Data management is a process that involves creating and enforcing policies, procedures and processes to manage data throughout its entire lifecycle. It ensures that data is easily accessible and useful, which facilitates regulatory compliance and informed decision-making, and ultimately provides 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 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, Internet of Things (IoT) sensors,, machine learning, and generative artificial intelligence (AI) tools for advanced insights.
Without a well-defined data management strategy, companies can end up with incompatible data silos and inconsistent data sets which hinder the ability to run analytics and business intelligence applications. A poor data management strategy can reduce trust between employees and customers.
To address these challenges It is essential that businesses make a plan for data management (DMP) that includes the necessary people and processes to manage all types of data. For instance the DMP can help researchers determine the naming conventions that they should apply to organize data sets for long-term storage and access. It can also contain an data workflow that specifies the steps involved in cleansing, checking and integrating raw as well as refined data sets to make them suitable for analysis.
For organizations that collect consumer data for their customers, a DMP can assist in ensuring compliance with privacy laws maintaining data processes the information lifecycle around the world such as the European Union’s General Data Protection Regulation or state-level regulations such as California’s Consumer Privacy Act. It can be used to guide the development and implementation of policies and procedures to address security threats to data.