Balaji Ganesan

Balaji Ganesan

The primary challenge for Chief Data Officers (CDOs) is getting faster access to trustworthy data for various business lines. The productivity of data scientists, business analysts, and other end users suffers when they’re waiting for the necessary data to do their jobs.

CDOs want their organizations to become data-driven, which inherently requires faster access to data spread across cloud services. However, with the traditional top-down, dictated style of data governance (in which IT is the gatekeeper for data access, tools, and governance policies), business lines are frequently denied data access when they need it due to the time it takes to onboard their users.

This conflict partly arises from three different parties in traditional governance models. Data Policy Drivers understand governance policies, but not the tools or  how data impacts the business. Policy Implementers (IT) understand the technology but not the meaning of the data, while Data Consumers understand the data but not the policies or IT systems involved. This dilemma slows access to data, lowers productivity, creates tension with IT, and diminishes the ROI for data initiatives.

CDOs can overcome this longstanding challenge with a delegated data  governance model, which leading analysts indicate is a natural evolution of the dictated and decentralized models in which business lines have respective governance policies that result in silos and conflicts with each other. With this delegated approach, data stewards configure centralized policies for respective business lines, resulting in faster access because stewards understand the data. More importantly, this strategy creates a winning situation because governance councils still centralize policies, IT still selects and configures tools, and stewards who know data implement controls for quick, secure data access for analytics.

Governed Data Sharing Results in Strategic Data Assets

Data stewards play a central role in the delegated data governance model that helps CDOs get rapid access to data for analytics teams. They understand what the data means, the business use cases the data supports, which users need what data, and why. Consequently, they can tailor centralized policies to meet the needs of users in diverse business lines with, for example, different data stewards in finance, marketing, or HR. Delegating governance authority to data stewards gives the business local enforcement of centralized policies for faster data access and more effective data governance.

There are a couple of key outputs of this paradigmatic shift in data governance from dictated or decentralized approaches to the delegated model. CDOs meet their goals of helping business lines become more data-driven. Data savvy data stewards become the point of access for making data available to business analysts and other data stewards, freeing IT teams with limited knowledge of data from this responsibility. Most of all, the data consumers enjoy quicker access to data, more profound insights, and better job performances.

Despite achieving core objectives of increasing data’s availability, hastening the speed at which it’s accessed, and enhancing its secure governance, there are other ways CDOs benefit from the delegated governance model. The first is that data from a multitude of sources, owners, and formats becomes a strategic asset for any line of business. Instead of thinking about where data  resides and what must be done to use it, consumers can simply conceive of it as an asset for their individual needs.

The IT group also benefits, as they can logically group data across cloud services for use in business functions like sales, marketing, or other departments. Instead of worrying about different access controls, policies, sources, clouds, or permissions, a marketer can simply request marketing  data from numerous sources aggregated into a logical data asset. When properly implemented with a credible governance solution, all of this complexity will be automated via access control mechanisms performed from a single platform.

Accelerating Analytics While Achieving the CDO’s Dream

This delegated data governance model gives CDOs everything necessary to cultivate an adaptive, data-driven organization for analytics users enabling data scientists, for instance, to access sales data from sources like Databricks, Amazon S3, Snowflake, and other options. That data would automatically span multiple locations, sources, and clouds. Users might not even know—or care—where this information is from because it all will have been vetted according to centralized governance policies locally enforced for their immediate consumption.

This approach is also ideal for sharing data between teams, departments, and users. For instance, a finance team member might choose to share relevant data with the marketing team—which is almost impossible to do with the decentralized model and highly time-consuming with the dictated model.

= It also removes the wait for data (and for IT teams with top-down governance), reduces time to value, and boosts the ROI for data-driven processes.

Most significantly, it empowers data consumers by giving them the right data as a strategic asset to do their jobs well, reinforcing data culture. This newfound speed and agility are ideal for adjusting to emergent business circumstances and hinges on data savvy data stewards configuring and enforcing central policies for the local lines of business. Thus, everyone gets what they want without the hassle or the wait.

About the Author

Balaji Ganesan is CEO and co-founder of both Privacera, the cloud data governance and security leader, and XA Secure, which was acquired by Hortonworks. He is an Apache Ranger committer and member of its project management committee (PMC). To learn more visit or follow the company on Twitter.