Oferta

The Importance of Data Management

Data management is a method that involves creating master data management and enforcing processes, policies and procedures to handle data throughout its entire life cycle. 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 leads to a plethora of data that must be consolidated and then delivered to business analytics (BI) systems and enterprise resource management (ERP) platforms, and the Internet of Things (IoT) sensors,, machine learning and generative artificial intelligence (AI) tools, to gain advanced insights.

Without a clear data management plan, businesses may end up with data silos that are not compatible and inconsistent data sets, which hinder the ability to run business intelligence and analytics applications. Inadequate data management can cause distrust between customers and employees.

To overcome these challenges it is crucial that companies come up with a data management plan (DMP) that includes the people and processes needed to manage all types of data. For example, a DMP can help researchers determine the file name conventions they should apply to organize data sets for long-term storage and for easy access. It can also contain an information workflow that outlines the steps to cleanse, verifying and integrating raw and refined data sets in order to ensure they are suitable for analysis.

For organizations that collect consumer information for their customers, 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 like California’s Consumer Privacy Act. It can be used to guide the development and implementation of policies and procedures to address security threats to data.