Blogs
AI Analytics and Data Sciences
The Power of Graph Technology in AI Landscape
Overview A recent study by Gartner states that by 2025, graph technology will dominate ...
AI Analytics and Data Sciences
Bridging the Digital Gap: Graph Technology Empowering AI Applications
Overview Businesses are embracing graph technology as the ultimate solution to unlock ...
AI Analytics and Data Sciences
The What, Why, and How of Entity Resolution in Modern Organizations
Introduction As a powerful tool for modern organizations, entity resolution harnesses the ...
AI Analytics and Data Sciences
Strategic and tactical things to consider when building a Minimum Viable Knowledge Graph
In today’s environment, one does not have to be a particularly large organization to ...
AI Analytics and Data Sciences
What It Means to Be an Analytics Advisor in Today’s Data and Computational Environment
Today's businesses must derive insight from decentralized and multi-modal data near real ...
AI Analytics and Data Sciences
Consumer Confidence After the COVID Crash – Is Pent-Up Demand Really Backed with Money?
Overview The year and a half after the COVID crash has left consumer confidence adrift on ...
AI Analytics and Data Sciences
Connecting the Dots: Data, Artificial Intelligence, and Cloud (A Message to Shareholders)
Overview Technology spend has been shifting to the business for some time and now more ...
AI Analytics and Data Sciences
Antifragility, Machine Learning, and Graph-Structured Data (Ontologies) – Part 3 of 3
Antifragility is a strong criterion that says that if we experience shocks or unexpected ...
AI Analytics and Data Sciences
Antifragility, Machine Learning, and Graph-Structured Data (Ontologies) – Part 2 of 3
Overview In the movie “The Core” [spoiler alert!] there is a great example (completely ...
AI Analytics and Data Sciences
Antifragility, Machine Learning, and Graph-Structured Data (Ontologies) – Part 1 of 3
Overview A client recently asked if our entity matching algorithms are “antifragile”. ...