Reference and Master Data Chapter 10 PDF

Reference and Master Data Chapter 10  Introduction In any company, certain data is required across business areas, processes, and systems. Stakeholders benefit if they can access the same customer lists, geographic codes, government tax codes, accounting cost centers, etc...

Reference and Master Data Chapter 10  Introduction In any company, certain data is required across business areas, processes, and systems. Stakeholders benefit if they can access the same customer lists, geographic codes, government tax codes, accounting cost centers, etc. Systems and data evolve quicker than data management professionals would like. Permissible values: specific allowable values that a particular data can take Reference data is data used to categorize other data. Used to define permissible values for other data, it dosen’t change much(static ❑ Specifies permissible values to be used by other data elements. ❑ Customer Status – active, inactive, : this is reference because it consists of predefined values that categorizes customers based on their relationship to the company ❑ Level of education – MS, BS, PhD: predefined categories that describe an individuals education, used across various systems ❑ Most widely shared class of data in a company Master data are those entities, relationships, and attributes that are critical for a company and foundational to key business processes and systems./represents the primary objects that are critical to business operations ❑ Provide context for business transactions and analysis ❑ Employees, customers, products, financial structures, etc... )..  Business Drivers The business drivers for establishing a master data management program include ❑ Meeting organizational data requirements ❑ Managing data quality ❑ Managing the costs of data integration ❑ Reducing risk The business drivers for establishing a reference data management program include ❑ Meet data requirements for multiple initiatives and reduce risks and costs of data integration through consistent use of reference data ❑ Manage the quality of reference data : : Goals and Principles The goals of a reference and master data management program include: Ensuring the company has complete, consistent, current, authoritative master and reference data across company processes Enabling master and reference data to be shared across company functions and processes Lowering the cost and reducing the complexity of data usage The principle of a reference and master data management program include: Shared data: data like customer info and product detail are not isolated in one department instead their share Ownership : responsibility for managing and maintain these two datas within a syste Quality: accurac Stewardship :roles and responsisblites assigned to the individuals who ensure integrity and quality of these two data Controlled change: how changes are handled Authority: decision making power related to the data. y d s m MDM vs RDM MDM entail controls over master data values and identifiers that enable consistent use, across systems, of the most accurate and timely data about essential business entities. The goals of MDM include ensuring availability of accurate, current values while reducing risks associated with ambiguous identifiers. RDM entails control over defined domain values and their definitions. The goal of RDM is to ensure the company has access to a complete set of accurate and current values for each concept represented. MDM is the practice of managing and governing the organization’s key business entities (master data), which include critical information about customers, products, employees, suppliers, assets, and more MDM focuses on managing core business entities that are central to business operations. The goal is to ensure consistency, accuracy, and reliability of this core data across multiple systems and departments RDM focuses on managing reference data, which consists of prede ned, standardized values used to categorize and classify other data. Reference data is used to provide context for master and transactional data. RDM ensures the consistency and accuracy of categorical values that are used to classify data across the organization, such as country codes, currency codes, industry classi cations, product categories, etc fi.. fi. MD Gartner definition ❑ “a technology enabled discipline in which business and IT work together to ensure the uniformity, accuracy, consistency, and accountability of the company’s official shared master data assets.” A discipline made up of people, processes, and technology. M :  Matchin The process of identifying which different records may relate to a single entit The risks with this process are: False positives – two references that do no represent the same entity are linked with a single identifier, resulting in one identifier that refers to multiple entities. False negatives – two references represent the same entity but are not linked with a single identifier, resulting in multiple identifiers for the same entity. Data matching is the process of identifying similar or identical records across datasets. It is often used to combine or consolidate records that refer to the same entity but may be represented differently in various datasets Purpose: Data matching is essential for eliminating duplicate records, improving data quality, merging datasets, and ensuring consistency across systems. A false positive occurs when the system incorrectly matches two records, identifying them as the same entity when they are actually different. A false negative occurs when the system fails to match two records that actually represent the same entity, treating them as different when they should be considered a match. g. y  Party Master Data Includes data about individuals, organizations, and the roles they play in business relationships. Agent Beneficiary Customer Employee A single individual can occupy one or many roles  Party Master Data Create 360° Visibility by Linking all Roles to a Central Perso Owner Agent Employee Insured Person Beneficiary Customer Other n  Reference Data Structure Lists ❑ Simplest form of reference data Cross reference lists ❑ Translate between code value ❑ s  Reference Data Structure Taxonomies ❑ Hierarchical reference data information  Internal Reference Data Many companies create their own reference data for internal processes RDM must manage and standardize reference data sets across the company Client Applicatio ❑ Accepted or Received ❑ Paid or Funded ❑ Closed or Completed? refers to standardized, prede ned values used within an organization to categorize and manage various internal operations, processes, or statuses. These values are often speci c to the organization and are not necessarily tied to external standards (such as ISO country codes or industry classi cations). Instead, they re ect internal business rules, work ows, or applications. fi ? n fi fi fl ? fl..  Industry Reference Data Data sets created and maintained by industry or government bodies rather than individual companies to provide a common standard for codifying important concepts. https://www.icd10data.com/ICD10CM/Codes Computational reference data(used in analytics and modeling) - foreign exchange rates industry reference data refers to standardized sets of values and classi cations speci c to an industry. This data helps organizations categorize, validate, and manage their information in a way that aligns with industry norms and standards. Examples of industry reference data include codes for industries, sectors, products, services, and other classi cations that are commonly used across the industry. in this context, foreign exchange rates are considered computational reference data because they are standardized values that are used in calculations or models to perform speci c nancial operations. These values help organizations convert amounts between currencies for reporting, accounting, and decision-making purposes fi fi. fi fi fi Reference and Master Data Governance Both require stewardship and governance Not all issues can be solved through automation. Without governance, reference and master data will not deliver their true potential The Data Governance Council should ensure policies and procedures are implemented to handle changes. Governance processes will determine: ❑ Data sources to be integrate ❑ Data quality rules to be enforced ❑ The priority and response levels of data stewards ❑ How data is to be presented to meet stakeholder needs d..  System of Record vs System of Reference System of Record is an authoritative system where data is created/captured through a defined set of rules and expectations. System of Reference is a system where data consumers can obtain reliable data even if it did not originate there. (i.e., data warehouse), data is trustworthy and usable regardless of its sourc Data warehouse is like a big storage space for data where information from different places is collected and kept in one place. e Data Sharing Agreements Agreements stipulate what data can be shared and under what conditions. Those responsible for the date sharing environment must ensure high quality data is provided to consumers. Processes should be put in place to address the root causes of issues with quality or availability. Metrics Certain metrics can be tied to reference and master data and their processes ❑ Data quality and compliance ❑ Data change activit ❑ Data ingestion and consumptio ❑ Service Level Agreements ❑ Data steward coverag ❑ Total cost of ownership ❑ Data sharing volume and usage y e n : Closing Thought Babysitting is a way for teenagers to feel like adults while adults go out to feel like teenagers.