Data Resource Management
Data Resource Management (DRM) is vital in organizations as it ensures that data are treated as a valuable resource.
Data Resource Management Methodologies
DRM methodologies are designed to provide the right data to the right people at the right time. Data governance is foundational to an organization because it ensures data's availability, usability, integrity, and security. Data Quality Management ensures the data are accurate, consistent, and relevant for its intended use. Data Security protects this valuable asset by implementing measures like proper access controls and encryption. Data Integration aligns data from multiple sources, making it cohesive and usable throughout the organization. Data Accessibility focuses on making data easily available and user-friendly for those who need it. Data Lifecycle Management oversees the entire data process within the organization. It manages everything from its creation and storage to its eventual archiving or deletion while adhering to organizational policies and regulatory requirements. Data assessment and planning are two aspects provide a foundation for recognizing what data are needed. Data processing and transformation converts raw data into a structured, usable format. Data storage and organization phase is when data is stored and organized securely. Data analysis is when you are employing various tools to extract valuable insights from the stored data. Data security and compliance measures are implemented to ensure data integrity and legal compliance Data monitoring and maintenance is when ongoing quality and reliability are maintained. Data disposal and archival used to manage the secure deletion or long-term storage of data.
Building Employability Skills and Competence
The skills in this section are:
Database Administration
Database Maintenance: Maintain databases and database management systems. Data Processing
Data Integration Methods: Explain data integration methods to process data. Critical Evaluation: Demonstrate an understanding of the importance of using data to inform business decisions and recommendations. Data-Driven Decision-Making
Data-Driven Business Decisions: Develop data-driven solutions to problems. Big Data
Data Quality: Ensure structure, accuracy, and quality of data. Data Literacy
Use Data Visualization Tools: Use data visualization tools to effectively communicate data. Data Analysis
Use Data Analysis: Use data analysis to inform decision-making.
Database Management System (DBMS)
A database management system (DBMS) is specialized software designed to interact with the user, applications, and the database itself to capture and analyze data.
A general-purpose DBMS is designed to allow the definition, creation, querying, update, and administration of databases. Database management systems (DBMS) serve as organized repositories for the systematic storage, retrieval, and governance of data. DBMS systems fulfill a range of roles, from ensuring data integrity, security, and accessibility to facilitating data sharing, backup, and analytics. Critical to achieving organizational objectives and long-term success. An entity-relationship diagram is a schematic of the entire database that describes the relationships in a database. Data definition diagram enables a user to be able to specify the structure of the content of the database. A data dictionary is an automated or manual file that stores information about data elements and data characteristics such as usage, physical representation, ownership, authorization, and security. The ability to minimize isolated files with repeated data enables a DBMS to reduce data redundancy and inconsistency.
Lesson 3: Data Resource Management
