Graph + AI World:                   

From Dataframes to Graph: Data Science with pyTigerGraph

Graph + AI World Session - Recorded September 2020
pyTigerGraph empowers data scientists to create, load and analyze their data with TigerGraph and Python. This workshop will demonstrate an end-to-end graph analytics pipeline using pyTigerGraph that starts with a tabular dataset, then creating and loading a graph model, and ultimately generating insights utilizing the relationships between data points.

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“TigerGraph is highly configurable ands can fit your specific use case. Whether you’re trying to get super fast query times or run heavy graph processing algorithms, setting the right configuration on your cluster will make all the difference.”


About TigerGraph

TigerGraph is the only scalable graph database for the enterprise. Based on the industry’s first Native and Parallel Graph technology, TigerGraph unleashes the power of interconnected data, offering organizations deeper insights and better outcomes. TigerGraph fulfills the true promise and benefits of the graph platform by tackling the toughest data challenges in real time, no matter how large or complex the dataset. TigerGraph’s proven technology supports applications such as fraud detection, customer 360, MDM, IoT, AI and machine learning to make sense of ever-changing big data, and is used by customers including Amgen, China Mobile, Intuit, Wish and Zillow, along with some of the world’s largest healthcare, entertainment and financial institutions. 


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