Add Graph to Your 2021 Resolutions

Blog >
Add Graph to Your 2021 Resolutions

Happy new year! Here’s a selection of our best webinars, workshops and conference presentations from 2020, along with our most popular blog articles – there’s never been a better time to explore graph databases and analytics and this content is a great way to do that.

Top TigerGraph Webinars:

Graph Gurus 26: Using Graph Algorithms For Advanced Analytics – Part 1 Shortest Paths

Have you ever wondered how routing apps like Google Maps find the best route from one place to another? Finding that route is solved by the Shortest Path graph algorithm. Today, graph algorithms are moving from the classroom to a host of important and valuable operational and analytical applications. This webinar will give you an overview of graph algorithms, how to use them, and the categories of problems they can solve, and then take a closer look at path algorithms.

Graph Gurus 42: Accelerating Data Science With Python + TigerGraph

In this webinar we demonstrate how pyTigerGraph provides a familiar Python interface to TigerGraph database, allowing the data scientist to exploit the performance and functionality of the native, parallel graph engine and bringing the results into their data models and analytical methods. We will also show how quickly they can go from data exploration to visual query building to operationalisation of the insights.

Graph Gurus Episode 43: Introduction to Graph Algorithms for Machine Learning Certification

Graph algorithms are essential building blocks for analyzing your connected data and for conducting machine learning to gain deeper insights from that data. Graph algorithms can be used directly as unsupervised learning, or to enrich training sets for supervised learning. In this session, we will provide an overview of TigerGraph’s new training and certification program for Graph Algorithms for Machine Learning: content overview, video and demo format, and the certification process.

Graph Gurus 44: Building The Next Generation Customer Experience With Graph And Machine Learning

Improving customer experience in a digital world requires connected intelligence with the ability to have a real-time 360 view of your customers and the ability to make real-time decisions from every channel. This webinar shares the next generation customer experience solution powered by graph and machine learning.

TigerGraph Architecture Overview – Why It’s 100x Faster Than Competition

TigerGraph is the graph database designed from the ground up for speed with scale and scalability, on OLTP or OLAP workloads.

TigerGraph is in production with large graphs containing tens of terabytes of data, tens of billions of entities(vertices) and relationships (edges), supporting 23,000+ users.

Top Partner Webinars:

Expero and TigerGraph: Round Table On Fraud Detection With Graph And Machine Learning

During this online meet up, you learn from our experts on how Expero and TigerGraph technology can unlock the potential in your organization. We will feature unique TigerGraph and Expero technology lightning talks, followed by a short Q&A session. Four bite sized informative sessions to learn how to use TigerGraph and Expero to maximize the effectiveness of your business.

Expero and TigerGraph: Energy Roundtable On Graph And Machine Learning

Xilinx and TigerGraph: Powering the Next-Generation Machine Learning Solution with Graph Analytics on Connected Data

In this webinar, learn about the next-generation machine learning solution combining cutting edge hardware with graph analytics on connected data to answer these key questions:

How do I understand the wellness journey of a patient and find patients like them in real-time to figure out the recommended next steps?
Can I understand a customer’s journey while buying a product or service and find other customers who are on a similar journey in real-time to help them buy a suitable product or service?
Which groups of users and accounts are connected and appear to be part of a fraud or money laundering ring?

Top Graph Gurus Workshops:

Graph Gurus Workshop: Double the Performance of Your Fraud Detection System with Graph and Machine Learning

In this workshop we show you how to design a state of the art fraud detection system with graph database & machine learning:

A walk-through and demonstration of what analytic features can be rapidly generated by using graph analytics on modest cloud hardware
How the new system can dramatically improve fraud scores, find missed fraudulent activity and, reduce false-positives, in a standard machine-learning pipeline
Hands-on exercises to follow along and learn how to build your own solution

Graph Gurus Workshop: Business User Workshop – No Code Graph Analytics

In version 3.0, TigerGraph introduces two brand new no code tools – visual query builder and RDBMS to graph migration tool. Through simple clicks and drag-and-drop in GraphStudio UIs, these no code tools decrease the learning curve for more users, such as relational database developers, data scientists and business analysts. In this workshop, we will guide users to use no code RDBMS to Graph migration tool to auto generate graph schema and import data, and use visual query builder to construct graph patterns to query TigerGraph. In particular, we will discuss building Graph features for machine learning use cases. Additional hands-on sessions will cover more advanced features in GraphStudio and Admin Portal such as MultiGraph support and User Management.

Graph Gurus Workshop: Building the Next Generation Customer Experience

In this workshop we will show you how to design your next-generation customer experience solution with graph and machine learning in addition to:

A walk-through and demonstration of a real-time customer360 graph database that leverages graph analytics.
How a graph analytics solution can dramatically improve customer experience across all channels, provide personalized recommendations for Next Best Action and Offer.
How to use graph analytics for high value customer experience algorithms for customer segmentation, customer churn, and customer journey.
An overview of the TigerGraph Developer Ecosystem and various integration options for Data Science, Engineering, and DevOps groups.

Top Graph + AI World Sessions:

“Accelerating Supply Chain Planning at Jaguar Land Rover from 3 weeks to 45 minutes with Graph”

Harry Powell, Director of Data and Analytics, Jaguar Land Rover

The automotive supply chain is one of the most complex and global in the world, with the average car being made up of around 4,500 parts from a supply base of 30,000 individual parts, produced by hundreds of suppliers, relying on forecasts issued years in advance. This session will cover how by using graph, Jaguar Land Rover have reduced query times across their complex supply chain model from 3 weeks to 45 minutes allowing them to accurately plan and rapidly pivot in response to supply and demand uncertainties around the Covid-19 pandemic.

“Combining World’s Largest Healthcare Graph and AI to Deliver Member 360 at UnitedHealth Group”

Edward Sverdlin, VP, Advanced Technology Collaborative, R&D at UnitedHealth Group

UnitedHealth Group has developed the largest graph database in healthcare and combined it with AI to link, analyze, and make real-time care path recommendations for 50 million patients. Key highlights include:

Largest healthcare graph with 10+ billion vertices (entities – claims, patients, doctors) and 50+ billion edges (relationships)
Member(Customer) Journey application used by over 23,000 call center and other employees for never-before visibility and insights
Real-time AI application: similarity matching to find matching patients based on 200 features across tens of millions of population in milliseconds
Combine Graph Database with AI/ML to build a model to predict disease in just 8 hours

“Leveraging Knowledge Graphs to Accelerate Intuit’s AI Journey”

Dr. Jay Yu, Distinguished Engineer & Architect, Intuit

Tens of millions of consumers and businesses around the world rely on Intuit to deliver financial, accounting, and tax preparation software and services. Knowledge Engineering, Knowledge Graphs, and Machine Learning are the foundational technology for Intuit to transform into an AI-driven expert platform.

“Graph-Based Identity Resolution at Scale”

Chinmay Nerurkar, Dr. Subha Narasimhan, Dr, Yana Volkovich, Michael Berry

One of the main drvers of the AT&T, WarnerMedia and Xandr success story is to combine their data assets to provide solutions for customers including the cross-device product offering, targeting the right users and content personalization. The data across these companies is not only large, containing billions of identifiers but also consists of various types of identifiers, for example, user accounts and cookies. Additionally, data from other third-party data providers is utilized to further extend our data coverage and provide a wider breadth of offerings to our clients. To this end, Xandr has built a multi-node, high-availability TigerGraph cluster to consolidate this data and store it in an identity graph. The Identity Resolution algorithm comprises of three components – label propagation, resolving large clusters and label persistence – which is run in a MapReduce fashion on the distributed identity graph.

“Application of Graph Model in Fintech and Risk Management”

Dr. Jing Wang, Founder and CEO, Fintell

FinTell has built a graph network with tens of billions edges and nodes based upon 1.5 billion monthly active mobile devices. Graph model helps FinTell provide superior service for the risk management of financial institutions.

2021 - The Year Graph Databases Go Mainstream

2021 is going to be the year that graph databases and analytics become mainstream – now is an ideal time for you to get started with this exciting technology. One of the best ways to get started with graph analytics is with TigerGraph Cloud – it’s free and you can create an account in a few minutes. Sign up here.