Data management is a method which involves the creation and implementation of procedures, policies and processes to handle data throughout its entire lifecycle. It ensures that data is useful and accessible, which facilitates regulatory compliance, and permits 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. The result is a flood of data that needs to be consolidated and sent to business intelligence (BI) and analytics systems such as enterprise resource planning (ERP) platforms, Internet of Things (IoT) sensors, machine learning and artificial intelligence (AI) tools for advanced insights.
Without a clearly defined data management plan, businesses may end up with data silos that are incompatible and inconsistent data sets which hinder the ability to operate business intelligence and analytics applications. Poor data management can also affect the confidence of employees and customers.
To tackle these issues it is crucial that companies https://taeglichedata.de/generated-post develop a data management plan (DMP) that includes the people and processes needed to manage all types of data. A DMP, for example, can help researchers determine the appropriate file name conventions they should utilize to organize data sets to store them long-term and make them simple to access. It can also contain an data workflow that specifies the steps for cleansing, testing and integrating raw and refined data sets to ensure they are suitable for analysis.
A DMP can be used by organizations that collect consumer data to ensure compliance with privacy laws on a global and state level, for example, the General Data Protection Regulation of the European Union or California’s Consumer Privacy Act. It can also aid in the creation of policies and procedures to deal with security threats to data and audits.
