Data Management at Scale

Chapter 9. Mastering Enterprise Data Assets

In previous chapters, you learned about the scale at which enterprises need to manage and distribute data. Enterprises typically have a large multitude of domains, each with its own systems and data. This means increased complexity because the data is spread around and multiple versions of the same data might exist. Integration, for example providing a 360-degree view of your customers, consequently takes more effort because it requires you to integrate and harmonize all the different independent parts of the same data from the different domains. Another challenge is that data may be inconsistent in contexts between the different domains, and there might be variances in the levels of data quality.

To address these challenges, we need the discipline of master data management (MDM). MDM, as described in Chapter 1, is about managing and distributing critical data to ensure consistency, quality, and reliability. This is important, because inconsistent and incorrect data can result in damaged credibility and decreased revenues and profits. Other trends driving the demand for master data management are security, fraud detection, and regulations, such as the EU’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Inefficiencies in managing master data can result in failures to detect fraud or penalties from regulators.

Note

MDM introduces more coupling into your architecture. It creates more enterprise ...