The Role of Taxonomy in Labeled Property Graphs (LPGs) & Graph Analytics
Taxonomies play a critical role in deriving meaningful insights from data by providing structured classifications that help organize complex information. While their use is well-established in frameworks like the Resource Description Framework (RDF), their integration with Labeled Property Graphs (LPGs) … Continue reading
Enhancing Insurance Fraud Detection through Graph-Based Link Analysis
A national agency overseeing insurance claims engaged EK to advise on developing and implementing graph-based analytics to support fraud detection. EK applied key concepts such as knowledge graphs, graph-based link analysis for detecting potentially suspicious behavior, and the underlying technology architecture required to instantiate a fully functional solution at the agency to address client challenges. Continue reading
Women’s Health Foundation – Semantic Classification POC
A humanitarian foundation focusing on women’s health faced a complex problem: determining the highest impact decision points in contraception adoption for specific markets and demographics. Two strategic objectives drove the initiative—first, understanding the multifaceted factors (from product attributes to social influences) that guide women’s contraceptive choices, and second, identifying actionable insights from disparate data sources. The key challenge was integrating internal survey response data with internal investment documents to answer nuanced competency questions such as, “What are the most frequently cited factors when considering a contraceptive method?” and “Which factors most strongly influence adoption or rejection?” This required a system that could not only ingest and organize heterogeneous data but also enable executives to visualize and act upon insights derived from complex cross-document analyses. Continue reading
Cutting Through the Noise: An Introduction to RDF & LPG Graphs
Graph is good. From capturing business understanding to support standardization and data analytics to informing more accurate LLM results through Graph-RAG, knowledge graphs are an important component of how modern businesses translate data and content into actionable knowledge and information. … Continue reading
What are the Different Types of Graphs? The Most Common Misconceptions and Understanding Their Applications
Over 80% of enterprise data remains unstructured, and with the rise of artificial intelligence (AI), traditional relational databases are becoming less effective at capturing the richness of organizational knowledge assets, institutional knowledge, and interconnected data. In modern enterprise data solutions, … Continue reading
The Resource Description Framework (RDF)
Simply defined, a knowledge graph is a network of entities, their attributes, and how they’re related to one another. While these networks can be captured and stored in a variety of formats, most implementations leverage a graph based tool or … Continue reading
Enhancing Retail Performance with Semantic Layer As an Enabler for Data and Analytics Teams
In the fast-paced retail sector, organizations need to be able to quickly view store performance analytics in order to make crucial decisions. A leading global retail chain faced significant delays of up to 5-6 weeks when attempting to retrieve essential store performance metrics and create reports for executive leadership. This bottleneck was largely due to … Continue reading
A Semantic Layer to Enable Risk Management at a Multinational Bank
Enterprise Knowledge is working with a multinational bank to enable their risk-assessing processes by using semantics and connected data. Heavily regulated financial services firms require comprehensive and complex risk management. This requires employees to thoroughly account for risk and report it in detail to regulators. Continue reading
A Semantic Layer Approach to Enterprise Knowledge Management and Information Findability
Within an organization or enterprise, multiple knowledge organization systems tend to be siloed and used for different purposes in different systems (the website, the intranet, technical documentation publishing, the product catalog, customer support articles, training materials, etc.). If this disparate … Continue reading
The Metadata Knowledge Graph
Modern data landscapes are characterized by immense volumes of diverse, disparate, and dynamic data sources, leaving many organizations struggling to effectively manage and derive value from their data assets. To address these challenges, a metadata knowledge graph serves as a … Continue reading