https://taeglichedata.de/pflege-von-datenprozessen-nach-sitzungssaal
Data management is the process of establishing and enforcing rules, processes and procedures for handling data throughout its entire lifecycle. It makes sure that data is available and useful, assists in the compliance of regulators and makes informed decisions, and ultimately provides 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 proliferation 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, machine learning and Artificial Intelligence generative (AI) tools to provide advanced insights.
Without a well-defined and standardized data management strategy, companies can end up with uncompatible data silos and inconsistency of data sets which make it difficult to run business intelligence and analytics applications. Inadequate data management can cause distrust between customers and employees.
To tackle these issues, companies must develop an effective data-management plan (DMP) that includes the processes and people needed to manage all types of data. For instance an DMP will help researchers determine the file name conventions they should employ to structure data sets for long-term storage and access. It may also include a data workflow that defines the steps involved in cleansing, validating and integrating raw and refined data sets in order to ensure they are 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 scale, such as the General Data Protection Regulation of the European Union or California’s Consumer Privacy Act. It can also guide the development of policies and procedures to address security threats to data and audits.