Top 5 Drivers of Enterprise Data Governance

Tally Netzer

Tally Netzer

Product Marketing Manager, K2View

Enterprise data governance should not be taken lightly. Multiple market trends are driving companies to make data governance a top business imperative

Table of Contents


Enterprise Data Governance Challenges
Enterprise Data Governance Drivers
The Right Data Governance Strategy

Enterprise Data Governance Challenges

The growing volume and complexity of data make it harder to manage, and enterprise applications, deployed across disparate cloud and on-premise environments, create an even bigger obstacle. Companies face a dynamic data privacy landscape, where new laws and amendments are constantly popping up, and the online world marches at a fast pace that enterprises struggle to keep up with. There is pressure to grow and improve cost-efficiency, while avoiding mistakes that are not easily forgiven due to fragile consumer trust.

Still, despite, and perhaps because of, the above challenges, enterprise data governance is more critical and needed than ever before. It presents clear benefits that are more than enough to encourage companies to invest in this area.

Enterprise Data Governance Drivers

  1. Data privacy compliance

    Enterprises must remain compliant as new regulation comes into play in different regions. Laws such as GDPR and CCPA, have transformed how businesses and consumers approach data issues, and many more are set to follow. Managing their data accordingly is the only way businesses can avoid heavy fines, a media crisis, and losing customers’ trust.

    Companies need data governance tools that supports the entire data lifecycle, including ingestion, processing, storage, use, communication, and deletion. Since privacy laws are local, the chosen enterprise data governance solution needs to embed privacy in a way that easily adapts to fit specific regional requirements.

  2. Analytics optimization

    When the Big Data revolution started, and even before, many businesses focused on collecting as much data as possible. They soon learned that it’s not enough to collect data, you also need to analyze it turning data into valuable information and actionable insights.

  3. Digital business

    An enterprise must always ensure that its data is always complete, managed, updated, compliant and secure. This trusted data is then fed into real-time analytics engines to enable companies to make informed decisions – instantly, and at scale. This is operational intelligence at its best. With real-time data governance, companies can leverage their data to significantly boost digital business performance.

  4. Consumer trust

    The link between data and trust has been established many times, and it’s easy to see why companies with strong data governance capabilities grow their business with transparency. Enterprise data governance allows companies to embrace data capabilities, like personalization, in a compliant way that builds trust. Together, trust and transparency can go a long way in delivering value to businesses and their customers. Today’s customers are used to sharing their data with companies, as long as it provides them with value, like special offers, discounts, recommendations, etc.

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    Business-focused data governance promotes cross-functional team collaboration.

  5. Operational efficiency

Data can be used not only to increase sales, but also to improve every aspect of the company’s operations. The right data privacy management tools need to govern massive amounts of data to deliver business value – e.g., reducing costs, reaching critical decisions in real-time and with greater accuracy, improving profitability, or beating the competition. Data-driven automation is paramount to operational efficiency at the pace and scale of digital business.


The right data governance strategy

As we can see, there are compelling reasons to invest in enterprise data governance. However, overcoming the challenges to deliver business value requires a business-focused data governance strategy; one that promotes cross-functional team collaboration to align on shared data-driven business goals. One aspect in particular opposes the traditional approach to data governance. To deliver the trusted and compliant data needed to drive real-time decisions and instant interaction, data governance cannot operate as disconnected policies and best practices. It must be embedded within data operations as active data governance.

Read about a game-changing approach to data governance and compliance based on Gartner model