Enterprise data management (EDM) is an organization's ability to accurately define, integrate, and efficiently retrieve data for both internal applications and external communications. EDM focuses on creating consistent, secure, and high-quality data that can be used to make informed decisions. It helps ensure rich raw data collection through ETL and proper storage in a data warehouse. Additionally, it can help organizations identify any type of discrepancy in data and data accessibility among the user group. Data loss is an issue that must be addressed at the organizational level, and EDM helps prevent the loss of key business data by ensuring timely and complete backup.
This task is to adopt, integrate and manage business data that is constantly moving through your systems; needless to say, the amount is increasing by leaps and bounds. As mentioned earlier, enterprise data management is as much about managing people as it is about managing data. Master Data Management (MDM) defines the architecture and business practices to better utilize all data from the Internet. However, many organizations struggle with enterprise data management, especially if they didn't implement policies and systems years ago. While some people use them interchangeably, enterprise data management is a crucial component of data governance. The sheer amount of data and the relentless flood of new incoming data make enterprise data management absolutely vital to an organization's success.
With software solutions, organizations can centrally manage their data assets, automate workflows, and ensure greater compliance with data regulations. Examples include multi-factor authentication, firewall, authorization access, antivirus software, and other data protection standards. Documented data management procedures ensure transparency for the rest of your organization and their integrity should be carefully considered. When successfully implemented, business transformation enables companies to pivot with agility based on data analysis of trends and desires. Proper data management across your organization enables you to detect hidden or siloed data assets and assess their value and level of risk.
Sub-optimal data quality reduces everything it touches, from affected productivity levels to analytics and business intelligence, and leads to the wrong conclusions.