In any enterprise, digital transformation is not only a technology transformation but enables business transformation itself, driving new products, solutions and innovations. Having an efficient data strategy is critical to any successful digital transformation but requires careful investment into both people and systems. “To achieve that goal, availability of good data, of the right data, and availability of that to the right people and systems is very, very critical. So that forms the data strategy for an...
In any enterprise, digital transformation is not only a technology transformation but enables business transformation itself, driving new products, solutions and innovations. Having an efficient data strategy is critical to any successful digital transformation but requires careful investment into both people and systems.
“To achieve that goal, availability of good data, of the right data, and availability of that to the right people and systems is very, very critical. So that forms the data strategy for any enterprise today,” says chief architect for data and AI services at Kyndryl, Sundar Shanmugam.
Getting the most out of digital transformation investments means evaluating and optimizing agility throughout an enterprise to drive actionable insights, says Shanmugam. A strong data governance framework also goes a long way in keeping data high-quality. Often data governance primarily serves regulatory requirements. But truly effective data governance is holistic, he adds. Data usage, regulations, and the data itself are constantly evolving within an enterprise, effectively making data governance a continuous process.
Although tech teams are often dictating how data should be managed and used, Shanmugam says everyone across the enterprise, including leaders and decision makers, should be data literate.
“End of the day, the people are the ones who design the systems and who develop the systems that consume the data, so the right investment on literacy is paramount in that aspect,” says Shanmugam.
Another key component to digital transformation lies in maximizing investments across business units. The combination of software development and operations to form devOps, AI and machine learning to form MLOps, and finance and operations to form finOps all fall under the broader umbrella of XOps that categorize these merging of IT disciplines with business operations. XOps all come together to deliver value in the most efficient way with each combination focused on maximizing automation, reusability, and agility, says Shanmugam.
“As we say, necessity is the mother of innovation, so that necessity can continuously change,” says Shanmugam. “At the core of that, if we keep that data proper [condition], then it can expand the horizons, not just internally, but even for the other external requirements and use cases.”
This episode of Business Lab is produced in association with Kyndryl.
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