The Importance of Data Management

Data management is a procedure that involves establishing and enforcing processes, policies and procedures to handle data throughout its entire life cycle. It ensures that data is useful and accessible, assists in regulatory compliance, and permits informed decision-making.

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 then sent to business analytics (BI) systems, enterprise resource management (ERP) platforms, Internet of Things (IoT) sensors,, machine learning, as well as generative artificial Intelligence (AI) tools for advanced insights.

Without a clearly defined strategy for managing data, businesses can end up with data silos that are incompatible and inconsistent, which hinder the ability to operate business intelligence and analytics applications. A poor data management strategy can reduce trust between employees and customers.

To tackle these issues businesses must devise a plan for managing data (DMP), which includes the processes and people needed to manage all types of data. For instance, a DMP can help researchers identify the naming conventions for files they should use to structure data sets to ensure long-term storage and access. It can also include a data workflow that defines the steps involved in cleansing, validating and integrating raw and refined data sets to make them suitable for analysis.

For businesses that collect consumer data, 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 such as California’s Consumer Privacy Act. It also can guide the formulation of policies and procedures to address security threats to data and audits.

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