Description

Data management is a procedure that involves establishing and enforcing procedures, policies and processes to handle data throughout its entire lifecycle. It ensures that data is reliable and accessible, facilitates regulatory compliance, and enables 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 results in a plethora of data that needs to be consolidated and delivered 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 provide advanced insights.

Without a clearly defined data management strategy, businesses can end up with silos that are incompatible and inconsistent data sets that hinder the ability to manage business intelligence and analytics applications. Unorganized data management can undermine employee and customer confidence.

To meet these challenges, companies must develop a plan for managing data (DMP) which includes the people and processes needed to manage all types of data. A DMP can, for instance can assist researchers in determining the appropriate file name conventions they should follow to organize data sets in order to store them long-term and make them easy to access. It can also include a data workflow that defines the steps needed for cleansing, testing and integrating raw and refined data sets in order to make them suitable for analysis.

A DMP can be utilized by organizations that collect consumer data to ensure compliance with privacy laws on a global and state level, such https://taeglichedata.de/generated-post as the General Data Protection Regulation of the European Union or California’s Consumer Privacy Act. It can also be used to guide the development and implementation of policies and procedures that address security concerns for data.