In order to maximize the value extracted for the company and its users the process of data governance includes compliance with legal obligations the implementation of internal processes and structures that enable them to be managed and used efficiently and thus ensuring that companies meet their legal obligations. DATA ARCHITECTURE Describes the structure of the business’ on-premise and local data assets and data management resources. Models rules policies and standards related to the collection storage integration and use of data are incorporated into this architecture.
DATA MODELING Data modeling techniques and methodologies are used to create simple diagrams of the systems and the data contained in those systems. It consists in creating a standard and consistent model of data in order to manage it effectively as a resource. METADATA Refers to information that describes different aspects of a dataset Whatsapp Mobile Number List and provides context. Metadata is data that provides information about other data. Most common information like size of the file its creation date and the author's name are included in metadata. Managing metadata involves setting up rules and processes to access share link integrate maintain and analyze metadata to help companies make good decisions based on reliable data.
DATA STORAGE A collection of methods and technologies for storing data. The company must determine where it needs to store its data Data warehouse - for clean and processed data Data lake - for raw data and bulk data Both - if the company manages both raw and processed data DATA SECURITY Various points such as encryption prevention of unauthorized access protection from moving corruption of data or accidental deletion of data must be implemented to ensure data security.