The Importance of Data Management

Data management is the process of establishing and enforcing policies, processes and procedures for handling data throughout its lifecycle. It ensures that data is useful and accessible, facilitates regulatory compliance, 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 that needs to be consolidated, and then sent to business analytics (BI) systems as well as enterprise resource management (ERP) platforms and Internet of Things (IoT) sensors,, machine learning and generative artificial intelligence (AI) tools for advanced insights.

Without a well-defined data management strategy, businesses could end up with incompatible data silos and unbalanced data sets that hinder the ability to run business intelligence and analytics applications. A poor data management strategy can undermine employee and customer confidence.

To address these issues, companies must develop a data-management strategy (DMP) which includes the people and processes required to manage all types data. A DMP can, for instance can help researchers decide the naming conventions for files that they should use to arrange data sets to preserve them over time and make them easy to access. It can also contain data workflows that define the steps to be taken for cleansing, validating, and integrating raw data sets and refined data sets to make them suitable for analyses.

For companies that collect consumer data, a DMP can help ensure compliance with global privacy laws such as the European Union's General Data Protection Regulation or state-level regulations like California's Consumer Privacy Act. It can also help guide the development of procedures and policies for addressing data security threats and audits.

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