Enterprise data management (EDM) is a comprehensive approach to managing an organization’s data. It includes processes and technologies for acquiring, storing, governing, and analyzing data.
EDM is designed to help organizations get more value from their data and use it more effectively. It helps them improve decision-making, increase operational efficiency, and better manage risk. EDM also enables organizations to share data more effectively and comply with regulations.
EDM is a complex undertaking that requires a deep understanding of an organization’s business goals and objectives. It also requires a sound technical foundation and the ability to integrate disparate data sources.
Organizations that implement EDM effectively can realize significant benefits. They can improve their decision-making, increase their operational efficiency, and better manage risk.
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Key Trends
Enterprise data management (EDM) is the comprehensive management of an enterprise’s data assets. It includes all aspects of data management, from data acquisition and warehousing to data quality and governance. EDM is a critical part of an enterprise’s overall information management strategy.
There are four key trends in Enterprise Data Management technology:
1. Data integration
2. Data quality
3. Data governance
4. Big data
Data integration is the process of combining data from multiple sources into a single repository. This is important for businesses because it allows them to have a single view of their data, which can be used for reporting and decision-making.
Key Drivers
The key drivers of the EDM market are the increasing volume and complexity of enterprise data, the need to improve data quality and governance, and the need to better leverage data assets for competitive advantage.
The volume of enterprise data is growing exponentially, driven by the proliferation of digital devices and sensors, the growth of social media and other online data sources, and the increasing use of data-intensive applications such as big data and analytics. This growth is straining the capacity of traditional data management approaches, such as relational database management systems, to cope.
At the same time, the need to improve data quality and governance is becoming more urgent. Poor data quality can lead to inaccurate business decisions, while inadequate data governance can result in regulatory compliance problems and reputational damage.
Finally, enterprises are under pressure to better leverage their data assets to gain a competitive advantage. The ability to effectively analyze and utilize big data is becoming a key differentiator in many industries.
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Market Segments
The Enterprise Data Management Market is segmented on the basis of component, deployment, organization size and region. On the basis of component, the market is segmented into software and service. By deployment, the market is segmented into cloud and on premises. By organization size, the industry are broadly classified into large enterprises and small and medium-sized enterprises (SMEs). Region-wise, the market is segmented into North America, Europe, Asia-Pacific, and the Rest of the World.
Key Players
The Enterprise Data Management Market report includes players such as IBM Corporation, SAS Institute Inc., Teradata Corporation, Oracle Corporation, SAP SE, Symantec, Cloudera, Inc., Amazon Web Services, Inc, EnterWorks, Inc. and Zaloni, Inc.
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