Enterprise Data Management Market is predicted to rise with a CAGR of 9.3% over the forecast period by generating a revenue of $126.9 billion by 2026.
Enterprise Data Management program collates all the data related with making major decisions and building a strategy for the organization. Enterprise Data Management helps to identify the compliance, operating efficiencies, risksand build client relationship, which results in data quality, control on the data and information storage.
Rise in the use of data management application in many of the organization is predicted to drive the Enterprise Data Management Market over the forecast period. The demand for data management has increased due to handling large data sets by data integration, data profiling, checking the quality of data, metadata management and many other data related problems. Moreover, enterprise data management helps in sharing, consistency, reliability and governing information to the organization for taking major decisions, and this is predicted to be the major driving factor for the market.
Data privacy is predicted to hamper the growth of the market during the forecast period. Most of the companies handle data with the help of open source applications which includes various processes and algorithms. Most of the processes and algorithms are run through open sources which enable hackers to get the source code without difficulty if the data are not highly protected. These are the biggest restraints for the growth of the market in the forecast period.
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Software component segment is predicted to rise with a CAGR of 8.5% over the forecast period by generating a revenue of $71.2 billion by 2026.Software component segment is predicted to have the largest market share over the forecast period. The Software component segment is predicted to grow as most of the organizations use open source software for analytics, testing and security for data visualization, data interpretation and handling data.
Cloud deployment segment is estimated to be the fastest growing segment over the forecast period. Cloud based segment is predicted to rise with a CAGR of 11.4% over the forecast period by generating a revenue of $53.6 billion by 2026.Cloud helps the organization to consolidate processes like backing up the data, recovering files if lost, archiving the data in the most cost-effective ways, due to which this segment is predicted to give boost to the overall market growth over the forecast period.
Telecom & information technologysegment is predicted to have the largest market share over the forecast period. Telecom & information technologysegment ispredicted to rise with a CAGR of 10.1% over the forecast period by generating a revenue of $15.6 billion by 2026. Telecom & information technology has a huge set of customer data base based on various criteria such as demographics and socioeconomics. This segment is in demand to handle this large data with the help of various enterprise data management software, which is predicted to boost the telecom & information technologysegment over the forecast period.
Asia-Pacific market is predicted to hold the largest market share.Asia-Pacific market is predicted to rise with a CAGR of 9.0% over the forecast period by generating a revenue of $36.8 billion by 2026.The Asia-Pacific region is expected to rise due to significant investments by large companies in the region and an improvement in technology over the projected period. North America market is predicted to rise with a CAGR of 9.8% over the forecast period by generating a revenue of $34.7 billion by 2026.With a huge number of professionals with respect to cloud and government concentrating primarily on analytics and other artificial intelligence applications, the market in the region is expected to grow over the forecast period.
The major players in Enterprise Data Management Market are Amazon Web Services, Inc., TierPoint, LLC., VMware Inc.,Microsoft, HP Development Company, L.P.,Cloudera, Inc.,SAS Institute Inc.,SAP SE,IBM Corporation, andNTT Communications Corporation among others.
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