, diverse data can be fed into your analytics system almost as soon it’s captured on the mainframe. Spark’s distributed memory-based architecture provides speed and ability to handle streaming data, making it better suited to machine learning, as algorithms can be trained in-situ and refined in near real-time. These real-time insights can be used in innovative, value-driving ways: from dynamically delivering customer recommendations to more accurately predicting infrastructure performance.
Opportunity 3. Test new business models with Blockchain
In Gartner’s view, “by 2022, a Blockchain-based business will be worth $10 billion.” A Blockchain is a “chain” of data “blocks” that prove a sequence of events has taken place and which can’t be changed by an individual. Best known as the underlying technology for crypto-currencies like Bitcoin, PwC says of Blockchain: “The major innovation is that the technology allows market participants to transfer assets across the Internet without the need for a centralized third party.” The mainframe’s ability to quickly and securely process very large data sets means it will play an increasingly central role in Blockchain’s move into the mainstream for financial services and other industries. Is this another emerging area that your mainframe and data teams could be engaging with right now?
As data experts, DBAs and SysProgs have spent a number of years owning the keys to the data kingdom. In my experience, the hardest part of applying machine learning in a business setting is knowing the art of the possible, understanding the business scenarios that can be improved to yield better value. We all need to do a better job of identifying the keys to driving business value. And then we need to deliver them – together.
 Gartner, Inc: Top Strategic Predictions for 2017 and Beyond: Surviving the Storm Winds of Digital Disruption, October 2016