Data management is the process of establishing and enforcing rules, processes and procedures to manage data throughout its entire lifecycle. It ensures that data is reliable and accessible, facilitates compliance with regulations, and facilitates informed decisions.
The importance of effective data management has grown significantly as organizations automate their business processes, leverage software-as-a-service (SaaS) applications and deploy data warehouses, among other initiatives. This results in a growing amount of data which must be consolidated, and delivered to business analytics (BI) systems such as enterprise resource management (ERP) platforms as well as the Internet of Things (IoT), sensors, and machine learning, as well as generative artificial intelligence (AI) tools for advanced insights.
Without a well-defined data management strategy, companies can end up with incompatible data silos and data sets that are inconsistent which hinder the ability to run business intelligence and analytics applications. Inadequate data management can affect the confidence of employees and customers.
To address these challenges, it’s essential that companies create a data management strategy (DMP) that includes the people and processes needed to manage all types of data. A DMP can, for instance can assist researchers in determining the appropriate file https://taeglichedata.de/verwalten-von-datenprozessen-mit-data-center-management-anwendungen/ name conventions they should utilize to arrange data sets to store them over the long term and make them simple to access. It can also include an data workflow that specifies the steps involved in cleansing, verifying and integrating raw and refined data sets to allow them to be suitable for analysis.
A DMP can be used by organizations that collect consumer data to ensure compliance with privacy laws on a global and state level, like the General Data Protection Regulation of the European Union or California’s Consumer Privacy Act. It can be used to guide the creation and implementation of procedures and policies to address security threats to data.