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, assists in the compliance of regulators and makes informed decisions and ultimately creates an advantage to 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 that needs to be consolidated, and delivered to business analytics (BI) systems as well as enterprise resource management (ERP) platforms, and the Internet of Things (IoT), sensors, and machine learning, as well as generative artificial Intelligence (AI) tools for advanced insights.
Without a well-defined and standardized data management strategy, companies could end up with uncompatible data silos and inconsistency of data sets that hinder the ability to run business intelligence and analytics applications. Inadequate data management can cause distrust between customers and employees.
To meet these challenges companies need to develop a data-management plan (DMP) which includes the people and processes needed to manage all types of data. For example, a DMP can help researchers identify the naming conventions that they should use to structure data sets to ensure long-term storage as well as easy access. It could also include data workflows which define the steps to follow for cleansing, validating, and integrating raw data sets and refined data sets to make them suitable for analysis.
For businesses that collect consumer information A DMP can assist in ensuring compliance with privacy laws around the world such as the European Union’s General Data Protection Regulation or state-level regulations like California’s Consumer Privacy Act. It can also guide the formulation of policies and procedures to address security threats to data and audits.