Data management is a process that involves the creation and enforcement of procedures, policies and procedures to handle data throughout its entire lifecycle. It makes sure that data is available and useful, which facilitates regulatory compliance and informed decision-making and ultimately provides 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. The result is a proliferation of data that needs to be consolidated and pushed to business intelligence (BI) and analytics systems such as enterprise resource planning (ERP) platforms, Internet of Things (IoT) sensors and machine learning and generative artificial intelligence (AI) tools to gain advanced insights.
Without a clear data management plan, businesses can end up with data silos that are incompatible and inconsistent, which hinder the ability to operate business intelligence and analytics applications. Poor data management can also cause distrust between customers and employees.
To meet these challenges, companies must develop a data-management strategy (DMP) that includes the people and processes required to handle all kinds of data. For example, a DMP will help researchers determine the file naming conventions they should apply to organize data sets to ensure long-term storage as well as easy access. It can also contain data workflows which define the steps that must be followed for cleansing, validating, and integrating raw data sets and refined data sets to make them suitable for analyses.
For organizations that collect consumer data For companies that collect consumer information, a DMP can help ensure 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 be used to guide the development and implementation of procedures and policies to address security threats to data.
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