Project : Data Governance and Policy All sources should be cited both in-text an

Project : Data Governance and Policy
All sources should be cited both in-text and in References using APA 7 format
At least 20 pages (Number of Pages Exclude references and cover page)
Case Study:
RealBeat LLC is a chemical manufacturing company that has existed for more than 50 years with over 150 employees. It has a strong Research and development (R & D) with many patents in its name. Other departments include Operations, Manufacturing, Shipping and Receiving, Accounting, Supply Chain, Sales, Marketing, Customer Service, and Legal. Its performance has been impressive, and it is even expected to grow rapidly in the next few years. The faster growth and without clear rules have resulted in inconsistencies and holes in its data and has affected the data integrity of its enterprise resource planning (ERP) and a Product lifecycle management (PLM) system. As a result, their data is not reliable and cannot be used for any meaningful planning. As it stands now, no amount of “AI technology” can help with that. As it is said, “garbage in, garbage out.”
Management realizing this has begun a data cleaning process but to ensure that all data stays clean and consistent as time goes on, it’s necessary to establish rules governing the creation and maintenance of data.
RealBeat LLC needs a data governance system to manage the business; its master data and transactional data with the expected growth.
Project:
Create a data governance document that will encourage discipline behavior across the entire organization, execute the compliance and governance practice, ensure policies, standards, and guidelines are maintained, and establish and monitor KPIs to track master data management.
The paper should at least contain the following sections:
•    Purpose:
•    Governance: Directives to manage policies, principles, and organizational bodies.
•    Policy: The requirements and standards that the Master Data Management (MDM) must follow.
•    Accountability and Responsibility:
•    Enforcement rules (compliance; ensure data is handled in ways that meet organizational goals.
•    Organization: Getting the right people, such as data stewards, in the right places.
•    Measurement: How is your company performing in relation to outlined goals?
•    Process: Lays out processes across the data lifecycle.