The global cognitive data management market was worth USD 1.71 billion in 2023. The global market is expected to reach USD 2.07 billion in 2024 and USD 9.45 billion by 2032, growing at a CAGR of 20.9% during the forecast period.
Data management is the main and most important task of IT, but it has also been undervalued and largely overlooked. Cognitive data management allows you to look for leverage due to recent advances in cognitive computing to automate general manual activities within data management. As technologies develop, the volume of complex data also increases. Cognitive data management is used to reduce the administrative burden of data management. Cognitive management provides the contemporary data management strategy, synchronization with the storage resource management engine, and the data management strategy framework. 2016 RAVN Systems launched RAVN Connect Enterprise with the Google Search Appliance replacement program. This RAVN Connect Enterprise can connect companies that stand out from other search solutions by their cognitive characteristics and perform unstructured business research and data management. Therefore, the data management market is growing due to computer technology and advanced analytics developments.
The rapid adoption of automation and cloud technologies in enterprises and businesses has led to a significant increase in data generation and traffic in the cloud. This surge in data has, in turn, fueled the growth of data management software, driving the market demand for cognitive data management. It's worth noting that more than 90% of businesses using the cloud have reported a substantial growth in internet traffic, a clear indicator of the data management landscape's evolution.
The rapid adoption of Big Data and cloud computing has made cognitive data management more accessible and provides reliable results to various end industries, including the IT and telecommunications sector, which should better adopt these solutions during the forecast period. With automatic natural language processing (NLP) systems, data mining, and other characters in machine learning technologies applied to discover essential information from unstructured data, IT and telecommunications are expected to create increased demand for these solutions.
Furthermore, the volume of big data in data warehouses is changing rapidly, and its complexity leads to the selection of cognitive services. It provides the company with accurate information to refine and stimulate business decision-making. According to Cisco Systems Inc., this volume touched 124 exabytes in 2018 and is expected to generate 403 exabytes by 2021.
Machine assets create large amounts of data with the potential for exceptional business value. Companies also leverage cognitive machine learning to perform predictive maintenance to extract that value from a data lake. Several IT and telecom companies are adopting cognitive services to develop customer engagement, gain a competitive advantage, and streamline operations over others. For example, at the end of 2018, Du, a telecommunications company in the UAE, collaborated with Mircosoft for cognitive services on all of their contemporary touch points and digital channels.
Also, using cognitive data management in various vertical industry sectors will stimulate growth in the global market in the near future. Advances in industrial IT infrastructure worldwide have led to the growth of the market for cognitive data management worldwide. At the same time, the growing growth of IoT devices is reflected in the growth of digital data along with the growing adoption of cognitive data management solutions. These factors are expected to drive growth in the global cognitive data management market in the coming years.
However, integrating new technologies into traditional infrastructure has become a serious challenge for market players. The high cost of implementing cognitive data management solutions creates barriers for providers of these solutions. In addition, interoperability and the integration of new technologies in existing infrastructures are some of the main challenges for providers of cognitive data management solutions.
REPORT METRIC |
DETAILS |
Market Size Available |
2023 to 2032 |
Base Year |
2023 |
Forecast Period |
2024 to 2032 |
CAGR |
20.9% |
Segments Covered |
By Component, Organization Size, Deployment Type, Vertical, and Region |
Various Analyses Covered |
Global, Regional & Country Level Analysis, Segment-Level Analysis, DROC, PESTLE Analysis, Porter’s Five Forces Analysis, Competitive Landscape, Analyst Overview on Investment Opportunities |
Regions Covered |
North America, Europe, APAC, Latin America, Middle East & Africa |
Market Leaders Profiled |
Attivio, CognitiveScale, Cognizant, DATUM, Expert System, HPE, IBM, Immuta, Informatica, Infosys, Kingland Systems, Microsoft, Oracle, Pingar, Reltio, Saksoft, Salesforce, SAP, SAS and Others. |
North America is foreseen to account for the most substantial portion of the global cognitive data management market in the future. Various determinants are envisaged to strengthen market growth in the region. These factors include increased investment in multi-stakeholder cognitive technologies, greater infrastructure advances, adoption and government support for artificial intelligence (AI), transformation of digital budgets, and growing IT.
Some of the major players in the global cognitive data management market include Attivio, CognitiveScale, Cognizant, DATUM, Expert System, HPE, IBM, Immuta, Informatica, Infosys, Kingland Systems, Microsoft, Oracle, Pingar, Reltio, Saksoft, Salesforce, SAP, SAS and other providers of cognitive data management solutions.
By Component
By Organization Size
By Deployment Type
By Vertical
Of these, the IT and telecommunications segment accounted for the leading portion and is also anticipated to expand with a rapid share in the foreseen years.
By Region
Frequently Asked Questions
Implementing GCDM enables multinational corporations to streamline data management processes across diverse regions, enhance data quality and accuracy, facilitate real-time insights, improve decision-making, and maintain regulatory compliance across jurisdictions.
GCDM utilizes natural language processing (NLP) and cultural context analysis to process multilingual and multicultural data effectively. It can identify language nuances, translate data accurately, and contextualize information based on cultural sensitivities, ensuring a comprehensive understanding of global datasets.
GCDM leverages advanced streaming analytics capabilities to process real-time data streams from diverse sources across the globe. It enables organizations to derive actionable insights, detect emerging trends, and make informed decisions in real-time to drive business agility and competitiveness.
Organizations can measure the ROI of implementing GCDM by assessing factors such as improved operational efficiency, cost savings from automation, increased revenue through data-driven insights, reduced compliance risks, and enhanced competitive advantage in global markets.
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