Distributed data management, or DDM, is the efficient control and management of the ingestion, storage, organization, and maintenance of the data created and collected by an organization. Effective data management practice is critical in the implementation of Data Governance systems that run applications and provide analytical information to help drive strategic planning and decision making.
DDM is a function of the operating system that allows an application or user to use data stored in a database on remote systems. The system must be connected to a communication network, and remote systems must also use DDM.
With DDM, applications or users can perform the following tasks:
- Access data files that reside on remote systems as well as data on the local system.
- An application can handle data records in a file that exists on a target system.
- Manipulate data on a remote system.
When DDM is in use, applications and users can manipulate data, regardless of whether it exists locally or on a remote system. Local and remote file processing is handled in the same way.
The data management process includes a combination of different functions that ensure that stored data is accurate, available, and easily accessible. Most of the work is required to do engineering and data management teams. Still, users are also generally involved in some parts of the process to ensure that the data meets their needs and adheres to its use policies.
Within companies, data is increasingly viewed as a corporate asset that users can use to make more informed business decisions, such as improving the performance of marketing campaigns, optimizing business operations, and reducing costs. Lack of proper data management can lead organizations to create incompatible data silos, inconsistent data sets, and data quality issues that limit their ability to run business intelligence and analytics applications or make the wrong decisions.
Data management has also gained in importance as companies are subject to an increasing number of regulations, including data protection and privacy laws, such as the GDPR and the Consumer Privacy Act of California.
The various disciplines that are part of the overall data management process cover several steps, from data processing and storage to governance of how data is formatted and used in operational and analytical systems. The first step to effective distributed data management is the development of data architecture. Especially in large organizations with a lot of data to manage, a well-designed architecture provides a model for the databases and other data platforms on which specific technologies will be deployed to suit individual applications.