Data – Roadmap
I start to realize the biggest problem in the Data.
1.There is no perfect framework (DMBOK vs DCAM is no sufficient)
https://datacrossroads.nl/2018/12/02/data-management-metamodels-damadmbok2-dcam/
2.Multiperspective of Data
3.Different understanding of data
School of DB, School of Architecture
https://stackoverflow.com/questions/3873346/logical-model-versus-domain-model
Master Data: “A consistent and uniform set of identifiers and attributes that describe the core entities of the enterprise and are used across multiple business processes.” Gartner Data & Analytics Summit
MDM: “that describe the core entities of the enterprise” – Master data exists and should be identified within multiple data domains:
• Party – This data domain can extend to an individual customer in B2C or a business (even hierarchy) in a B2B context. In other contexts, this domain can be extended to Patients, Providers, Citizens, Suspects or any other domain that has similar attributes like name, contact information, and, most importantly, survivorship rules when one or more records are resolved into a single record that represents the truth of that entity. It can also extend to suppliers, although that can arguably be considered a distinctly different data domain, and many MDM vendors will treat it as such.
• Product – A critical data domain for commerce, catalog, and compliance efforts, product master data differs from customer data primarily in that while the volume of records may be lower, the complexity is higher, hierarchies are much more important, and collaborative authorship is key.
• Asset – This domain can extend to both physical assets, such as replacement parts in a warehouse, physical buildings, such as hotels or warehouses, or beds within a hospital, for example, or digital assets, such as images, videos or reviews that relate to another data entity like a product or a location.
• Location – A more nebulous, but no less critical data domain, location master data will usually be a geographical location that corresponds to another data domain (like an address for a retail store or location of an off-shore drilling site) or some other location reference that can be tracked, such as delivery trucks or IP addresses.
Data Domain: Big level block that used to define master data
Data – Maturity Ladder
https://datacrossroads.nl/2018/12/02/data-management-metamodels-damadmbok2-dcam/
Data warehouse sources are often operational or transactional systems. In these types of systems, the master data comes along for the ride when an event or transaction occurs, such as a change in product inventory levels or a customer making a purchase. MDM often incorporates all possible master data sources, including not only data associated with or generated by internal systems, but also external data.
Another major difference between MDM and data warehousing is that MDM focuses on providing the enterprise with a single, unified and consistent view of these key business entities by creating and maintaining their best data representations. While a data warehouse often maintains a full history of the changes to these entities, its current view represents the last update. Plus, each data warehouse update is applied to the current view without a re-assessment of how previous updates might change the best representation.
Matching and consolidating related records doesn’t typically occur in data warehousing. MDM, on the other hand, standardizes, matches and consolidates common data elements across all possible data sources for a subject area to iteratively refresh and maintain its best master record.
https://blogs.sas.com/content/datamanagement/2017/04/27/mdm-different-data-warehousing
Anjar Priandoyo 
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