The lifecycle concept is widely used when it comes to the creation, use, dissemination and preservation of data. Various authors and institutions have created different representations to understand the lifecycle of data, identifying their respective stages.
What is data management in business environments?
Data management refers to the professional practice of building and maintaining a framework for ingesting (see here), storing, extracting, and archiving essential data for the modern business. Data management is the backbone connecting all segments of the information lifecycle.
Data management works symbiotically with process management, ensuring that the actions that teams take are informed by the cleanest and most up-to-date data available, which requires the monitoring of changes and trends in real time. Here is a more comprehensive view of this practice, its benefits and pitfalls, as well as the best practices that will help your organization get the most out of its business intelligence.
7 data management modalities
Data management experts often focus on various specialties within this domain. These specialties usually correspond to one or more of the following fields:
The specific requirements of any organization that performs data management might require a mixture of some or even all of these approaches. Being familiar with the various areas of management provides data managers with the training necessary to create customized solutions for their environments.