TigerGraph 101 - Part One - An Introduction to Graph

Presented by

Dan Barkus, TigerGraph Developer Advocate

About this talk

“By 2025, graph technologies will be used in 80% of data and analytics innovations, up from 10% in 2021, facilitating rapid decision-making across the enterprise.” * – Rita Sallam, Distinguished VP and Fellow, Gartner Research Now is the best time to learn the fundamentals of graph and take advantage of the next frontier for data science and analytics. Watch the 4-part series now. Watch part 1 of our 4-part series, covering: - An introduction to graph - How graph compares to relational databases - Real-world use cases for graph - How to create your first graph using TigerGraph Cloud's GraphStudio Resource list and the slide deck here: https://bit.ly/3kRz0Tw Coming up... Part 2 - Data Acquisition and Graph Preparation Part 3 - Schema Modeling and Data Loading Part 4 - Querying and Beyond * Gartner, Inc.: Graph Steps Onto the Main Stage of Data and Analytics: A Gartner Trend Insight Report. Published 14 December 2020.
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TigerGraph is a platform for advanced analytics and machine learning on connected data. Based on the industry’s first and only distributed native graph database, TigerGraph’s proven technology supports advanced analytics and machine learning applications such as fraud detection, anti-money laundering (AML), entity resolution, customer 360, data operations, digital twin, recommendations, knowledge graph, cybersecurity, supply chain, IoT, and network analysis. This channel showcases TigerGraph's technology and how it helps organisations tap into their data to gain key insights into the business decisions and processes driving innovation, growth and cost optimisation. For more information visit www.tigergraph.com