The Importance of Data Management
Data management is the process of establishing and enforcing policies, procedures and procedures for handling data throughout its lifecycle. It ensures that data is useful and accessible, which facilitates compliance with regulations 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. The result is a flood of data that needs to be consolidated and delivered to business intelligence (BI) and analytics systems as well 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 well-defined data management strategy, companies could end up with uncompatible data silos and inconsistency of data sets which make it difficult to run analytics and business intelligence applications. Data management issues can cause distrust between customers and employees.
To tackle these issues it is crucial that companies develop a data management plan (DMP) that includes the people and processes required to manage all types of data. A DMP, for example will help researchers identify the conventions for naming files that they should utilize to arrange data sets to preserve them over time and make them easy to access. It can also contain an information workflow that outlines the steps involved in cleansing, verifying and integrating raw and refined data sets to make them suitable for analysis.
For businesses that collect consumer information for their customers, a DMP can assist in ensuring compliance with global privacy laws like the European Union’s General Data Protection Regulation or state-level laws like California’s Consumer Privacy Act. It can be used to guide the development and implementation of policies and procedures that address security concerns for data.
