Enterprise-Level Data Governance and Compliance

As organizations continue to generate and consume vast amounts of data, it has become increasingly important to manage this data in a strategic and structured manner. This is where data governance comes in, providing a framework for managing data as a valuable organizational asset. With data governance practices in place, we can ensure that an organization’s data is accurate, secure, and accessible, while also complying with relevant regional or industry-specific regulations. Without proper data governance practices, we run the risk of struggling with disparate data sources and inaccurate data and having difficulties in ensuring data privacy and security. As such, data governance and compliance have become essential components of any organization’s data strategy.

In this chapter, you will learn about the importance of data governance, the roles involved in its implementation, and tools such as Microsoft Purview that can...

The importance of data governance and compliance

Businesses are becoming more and more data-driven as time goes on. They have good reason to do so, as revenue, time-to-market, profits, and customer satisfaction increase greatly for data-driven businesses. Given this trend, the need for data governance is higher than ever.

The goals of data governance can be summarized as follows:

• Managing an ever-growing data landscape
• Overcoming data silos
• Increasing data agility
• Complying with data regulations

More data-driven organizations mean a faster growth of the global data volume, but also a larger data landscape per organization. The latter will cause serious issues in the long run when managed incorrectly. With a strong data governance strategy alongside the right tools and services, a data landscape will remain clear and structured at scale. The data landscape tends to grow exponentially with the business. When the business grows, new subsidiaries or acquisitions...

Governing data with Microsoft Purview

Microsoft Purview is a unified data governance service that allows organizations to manage and govern data that resides anywhere, from on-premises data stores to multi-cloud and even SaaS data.

Purview enables data discovery by providing data scanning and classification for assets across the entire data landscape. Metadata and descriptions of discovered data assets are integrated into a holistic map of the data estate, as shown in the following figure:

Figure 10.3 – Purview is built upon core components: Data Insights, Data Catalog, and Data Map. The Purview data map holds important metadata from multi-cloud, SaaS, and on-premises sources. Data officers can also set data access policies, which are straightforward.

The service consists of three core components:

• Data Map
• Data Catalog
• Data Estate Insights

Let’s take a look at each of them.

Data Map

Purview Data Map provides...

Applying enterprise-level data governance

Not every cloud data architect will have to be as well-versed in the following part, as the implementation of data governance is something that happens organization-wide, rather than on the level of a single data solution. It would mainly involve a chief architect, CDO, or CIO.

Data governance forms an essential component for any data estate at scale, yet we cannot implement data governance blindly. As we will see later, data governance can be implemented too late or too early.

Neglecting the need for governance over a longer period of time, until the data platform reaches full-scale maturity, will cause many issues in the long run. The longer governance, compliance, and data management are neglected, the more technical debt is built up. The data landscape will turn into an unmanageable swamp, making it hard or near impossible to clean up and organize. Therefore, the key takeaway here is to think about data governance from the start.

...

Summary

Data governance and compliance are critical components of any data strategy. In this chapter, we explored the importance of data governance, its goals, and the roles involved in its implementation, along with Microsoft Purview and data governance frameworks.

We highlighted four main goals of data governance, namely managing an ever-growing data landscape, overcoming data silos, increasing data agility, and complying with data regulations.

The chapter also discussed the different roles involved in data governance. Executives, governance boards, data stewards, data owners, and SMEs all have a part to play in ensuring that data is managed effectively and efficiently.

We explored Microsoft Purview as a core component for the implementation of data governance and compliance, which provides a Data Map, Data Catalog, and Data Estate Insights. This tool can help organizations understand their data landscape (even in its most decentralized form) and make better decisions about...