Data management is the process of creating and enforcing rules, processes and procedures for handling data throughout its lifecycle. It ensures that data is easily accessible and useful, assists in regulatory compliance and informed decision-making and ultimately provides businesses with an edge in the market.
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 needs to be consolidated and sent to business analytics (BI) systems such as enterprise resource management (ERP) platforms, Internet of Things (IoT), sensors, and machine learning, and generative artificial Intelligence (AI) tools, for advanced insights.
Without a clear https://taeglichedata.de/ strategy for managing data, businesses could end up with data silos that are incompatible and inconsistent data sets which hinder the ability to manage business intelligence and analytics applications. Poor data management can also cause a loss of confidence in employees and customers.
To tackle these issues, companies must develop a data-management strategy (DMP) which includes the people and processes needed to handle all kinds of data. For instance an DMP can assist researchers in determining the naming conventions for files they should employ to structure data sets to ensure long-term storage as well as easy access. It can also contain the data workflow that outlines the steps needed for cleansing, checking and integrating raw as well as refined data sets in order to make them suitable for analysis.
A DMP can be utilized by companies that collect consumer data to ensure compliance with privacy laws on a global and state level, like 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 procedures and policies which address threats to data security.