Data management is a process that involves establishing and enforcing procedures, policies and processes to manage data throughout its entire life cycle. It ensures that data is reliable and accessible, facilitates regulatory compliance and enables informed decisions.
The importance of effective data management has grown https://taeglichedata.de/information-lifecycle-management-establishing-data-processes 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 growing amount of data that needs to be consolidated and delivered to business intelligence (BI) and analytics systems, enterprise resource planning (ERP) platforms, Internet of Things (IoT) sensors and machine learning and artificial intelligence (AI) tools to provide advanced insights.
Without a well-defined and standardized data management strategy, companies could end up with incompatible data silos and inconsistency of data sets that hamper the ability to run business intelligence and analytics applications. Data management issues can reduce trust between employees and customers.
To address these issues, companies must develop a plan for managing data (DMP) that includes the people and processes required to manage all kinds of data. For instance the DMP can assist researchers in determining the naming conventions that they should follow to organize data sets for long-term storage and easy access. It could also include data workflows that define the steps that must be followed to cleanse, validate and integrating raw data sets and refined data sets to make them suitable for analysis.
A DMP can be used by companies that collect customer data to ensure compliance with privacy laws at the state and global level, such as the General Data Protection Regulation of the European Union or California’s Consumer Privacy Act. It can be used to guide the creation and implementation of procedures and policies to address security threats to data.
