Global Enterprise Data Management Market

Enterprise Data Management Size, Share, Growth Analysis, By Component (Software and Services), By Deployment Mode (On-Premises and Cloud), By Organization Size (Small & Medium Enterprise (SME) and Large Enterprise), By Industry Vertical (Healthcare & Life Sciences, Banking, Financial Services, & Insurance), By Region - Industry Forecast 2024-2031


Report ID: SQMIG45B2084 | Region: Global | Published Date: September, 2024
Pages: 165 | Tables: 87 | Figures: 76

Enterprise Data Management Market Insights

Global Enterprise Data Management Market size was valued at USD 93.40 billion in 2022 and is poised to grow from USD 102.28 billion in 2023 to USD 211.39 billion by 2031, growing at a CAGR of 9.5% in the forecast period (2024-2031).

The Enterprise data management market is expected to experience significant growth in the coming years, driven by the increasing adoption of data management applications in organizations. The rise in demand for data management is a result of the need to handle large data sets, perform data integration, conduct data profiling, ensure data quality, and manage metadata effectively. These challenges have prompted organizations to invest in data management solutions to enable efficient sharing, consistency, reliability, and information management for critical decision-making processes. This is anticipated to be a major driver for market growth. However, data privacy concerns are expected to hinder the growth of the market during the projected period. Many businesses rely on open source software for data management, which involves various procedures and algorithms. If data is not adequately safeguarded, hackers can easily access the source code, as most procedures and algorithms are operated through open sources. Ensuring robust data security measures will be crucial to overcome this obstacle, as data breaches can have severe consequences. 

Addressing data privacy concerns will be vital to fostering market growth in the predicted year. Moreover, there is increasing consumer demand for business data management solutions that enable the generation of valuable insights from unstructured or redundant data. These solutions facilitate effective data management across departments within an organization. As organizations place greater emphasis on ensuring timely and accurate information, the demand for enterprise data management solutions is expected to rise. These factors are projected to drive the growth of the global corporate enterprise data management market during the forecast period.

US Enterprise Data Management Market  is poised to grow at a sustainable CAGR for the next forecast year.

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FAQs

The key element of enterprise data management (EDM) is data governance. Data governance is the set of policies, processes, and structures that ensure that data is managed effectively within an organization. It includes activities such as data quality management, data security, and data compliance.

Enterprise data management (EDM) and Infrastructure as a Service (IaaS) are two different approaches to managing data. EDM is a holistic approach that encompasses the entire data lifecycle, from collection to storage to analysis. IaaS is a more focused approach that provides the underlying infrastructure for storing and managing data.

Achieving enterprise data management can be challenging due to various factors. Some of the main challenges include ensuring data quality, integrating data from different sources, protecting data security, establishing data governance policies, designing a scalable data architecture, developing data analytics capabilities, and ensuring compliance with data privacy regulations.

Enterprise data management initiatives typically focus on key activities such as data governance, data quality management, data integration, and master data management. Data governance involves establishing policies and procedures for managing data. Data quality management ensures that data is accurate, complete, and consistent. Data integration involves integrating data from different sources into a single view. Master data management creates a single source of truth for key data elements. These activities are critical for effective enterprise data management.

Global Enterprise Data Management Market size was valued at USD 93.40 billion in 2022 and is poised to grow from USD 102.28 billion in 2023 to USD 211.39 billion by 2031, growing at a CAGR of 9.5% in the forecast period (2024-2031).

The global enterprise data management market is highly competitive and characterized by the presence of several key players. Companies operating in this market focus on developing innovative solutions to meet the evolving data management needs of organizations across various industries. Some of the major players in the market engage in strategies such as mergers and acquisitions, partnerships, collaborations, and product launches to strengthen their market position and expand their customer base. Additionally, technological advancements, particularly in areas like AI, ML, cloud computing, and cybersecurity, are key areas of focus for these players as they seek to provide robust and comprehensive enterprise data management solutions to their clients. 'IBM (US) ', 'SAS Institute (US) ', 'Teradata (US) ', 'Oracle (US) ', 'SAP SE (Germany) ', 'Talend (France) ', 'Symantec (US) ', 'Cloudera (US) ', 'Ataccama (Canada) ', 'Informatica (US) ', 'Mindtree (India) ', 'Qlik (US) ', 'Enterworks (US) ', 'MapR (US) ', 'Goldensource (US) ', 'AWS (US) ', 'MuleSoft (US) ', 'Micro Focus (UK) ', 'Zaloni (US) ', 'Actian (US)'

Organizations across various industries are recognizing the value of data as a strategic asset. To make informed decisions, enterprises are adopting enterprise data management strategies and solutions. By implementing robust data management frameworks and platforms, organizations can ensure data quality, consistency, and reliability, enabling effective data-driven decision-making. For example, a multinational retail corporation may implement an enterprise data management strategy to centralize customer data, enabling personalized marketing campaigns and targeted promotions based on customer preferences.

Artificial Intelligence and Machine Learning: AI and machine learning technologies are transforming enterprise data management. These technologies can automate data profiling, data cleansing, and data integration tasks, reducing manual effort and enhancing data quality. AI-powered analytics also enable organizations to uncover valuable insights from their data, driving business growth and innovation. For instance, a financial services firm may utilize AI algorithms in an enterprise data management solution to automate fraud detection and risk assessment processes.

In 2022, the North America region emerged as the dominant market in the enterprise data management industry, accounting for the largest share of 36.5% in terms of overall revenue. The region's market growth can be attributed to the increasing demand for risk management solutions and the growing need for timely and accurate information. Several prominent companies in North America, including Amazon Web Services, Oracle, and IBM, are placing strong emphasis on digital transformation and are often at the forefront of adopting next-generation technologies such as Internet of Things (IoT), big data analytics, Artificial Intelligence (AI), and machine learning. For example, in May 2021, IBM Corp. acquired Catalogic Software, a leading provider of data protection and copy data management solutions across industries. This acquisition enables Catalogic Software to focus on developing data security and enterprise and cloud data protection solutions. The continued adoption of these advanced technologies by enterprises in the region contributes to the positive market growth outlook.

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Global Enterprise Data Management Market

Report ID: SQMIG45B2084

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