(US and Canada) Drew Smith, VP of Global Data & Analytics at Little Caesars Enterprises and IIitch Companies, speaks with David Yehle, VP of Global Sales and Field Operations, Acceldata, about the notion of data governance versus data operations, realistic goals, cloud migration, and his views on data reliability.

He says data governance is process- and procedure-driven; data operation is a task. Smith notes that understanding data flow is a challenge. He also mentions that data operators cannot treat data as an asset without proper data governance.

A CDO is a strategic role in achieving realistic goals, Smith continues. If the employer feels good about hiring him, Smith says, it’s a sign of success. In the long term, a CDO must start from a ground truth to build and maintain same-store sales accuracy. Depending on the goals, the faster CDOs get people to act on data and increase the clock speed.

Smith refers to migration to the cloud as a significant change. He adds that the cloud has been around for some time, but successful migration stories are few. The cloud is critical for little Caesars, given the vast amount of data generated from sold pizzas.

Although the cloud is a much-needed resource now and in the near future, Smith is wary of cloud providers using embedded tools. He senses that these embedded tools increase cloud dependency and generate cross-incentives. In addition, Smith indicates there might be a need to migrate back to on-premise after running over the cost cliff.

Smith maintains that along with auto-discovery tools and AI and ML, new tools help with data governance. He also mentions automation. Smith confirms using Databricks, Kubernetes, and other tools to handle unstructured data. Additionally, he maintains that CDP tools generate analytic insights for outbound marketing activities.

In conclusion, Smith states that he learned the concepts of data virtualization and data fabrics over time. He commits to learning from the tech and data geeks to build a bridge of trust, understand the issues in the present tech scenario, and enhance data accuracy.