Handling Intricate Datasets Efficiently with the Semantic Knowledge Graphing Market

A knowledge graph, also called a semantic network, is a graph-structured data model representing a network of real-world entities. These entities may be objects, situations, events, or other abstract concepts. Since the introduction of the semantic web, knowledge graphs are usually linked to open data projects, acting as a connection between concepts and entities.

Besides, knowledge graphs are primarily used by search engines like Google and Bing, knowledge engines such as Alexa and Siri, and social platforms like LinkedIn and Facebook. This blog post covers the basics of semantic knowledge graphing and sheds light on the major developments in the semantic knowledge graphing market.

Quick Overview of Knowledge Graphs

As mentioned earlier, knowledge graphs are large collections of interlinked descriptions of real-world entities. These graphs focus on the semantic relation and attributes between entities, crucial for providing machines and humans context and means for automated reasoning.

Unlike traditional database systems that usually deal with simple data storage, knowledge graphs focus on entities and their connection. What makes a knowledge graph unique is the ontology or semantic data model the graph is built upon. The ontology offers a holistic view of the data and gives it meaning that machines and humans can interpret.

What’s Driving the Market Growth?

According to a new study by Polaris Market Research & Consulting, Inc. , the semantic knowledge graphing market size was USD 1,387.68 million in 2022 and is expected to grow at a CAGR of 14.3%, generating an estimated revenue of USD 5,281.39 million by 2032.

The ever-growing volumes of data on the internet have resulted in increased demand for tailored experiences and personalized recommendations. Knowledge graphs can seamlessly collect and consolidate data from multiple sources like daily activity and search history to create an in-depth user activity graph. This allows providers to cater to individual preferences by sending targeted messages and delivering personalized recommendations.

Another factor propelling the market forward is the growing prevalence of the Internet of Things (#IoT). Semantic knowledge graphs offer a way to analyze and integrate data from multiple #IoTdevices. Besides, organizations can use these graphs to optimize operations and improve marketing strategies by leveraging IoT connectivity.

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Key Characteristics of Semantic Knowledge Graph

Below are the major characteristics of knowledge graphs developed by semantic knowledge graphing market key players:

Semantically modeled: These graphs come with a semantic layer that gives meaning to data through formal naming and representation.

Machine interpretable: Semantic knowledge graphs are designed so computers and humans can easily interpret them.

Follows open standards: Knowledge graphs follow open standards to promote collaboration and reusability.

Flexible: Semantic knowledge graphs are designed to be flexible enough to accommodate domain changes. This allows the graphs to grow and evolve.

North America Accounted for the Largest Market Share in 2022

The North America region held a considerable share of the semantic knowledge graphing market in 2022. The region’s growth can largely be attributed to the significant investments in semantic knowledge graphing technologies, especially in the #healthcaremedicine sectors. The United States has witnessed robust growth, with numerous firms actively developing solutions to improve data analysis and interoperability using knowledge graphs.

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Recent Developments

In October 2022, Amazon Web Services (AWS) (AWS) introduced its new graph database service, Amazon Neptune. The new service is specifically designed to handle large-scale knowledge graphs and caters to the processing needs of large interconnected networks.

To Conclude

A #semanticknowledgegraph is a network that caters to an organization’s need to handle and derive valuable insights from large datasets efficiently. The rising demand for personalized services and the growing demand for seamless interoperability across diverse systems will likely boost semantic knowledge graphing market sales in the coming years.