Future-Proofing Your Data Governance Strategy

Future-Proofing Your Data Governance Strategy

How to manage ever-shifting regulatory standards

This article was originally published on Forbes.com on May 11, 2022 as “Three Tools to Future-Proof Your Data Governance Strategy.”

With increased data volumes and complicated data ecosystems, businesses can no longer “wish” their way into maintaining data integrity. As a result, the C-suite has come to realize a robust data governance strategy is required to manage data controls and expose potential risks. However, with the data landscape constantly changing due to industry disruptions and evolving privacy regulations, a data governance program can be seemingly compliant one day but miss the mark entirely the next.

This became apparent after the predominant General Data Protection Regulation (GDPR) workaround in Europe was recently put on ice when Belgium’s data protection authority rejected IAB’s Transparency and Consent Framework (TCF). While data compliance is still a moving target, what remains constant is the need for a data governance strategy that transcends ever-shifting regulatory standards with the help of a holistic framework that can modulate the collection, retention, expiration, correction, and erasure of data across government jurisdictions. To attain this level of flexibility and control, businesses must first gain an understanding of their current data governance capabilities and then build out a future state that will safeguard information on a global scale. The following are three considerations for future-proofing your data governance strategy.

3 Pillars of a Future-Proof Data Governance Strategy

1. Data Separation

Most brands that have successfully expanded overseas could not have done so without the cloud. The cloud fast-tracks international expansion because companies can replicate environments at new sites with easy-to-use platforms. The problem is that companies scale so quickly now that they rely on outside firms to perform vital business functions. As a result, organizations are forced to broaden their data permissions to unlock these external services and measure business value in the region.

The best way to mitigate the potential risks of multi-tenant environments is through data separation, where users access their information without breaching the security of other tenants. Data separation inherently requires a deep understanding of where workloads and data are coming and going. Once companies can map their data streams, they can then establish buffers that minimize damage if an environment is compromised.

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2. Centralized Catalog

Quickly deriving value from a myriad of data sources can be challenging. One hurdle is that some data sources may contain private information, which, in the current regulatory environment, prevents certain data collaboration techniques that involve the exchange of private information. Having a centralized catalog provides data governance teams visibility into where private information is located in their framework. This becomes important when onboarding new teams, as businesses should be making it a priority to hide private information that may reside in their datasets.

A centralized catalog provides value beyond privacy considerations. Without one, companies are often dealing with sparse quality data scattered across multiple systems and teams, resulting in muddled insights that rarely translate into good business outcomes. In many cases, teams that require access to data are not technical; they just want the business insights from it. A strong data governance framework addresses this dynamic upfront. The ultimate goal is to give teams the right level of access so that no one is stepping on each other’s data.

3. Contextualizing Consent

Whether a business is building its data governance foundation for the first time or looking to update its current approach, consent has to be at the forefront of every consideration. In general, the marketing industry has tried to paint data governance as a struggle between disruption caused by privacy laws and the need to deliver personalized experiences. While there is some conflict, it does not necessarily have to come at the expense of the customer experience. Just as personalization can be contextual, so too can consent, as marketers are governed by different rules based on different jurisdictions and build trust by appropriately soliciting consent from the data subjects for different contexts. For example, the consumers may provide different consents and express preferences for different brands. Without a centralized framework, it is hard for companies to appropriately ask users for consent.

What’s Next

Despite growing interest in data, most business leaders do not fully grasp the operational burdens of data governance. Some vendors fall short of their promises when operating data governance or consent processes at scale, as it requires sophisticated platforms. With many companies still in the early stages of their respective digital transformations, perhaps they are only now understanding where their data is. Governance teams would be doing themselves a favor by clearly articulating that this is a gradual process where everyone is maturing. Over time, businesses will develop data governance schemes that can withstand future disruptions.

Treasure Data provides everything you need to quickly and easily manage even the most complex privacy and consent landscapes. Learn more about Treasure Data’s Trusted Foundation.

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Kazuki Ohta
Kazuki Ohta
Kazuki Ohta is the CEO and co-founder of Treasure Data. He also founded the Japanese Hadoop User Group, the world’s largest such group. Kaz is an acknowledged expert on distributed and parallel computing, and combines his knowledge of these technologies and Hadoop with the conviction that the service model is the only way to bring big data analytics to the mass market.
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