Improving Data Governance to Supercharge Data and Analytics in the Cloud

Our panel of leading female data and analytics experts discusses how they are enabling data and analytics initiatives in the cloud

It is becoming increasingly clear that the future of data-driven business is in the cloud.

Research conducted by Corinium Global Intelligence earlier this year shows that 94% of the largest financial organizations are now deploying models in cloud-based environments, and 98% accelerated their cloud migration plans during 2020.

However, making a success of digital transformation and cloud migration requires leaping over hurdles like creating the right data culture in your organization, improving and modernizing data governance practices and ensuring good data quality.

Our panel of leading female data executives took on these questions and more in our monthly panel in June, broadcasted live on LinkedIn.

“I think there is a shift that's happened given where organizations were going, but it has been hugely sped up and disrupted by the year that we've had,” said Chanel Head of Global Data Governance Sathya Bala.

She continues: “I think we need to take any opportunity as people in the data industry to find things that allow for flexibility. Because I think that technology and data more specifically have been maybe used as a reason beforehand [to] why organizations have stayed in kind of traditional practices.

Collecting the Right Kind of Data vs. Collecting All the Data

Considering the vast amount of data that modern enterprises generate, it’s hardly surprising that many organizations struggle to know what to keep. As MercyFirst Chief Data Officer Besa Bauta notes, data collection should be prioritized according to business needs and compliance requirements.

“I think [data professionals] operate in a sense of risk mitigation – collect everything, because you don't know what you are going to be asked down the line,” she says. “But it's really important to see which data elements are key data elements to collect. Otherwise, it becomes a huge Herculean test to collect everything, and not all the data has the same value.”

For RCS Bank Head of Data Maritza Curry an important first step is to define an ownership model to make sure that the right person is making the call about what data is valuable.

“If you have a very good data ownership model in your organization, then you have specific people who are accountable for making decisions about data in specific data domains,” she says. “Then they take the accountability to make the decisions around what is valuable and what will support the core capabilities of the organization.”

Preparing Data Quality and Governance Processes for the Cloud

For cloud initiatives to be a success, good data quality and sound governance processes are a ‘must have’. However, as the panel notes, these factors should be defined from the outset.

“Think about how hard it is to introduce data governance into our existing architecture, where you have systems that are limited, legacy systems. I actually think we need to see it as a real positive where we are moving to these new technologies in the cloud,” says Bala.

She continues: “If you've got a cloud initiative, it is so hard to try and retroactively go in and define data, clean data, and agree on data owners. If you have a cloud transformation happening, that is something that you want to set from the start.”

Curry concludes: “Whatever your data governance and data management policies and practices are, those can be extended to your cloud environment. And the advice that I would give, um, organizations is to look at your current policies, standards, and practices, and adjust them for the cloud. You don't have to rewrite them.”

Key Findings

• A turbulent year has created opportunities. Data and analytics leaders can capitalize on accelerated digital transformation initiatives due to the pandemic.
• Define a data ownership model. This will provide accountability and expertise about how to prioritize data storage.
• Update governance processes for the cloud. But you don’t need to reinvent the wheel.