This chapter provides an overview from DAMA-DMBOK2 on reference and master data (excerpted from pages 347-352), and then covers the additional reference and master data responsibilities needed for blockchain to work well within our organizations.

Overview from DAMA-DMBOK2

In any organization, certain data is required across business areas, processes, and systems. The organization (and its customers) benefit when this data is shared—when all business units can access the same customer lists, geographic location codes, business unit lists, delivery options, part lists, accounting cost center codes, governmental tax codes, and other relevant data. People using data generally assume a level of consistency exists across the organization… until they see disparate data.

In most organizations, systems and data evolve more organically than data management professionals would like. Particularly in large organizations, various projects and initiatives, mergers and acquisitions, and other business activities result in multiple systems executing essentially the same functions, isolated from each other. These conditions inevitably lead to inconsistencies in data structure and data values between systems. This variability increases costs and risks. Both can be reduced through the management of master data and reference data.

Master data management requires identifying and/or developing a trusted version of truth for each instance of conceptual entities (including product, place, account, person, or organization), and then maintaining the currency of that version. The primary challenge with master data is entity resolution (also called identity management), which is the process of discerning and managing associations between data from different systems and processes. The entity instances represented by master data rows will be represented differently across systems. Master data management works to resolve these differences, in order to consistently identify individual entity instances (specific customers, products, etc.) in different contexts. This process must also be managed over time, so that the identifiers for these master data entity instances remain consistent.

Reference data and master data share conceptually similar purposes. Both provide context critical to the creation and use of transactional data. (Reference data also provides context for master data.) They enable data to be meaningfully understood. Importantly, both are shared resources that should be managed at the enterprise level. Having multiple instances of the same reference data is inefficient, and inevitably leads to inconsistency between them. Inconsistency leads to ambiguity, and ambiguity introduces risk to an organization.

Reference data also has characteristics that distinguish it from other kinds of master data (e.g., enterprise or transactional structure data). It is less volatile. Reference datasets are generally less complex and smaller than transactional or master data sets. They have fewer columns and fewer rows. The challenges of entity resolution do not fall under the scope of reference data management.

Additional responsibilities due to blockchain

Those involved with MDM and RDM will find that their work will extend beyond organizational boundaries if blockchain applications are introduced. Many professionals in this discipline might find themselves working with standards organizations to define common master and reference data across their industries.

Creating consistent master and reference data

Master data management and reference data management will most likely cross enterprise boundaries when blockchain is introduced. Organizations will need to cooperate and invest resources to come up with consistent master data and reference data. RDM will have less of an issue than MDM, hopefully, because many of the RDM codes (such as diagnostic or ISO codes) should be industry standards.

Maintaining master and reference data

Even after the initial set of terms is standardized, there must exist a process to keep the data current. If one organization needs to change a reference data value, what process would allow this change to be made? It would need to involve all stakeholders, yet be made quickly so the organization can continue with their business.

Similarly, when standards change, there must be a process in place to update the standards within the application, and to notify all organizations of the change.

Those involved with RDM and MDM will need to work closely with data governance to define the maintenance of these codes in blockchain applications.

Retiring master and reference data

When master data and reference data values are no longer needed, what would be the process of removing them from the system? A simple delete can lead to issues with connected data; furthermore, deletes do not occur in the blockchain ledger because it is immutable. There would need to exist a process to “turn off” or deactivate values when they are no longer needed.

Similar to the maintenance activities, those involved with RDM and MDM will need to align with data governance to properly maintain these codes.