Data Management
Data management is the process of ingesting, storing, organizing and maintaining the data created and collected by an organization. Effective data management is a crucial piece of deploying the IT systems that run business applications and provide analytical information to help drive operational decision-making and strategic planning by corporate executives, business managers and other end users.
The data management process includes a combination of different functions that collectively aim to make sure that the data in corporate systems is accurate, available and accessible. Most of the required work is done by IT and data management teams, but business users typically also participate in some parts of the process to ensure that the data meets their needs and to get them on board with policies governing its use.
This comprehensive guide to data management further explains what it is and provides insight on the individual disciplines it includes, best practices for managing data, challenges that organizations face and the business benefits of a successful data management strategy. It also gives an overview of data management tools and techniques. Click the links on the page to learn more about data management trends and get expert advice on enterprise data management.
Importance of data management
Data is increasingly seen as a corporate asset that can be used to make more informed business decisions, improve marketing campaigns, streamline business operations, and reduce costs. All of these are aimed at increasing sales and profits. However, lack of proper data management can lead to incompatible data silos, inconsistent datasets, and data quality issues that limit the ability of organizations to run business intelligence (BI) and analytics applications. What remains, and worse, can lead to false results. As organizations face increasing regulatory compliance requirements, including privacy laws such as the GDPR and the California Consumer Privacy Act,
data management is becoming more important. In addition, organizations are collecting ever-growing data and a wide variety of data types, both of which are characteristic of big data systems adopted by many. Without proper data management, such an environment can be cumbersome and difficult to navigate.
Types of data management functions
The individual disciplines that are part of the overall data management process cover steps ranging from processing and storing data to controlling the format and use of data in operational and analytical systems. Developing a data architecture is often the first step, especially for large organizations that have a lot of data to manage. The architecture provides a blueprint for deployed databases and other data platforms, including specific technologies for individual applications. The
database is the most commonly used platform for storing enterprise data. These include collections of data organized in ways that can be accessed, updated, and managed. They are used in both transaction processing systems that create operational data such as customer records and sales orders, and data warehouses that store integrated records from business systems for BI and analytics.
Database management is a core data management function. After you set up your database, you need to perform performance monitoring and tuning to maintain an acceptable response time to database queries that users run to retrieve information from the data stored in the database. Other administrative tasks include designing, configuring, installing, and updating the database. Data security; database backup and recovery. Software upgrades and security patches.