A $2.4 billion opportunity despite issues with data quality and integration and scalability

Global Knowledge Graph Market

Dublin, Feb. 21, 2024 (GLOBE NEWSWIRE) — The “Global Knowledge Graph Market by Offering (Solutions, Services), By Data Source (Structured, Unstructured, Semi-Structured), Industry (BFSI, IT & ITeS, Telecom, Healthcare), Model Type, Application, Type and Region – Forecast to 2028” report has been added to ResearchAndMarkets.com’s offering.

The report predicts that the knowledge graph market is expected to grow from USD 0.9 billion in 2023 to USD 2.4 billion by 2028, at a CAGR of 21.8% during the forecast period. Organizations are increasingly focusing on knowledge discovery and management to improve decision-making processes and gain actionable insights. Knowledge graphs help organize complex information and extract valuable knowledge from structured and unstructured data, contributing to more informed decision making.

Vertically, the IT and ITeS segment is expected to grow at the highest CAGR during the forecast period

The market for knowledge graphs in the IT and ITeS sector has expanded and is expected to change significantly in the coming years, demonstrating the market’s critical role in data management and knowledge representation. Knowledge graphs are essential for integrating diverse data and facilitating well-informed decision making in various industries, including e-commerce, healthcare, finance, and others. These graphs have further strengthened search engines and recommendation systems, giving users more accurate and tailored results. Thanks to integration with AI systems and semantic technologies, they can now understand complicated relationships and situations much better.

According to data source, the unstructured data segment is expected to have the largest market size during the forecast period

Research in data enrichment, contextual understanding, and semantic analysis has advanced significantly due to the knowledge graph market’s increasing focus on unstructured data sources. By applying advanced natural language processing algorithms, businesses can gain significant insights from a variety of unstructured data sources, such as textual content, social media feeds, and customer reviews. Due to the abundance of rich data, the knowledge graph can provide a more thorough and integrated understanding of different disciplines, leading to more precise insights and tailored suggestions.

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Asia Pacific is expected to grow at the highest CAGR during the forecast period

The Asia Pacific region has become a hotbed for the rapid adoption of knowledge graphs, due to its dynamic technological landscape and the increasing complexity of data. With a strong emphasis on data-driven decision-making and an emerging need for personalized customer experiences, businesses have turned to knowledge graphs as a solution to manage and analyze complex data sets from diverse sources. Government initiatives supporting technological advancements have further fueled the growth of the knowledge graph market, facilitating innovation and economic development. As the region continues to invest in cutting-edge technology, the potential for knowledge graphs to streamline data management and informed decision-making remains a key focus for businesses and organizations across multiple sectors.

Key features

Market dynamics

Managers

Rapid growth in data volume and complexity

Advanced AI and ML algorithms and a large amount of generated data

Semantic Web and Linked Data Initiatives

Restrictions

Opportunities

Integrating NLP techniques into Knowledge Graph Market to aid data enrichment and improve user experiences

Increasing adoption in healthcare and life sciences

Challenges

Use cases

Kerberos Prevent Money Laundering and Develop Compliance Management Application for Risk Management with Neo4J

Yahoo7 represents content within Knowledge Graph with the help of Blazegraph

Neo4J enabled and visualized connections between elements of Panama Papers leaks

Graph technology helped the US military by tracking and analyzing equipment maintenance after Neo4J was put into service

The database group helped Springermaterials accelerate research with semantic search

Technology Analysis

Adjacent technologies

NLP

Big data and analytics

Graph of neural networks

Related technologies

Cloud computing

AI and ML

IoT

Blockchain

Companies profiled

ArangoDB

AWS

Necessities

Cambridge Semantics

Talk

Datavid

Diffbot

Eccena

Flurry

Franz Inc.

Graphicware

Chart base

IBM

Marklogic

Memgraph

Microsoft

Neo4J

Onlim

Ontotext

Openlink software

Oracle

JUICE

Semantic Web Company

star dog

Tigergrave

For more information on this report visit https://www.researchandmarkets.com/r/yctu1w

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