(US and Canada) Rex Davis, Chief Data Officer at RBC, speaks with Maria Villar, Head of Enterprise, Data Strategy, and Transformation at SAP, about technology, the utility of artificial intelligence and machine learning, cloud data management, and creating safe operating places for data scientists.

Davis begins by pronouncing synthetic data as the most exciting element of technology today because, instead of filling up the technological gaps, organizations have been creating complete artificial versions of everything. He states that today, organizations have a simulated field of systems and infrastructure that allow different training models and stress testing while prioritizing privacy.

He then highlights how artificial intelligence and machine learning benefit the present organizational data management scenario. Davis recalls his initial days as a data scientist when he had to make hypotheses first. The benefit of AI and ML for data professionals is that they lead to refined results easily, provided the data is structured in order and data quality is maintained. He also mentions that combining robotic process automation with AI has benefited employees by saving their time, as the RPA handles all tedious and repetitive day-to-day work.

Moving on to  the topic of cloud data management, Davis notes that the need to migrate to the cloud originally started as a business need. He states that the prime focus should now be on how data is shared and augmented across groups and people. He further affirms that keeping eyes on the right strategy is a better way to influence the cloud strategy.

Shifting the discussion, Davis highlights two points to ensure how different operating teams can work better together. First, he pinpoints the need for empathy, and next is to make sure that each professional is guided through the right path to deliver the right duties.

Emphasizing the adversities faced by data scientists in this situation, Davis states that if a data scientist does the job of a data engineer or a data steward, they are bound to go haywire in an organization. He considers this to be a tragedy wherein data-scientists work through all the layers of an organization to carry out an operation.

A data scientist needs a well-set-up space as the operational model wherein they can operate safely, without any barriers. He states that he knows of many organizations that have had a team full of data scientists without having other required elements in order. That is one challenge they need to overcome, to retain talent within the organization, Davis concludes.