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The Importance of Data Management
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 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 leads to a plethora of data that needs to be consolidated and sent to business analytics (BI) systems, enterprise resource management (ERP) platforms and Internet of Things (IoT), sensors, and machine learning and generative artificial intelligence (AI) tools for advanced insights.
Without a clear strategy for managing data, businesses can end up with silos that are not compatible and inconsistent data sets which hinder the ability to run business intelligence and analytics applications. Unorganized data management can reduce the trust of customers and employees.
To address these issues businesses must devise a data-management strategy (DMP) that includes the people and processes required to manage all types of data. A DMP, for example will help researchers identify the appropriate file name conventions they should utilize to arrange data sets to keep them for a long time and make them easy to access. It can also contain data workflows which define the steps to follow for cleansing, validating and integrating raw data sets and refined data sets to allow them to be suitable for analysis.
For businesses that collect consumer information for their customers, a DMP can assist in ensuring compliance with privacy laws around the world like the European Union’s General Data Protection Regulation or state-level regulations such as California’s Consumer Privacy Act. It can also help guide the formulation of policies and procedures to address security threats to data and audits.
