Master data management (MDM) comprises the processes, governance, policies, standards and tools that consistently define and manage the critical data of an organization to provide a single point of reference. Source: https://en.wikipedia.org/wiki/Master_data_management
As the attitude of the senior management cascades throughout the organisation, it is crucial that sufficient resources are allocated to ensuring the MDM are robust and reviewed regularly.
Data governance (DG) refers to the overall management of the availability, usability, integrity, and security of the data employed in an enterprise. A sound data governance program includes a governing body or council, a defined set of procedures, and a plan to execute those procedures. Source: searchdatamanagement.techtarget.com › … › Data and data management
It is crucial for the success of the business to ensure the quality and integrity of the data being used to provide the analysis is protected. Without having comfort that the raw data is accurate, the analysis becomes void, and if used by the management to make a decision, it could lead to disastrous consequences for the organisation.
Data quality refers to the level of quality of data. There are many definitions of data quality but data are generally considered high quality if, “they are fit for their intended uses in operations, decision making and planning.” Source: https://en.wikipedia.org/wiki/Data_quality
A basic understanding and appreciation of the above is essential when working in the realm of data analysis.