Data management is a method that involves creating and enforcing policies, procedures and processes to handle data throughout its entire lifecycle. It ensures data is accessible and useful, which facilitates the compliance of regulators and makes informed decisions and ultimately creates a competitive advantage for businesses.
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 creates a flood of data that needs to be consolidated, and delivered to business analytics (BI) systems and enterprise resource management (ERP) platforms, Internet of Things (IoT) sensors,, machine learning, as well as generative artificial intelligence (AI) tools, to gain advanced insights.
Without a clearly defined data management strategy, companies could end up with uncompatible data silos and data sets that are inconsistent that hamper the ability to run business intelligence and analytics applications. Poor data management can also reduce trust between employees and customers.
To address these issues, companies must develop a plan for managing data (DMP), which includes the people and processes required to manage all types of data. For instance, a DMP will help researchers determine the naming conventions that they should apply to organize data sets to ensure long-term storage and access. It may https://taeglichedata.de/information-lifecycle-management-establishing-data-processes/ also include data workflows which define the steps to take for cleansing, validating and integrating raw data sets and refined data sets in order to ensure that they are suitable for analysis.
A DMP can be used by organizations that collect consumer data to ensure compliance with privacy laws at the state and global level, such as the General Data Protection Regulation of the European Union or California’s Consumer Privacy Act. It can also aid in the creation of policies and procedures for dealing with data security risks and audits.