What Is Data Management?
Data management is the practice of collecting, keeping, and using data securely, efficiently, and cost-effectively. The goal of data management is to help people, organizations, and connected things optimize the use of data within the bounds of policy and regulation so that they can make decisions and take actions that maximize the benefit to the organization. A robust data management strategy is becoming more important than ever as organizations increasingly rely on intangible assets to create value.
Data Capital Is Business Capital
In today’s digital economy, data is a kind of capital, an economic factor of production in digital goods and services. Just as an automaker can’t manufacture a new model if it lacks the necessary financial capital, it can’t make its cars autonomous if it lacks the data to feed the onboard algorithms. This new role for data has implications for competitive strategy as well as for the future of computing.
Given this central and mission-critical role of data, strong management practices and a robust management system are essential for every organization, regardless of size or type.
Managing digital data in an organization involves a broad range of tasks, policies, procedures, and practices. The work of data management has a wide scope, covering factors such as how to
- Create, access, and update data across a diverse data tier
- Store data across multiple clouds and on premises
- Provide high availability and disaster recovery
- Use data in a growing variety of apps, analytics, and algorithms
- Ensure data privacy and security
- Archive and destroy data in accordance with retention schedules and compliance requirements
A formal data management strategy addresses the activity of users and administrators, the capabilities of data management technologies, the demands of regulatory requirements, and the needs of the organization to obtain value from its data.
Data Management Systems Today
Today’s organizations need a data management solution that provides an efficient way to manage data across a diverse but unified data tier. Data management systems are built on data management platforms and can include databases, data lakes and warehouses, big data management systems, data analytics, and more.
All these components work together as a “data utility” to deliver the data management capabilities an organization needs for its apps, and the analytics and algorithms that use the data originated by those apps. Although current tools help database administrators (DBAs) automate many of the traditional management tasks, manual intervention is still often required because of the size and complexity of most database deployments. Whenever manual intervention is required, the chance for errors increases. Reducing the need for manual data management is a key objective of a new data management technology, the autonomous database.