MDM is an approach to reducing data redundancy by maintaining a definitive "record of truth," or master data, for critical data in order to supply a single source as a reference. Ideally, MDM organizes data sharing among multiple applications or departments.
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In the example above, if the Credit Card Processing system receives updated customer address, which of the other systems also need to have that data? The Accounting and Distribution systems. If only the street address changed, but the city, state, and zip code information remain the same, then only the street address data element of the customer's data s data record needs to be updated in the other two systems.
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Note: An adaptor is software located within a system that connects to, and shares data through, the YOUnite Data Hub.
The adaptor functionality focuses on:
- Extract, Transform, and Load (ETL) functions at the system level, ensuring any
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- system's "outbound data"
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- is extracted and transformed to meet defined format requirements before it gets
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- loaded onto the message bus → sent through the YOUnite Data Hub → sent back out to the message bus again so that → the receiving system's router then transforms the data into an "inbound data" format that
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- system requires.
- Create, read, update, and delete (CRUD) functions at the system level,
- The YOUnite Data Hub sits between the various systems, routing data between them based on which systems have access to which data (data governance).
- Are changes handled in real time or in batch?
The easiest and most common change handling is via batch updates. However, latency between batch updates may cause business process issues.
- How is DI Data Integration handled?
Transferring data between systems can be a daunting task. Some applications have built-in adaptors to handle transformations, but these generally handle only a subset of the required data. Where the built-in adaptors fall short or don't exist, an organization may spend resources developing "one-off" adaptors to meet an ongoing transformation need.
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The data for a data domain defined in YOUnite can:
- Be stored in the MDM Data Store or(also referred to as a Centralized implementation), OR,
- Remain in the organization's systems and, through adaptors, share data with other systems via the YOUnite Data Hub. This is called federated MDM. With federated MDM, YOUnite's data store does not store the data. YOUnite's federated MDM implements what analysts often referr to as both Registry and Coexistence MDM.
Using the delivery service example above:
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Data Records vs Master Data
Data records are the latest, most recent version of a record stored in many systems connected to YOUnite. Master data is data is data in a particular domain or a particular element that has been declared the "Record of Truth."" by the Data Governance Steward or Zone Data Steward. It's not always necessary or appropriate for systems to access an organization's master data. Many data access requests are for data records that may or may not contain master data. However, YOUnite has the ability to propagate changes from a system that contains data records to others in the YOUnite ecosystem on a permission-appropriate basis (i.e. governance).
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Several terms have been introduced and it may be helpful to review them before moving on:
- Access Control Lists (ACLs) Data controls that control inbound/outbound messages for any given system, application, or role.
- Adaptor Software located within a system that shares data through the YOUnite Data Hub and acts as the connection point between a system and the YOUniteData Hub. It focuses on ETL (Extract, Transform, and Load) functions, ensuring the outbound data from a system meets the YOUnite Data Hub format requirements, transforming inbound data from the hub into what other systems require.
- Data Domain (Domain) A domain refers to a data entity model such as student, course, or customer, etc. and is defined by the parties responsible for data governance. It is a set of fields or properties that define a set of data (i.e. a domain may be a "Student" that includes data definitions (properties) such as student name, address, etc.).
- Data Governance Governance Managing data access (i.e. who accesses certain data sets based on role, application, etc. defining where the Master Data is stored).
- Data Integration (DI) The process of keeping data up to date between disparate systems.
- Data Record The latest (most recent) version of a given record. More technically, JSON objects in motion that follow the data domain model schema of the MDM ecosystem.
- Federated MDM An MDM model in which the data handled through MDM is not stored centrally in MDM-handled data is retrieved by the Data Hub but instead via a reference to the data is stored that points to the the data's source system where (i.e. the data hub can retrieve the data. is not stored centrally in the Data Hub).
- Master Data (MD) The master or golden version of a record (for a customer, for example). The "record of truth" as declared by a Data Governance Steward (DGS) or Zone Data Steward (ZDS).
- Master Data Management (MDM) An approach to reducing data redundancy across systems by maintaining a master file for critical data. MDM is the process of describing and cataloging data inside of an organization and understanding which stakeholders value which sources of data. It is an approach to reducing data redundancy across systems by maintaining a master file for critical data.
- YOUnite Data Store/MDM Data Store Store A centralized store natively connected to the YOUnite Data Hub that holds data records. The domains configured for this data store are locked in as the source of master data for that domain in the Tenant.
- YOUnite Data Hub The scaleable web application that handles the API and message broker requests through which adaptors and the YOUnite API consumers communicate.
Further Reading
An good Good source for more MDM background is include:
- Lyn Robison, A Comparison of Master Data Management Implementation, Gartner Research, 2017
- Mark Allen and Cervo Dalton's Multi-domain Master Data Management: Advanced MDM and Data Governance in Practice. Waltham, MA: Morgan Kaufmann, 2015. (ISBM 978-0-12-800835-5).
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