Data management is the process of creating and enforcing rules, processes and procedures for handling data throughout its entire lifecycle. It ensures data is accessible and useful, facilitates regulatory compliance and informed decision-making and ultimately creates an advantage to businesses.
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 growing amount of data that must be consolidated and delivered to business intelligence (BI) and analytics systems as well as enterprise resource planning (ERP) platforms, Internet of Things (IoT) sensors and machine learning and generative artificial intelligence (AI) tools for advanced insights.
Without a clear strategy for managing data, businesses could end up with data silos that are incompatible and inconsistent data sets that hinder the ability to manage business intelligence and analytics applications. Poor data management can also affect the trust of customers and employees.
To address these issues companies need to develop a data-management strategy (DMP) which includes the people and processes needed to manage all types data. For example an DMP will help researchers determine the file name conventions they should apply to organize data sets https://taeglichedata.de/maintaining-data-processes-throughout-the-information-lifecycle/ to ensure long-term storage as well as easy access. It can also include data workflows that define the steps to be taken for cleansing, validating and integrating raw data sets as well as refined data sets in order to allow them to be suitable for analysis.
A DMP can be utilized by organizations that collect consumer data to ensure compliance with privacy laws at the global and state 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 policies and procedures that address data security threats.
