If AI is your priority, start with a data strategy

By | 2 minute read | October 27, 2020

man looking at monitors

Every sector in the world is currently investigating artificial intelligence (AI). Groundbreaking advancements in AI will take place in health and life sciences, cyber-intelligence, smart cities and transportation.

But before anyone can execute an AI strategy, they’ll need a data strategy.

When we think about the vast majority of the work that data scientists do, 85% of that work is associated with data governance, cleansing, tagging and classification of data—all elements that are embodied in the concept of a data strategy.

Data insights drive competitive advantage

Thus, harnessing the power of data with AI requires understanding the data sets required and how relevant they are to the insights we are trying to drive.

We have to ask ourselves: is our enterprise data clean and meaningful, or is it filled with gaps or deceitful data? Can we leverage the immense amount of data that’s sitting outside the enterprise such as social media or retail data?

In many ways, our customers are still in the infancy stage of identifying relevant, clean data. They need to understand where their data is and how impactful it can be. Once they do, the stage is set for a meaningful discussion into using that data to drive insights that act as a competitive advantage.

Intel becomes a data-centric company

At Intel, we are moving to become a data-centric company—not only because it’s part of our corporate vision, but also because our customers demand that we do so. They’re determined to find a way to use our infrastructure to accelerate their AI strategies.

We are focused on ensuring that we understand how to optimize workloads and code on top of our silicon to drive the kinds of efficiencies and performance that our clients are asking us for.

Intel and IBM are great partners and closely aligned in becoming more data-centric. IBM has created IBM Cloud Pak for Data, a platform for advanced integration and interoperability of multiple datasets. Our companies are committed to ensuring that it’s optimized for Intel Xeon Scalable processors, accelerating performance for our customers.

Teaming for Discovery and integration of enterprise data

Many of our customers struggle with hundreds of data sets that they need to identify, discover, assess, clean up and integrate. Cloud Pak for Data helps with data discovery and rapid integration of enterprise-wide data, enabling business to deliver hyper-relevant experiences, services and products in the marketplace.

Intel’s participation and contribution is meaningful because customers can run the Cloud Pak for Data at speed on their Intel-based infrastructure. The union between IBM and Intel is supercharging the ability of data scientists to drive better insight and better business outcomes in a way that has never been seen before.

Watch Melvin Greer discuss optimizing insights and business outcomes with IBM Cloud Pak for Data: