Technology

Driving Digital Transformation With Data Science

So much data flows into and out of today’s businesses. Learn how successful organizations are able to crack the data science code and turn this data into actionable insights.

Few people will dispute that organizations have more data than ever at their disposal. But actually gaining meaningful insights from that data—and transforming these insights into action—is easier said than done. The bigger challenge, however, is how to effectively navigate through this massive amount of data in search for the right data needed to provide the necessary insights to successfully run the organization.

CIO defines digital transformation as “the acceleration of business activities, processes, competencies, and models to fully leverage the changes and opportunities of digital technologies and their impact in a strategic and prioritized way.” But more than just acceleration, digital transformation is about the need for businesses to outpace digital disruption and stay competitive in a rapidly evolving business environment.

By observing patterns in data and creating software that can regularly and reliably turn that data into actionable insights, data science can give your company an advantage that competitors can’t beat.

Modern enterprise technologies generate vast amounts of data, which can be challenging and time-consuming to analyze. By building data science models that are accessible, meaningful, and actionable, however, new opportunities can be identified quickly and speed up decision-making.

To do that, data science models should be:

Consumable—You shouldn’t need a PhD to benefit from data science. Having access to easily consumable, real-time insights and visualizations of complex sets of data can unlock new opportunities and revenue streams, help improve customer relationships, and help improve your bottom line.

Adaptable—Your data science models should be self-learning and highly automated, so users can get the most from them. Not only must your models learn and evolve, but your models and data must also be accessible through your existing enterprise platforms, so everyone can easily get to them.

Transparent—Your users must be able to drill down to understand the data that are driving the recommendation. When users understand the recommendation as well as the reasons for that recommendation, their experience is more meaningful.

There is no doubt that data science needs to be a fundamental component of any digital transformation effort and has incredible potential for businesses of all types to drastically improve operational efficiency across the board. A world of possibility awaits organizations that can crack the data science code.

To learn more, download the whitepaper, “Driving digital transformation with data science.”