Data Management

Data Management

Data Management

  • Data Management refers to the process of creating, storing, maintaining, and using data in a secure, efficient, and cost-effective manner.
  • Ultimately, successful data management ensures data integrity, availability, and confidentiality.

Types of Data in Data Management

  • Structured Data: This data has a predefined model or format, often stored in relational databases or spreadsheets.
  • Unstructured Data: This data does not have a specific format or structure and includes files such as images, videos, and emails.
  • Semi-structured Data: As the name suggests, this type of data falls in between structured and unstructured data. It can include elements of both, such as XML files.

Database Management Systems (DBMS)

  • A DBMS is software that provides an interface for users and other software to manage data within a database.
  • Benefits of using a DBMS include improved data sharing, data security, and decision-making capabilities.
  • Popular types of DBMS include Relational DBMS (RDBMS), Object-Oriented DBMS (OODBMS), and Hierarchical DBMS.

Data Life Cycle

  • Data Life Cycle represents the sequence of stages through which data goes from creation to deletion.
  • It typically includes collection, processing, storage, usage, sharing, archiving, and disposal of data.

Data Security

  • Data Security controls how data is protected from accidental or deliberate misuse, loss, or corruption.
  • Key ways to maintain data security include maintaining up-to-date backups, using encryption, and managing user access.
  • Threats to data security include malware attacks, hacking, and physical theft or damage.

Legal Considerations

  • Data Protection Act 2018 is the UK’s implementation of the General Data Protection Regulation (GDPR). It controls how personal information is used by organisations or the government.
  • Computer Misuse Act 1990 is aimed at preventing unauthorized access to computer systems and deliberately spreading malicious and damaging software.

Data Redundancy and Data Independence

  • Data Redundancy is the unnecessary duplication of data, which can lead to increased storage and confusion.
  • Data Independence is the ability to change the schema at one level of a database system without having to change the schema at the next level, improving flexibility and data security.

Data Backup and Recovery

  • Data Backup refers to creating a duplicate copy of the data to restore in case the primary data is lost or corrupted.
  • Data Recovery is the process of restoring lost or damaged data from backups. Various methods exist, for example, recovery software or use of professional recovery services.