What is data lifecycle and what is data lifecycle management (DLM)? And what are the main goals of data lifecycle management in an enterprise and what are some of the data lifecycle management framework?
The term “data lifecycle” describes the various phases that go through when data is created, deleted, or archived. This covers the procedures and actions necessary to collect, store, analyze, share, and discard data.
The process of managing data over the course of its lifecycle is known as data lifecycle management (DLM). In order to guarantee that data is adequately managed and safeguarded throughout its lifecycle, policies, procedures, and controls must be established. Throughout its existence, data must be usable, accurate, trustworthy, and secure.
The primary objectives of DLM in an organization include:
- Preventing data loss or damage: DLM aids businesses in making sure their data is backed up and that they have a disaster recovery plan in place to restore data in the event of loss or damage.
- Adherence to regulations: By ensuring that data is stored and handled in accordance with these regulations, DLM aids organizations in adhering to rules like GDPR, HIPAA, and CCPA.
- Improving data quality: By ensuring that data is accurate, consistent, and current, DLM aids organizations in raising the standard of their data.
- 4.Lowering data management expenses: By locating unneeded data and deleting it from systems, DLM assists organizations in lowering their data management costs.
And the following are a few data lifecycle management frameworks:
- Information Governance: This framework emphasizes the management of data as a strategic asset and consists of rules, practices, and controls to guarantee that data is efficiently managed and safeguarded throughout its lifecycle.
- Data Management Body of Knowledge (DMBOK): This framework offers a thorough explanation of best practises for data management and addresses all facets of data management, including data architecture, data governance, data quality, and data security.
- Integration of the capability maturity model (CMMI): This framework offers a maturity model for organisations to evaluate current data management skills and pinpoint areas for development.
- ISO 27001: This framework offers a collection of global standards for information security management and contains recommendations for managing data security over the course of a piece of information’s lifecycle.