Chapter 2: Data Modeling & Schema Design

How to Deduplicate Customer Data with Graphs

In this 4-minute video, we explore deduplicating records with the help of graph databases. 📊 Explore real-world examples showcasing how #GraphDatabases can help with data management and decision-making processes, making them a game-changer for businesses. Discover the transformative power of #EntityResolution and #DataQuality. #DataManagement...

Graph+AI Breakout: Graph Modeling for Blockchain Forensics: Better "Tokenomics"

Distributed Ledger Technologies (DLT), in general, and the blockchain specifically, offer a variety of interesting opportunities, from inclusive financing for underserved communities to being the platform for a scalable Web 3.0. Securing the blockchain involves understanding a special class of non-reciprocal, sequenced, temporal networks that...

GSQL SCHEMA DESIGN & QUERY WRITING BEST PRACTICES: Part 2: Query Writing Best Practices

GSQL is a user-friendly, highly expressive, and Turing-complete graph query language. Although learning GSQL is relatively easy, it can be challenging for some users to know where to start when writing a query. If that feels familiar, this is the right session for you. In this session you will learn how to:

Design a traversal plan with optimal...

GSQL SCHEMA DESIGN & QUERY WRITING BEST PRACTICES: Part 1: Schema Design Best Practices

A good graph schema design represents important relationships in a natural way, while also minimizing system resource consumption and enabling the best query performance. In this session, you will learn:

-What to think about when defining a graph schema -How to define a schema that can make your query writing easy -How to define a schema that...

Best Practices (Design, Schema, Query)

GSQL is a user-friendly, highly expressive, and Turing-complete graph query language. Although learning GSQL is relatively easy, it can be challenging for some users to know where to start when writing a query. If that feels familiar, this right session for you. In this session we will learn: -Design a traversal plan with optimal complexity -Make...

PartnerGraph Webinar - Eden Smith - Improving Data Science Skills and Training with Graph Analytics

Data science is a complex discipline and requires a broad set of skills. Data scientists need to be familiar with a broad variety of analytical methodologies, be fluent with statistical modeling, be able to program in different languages, and much more. Data science, moreover, is an evolving discipline and change is a given.

In this webinar hear...

Graph Gurus 50: Building a Comprehensive Data Lineage Solution with a Graph Database

Data lineage discovers the movement of data from its source to destination via various changes and hops along its way. A graph database is an ideal way to analyze and represent data lineage because it models the flow better than other approaches - relationships can be traversed with ease and a graph schema evolved to accommodate new data and...

EINE EINFÜHRUNG IN TIGERGRAPH

VERBESSERN SIE IHRE ANALYTISCHEN ERGEBNISSE MIT EINER GRAPH-BASIERENDEN ANALYSE PLATTFORM

In diesem Webinar lernen Sie:

-mehr über die sieben wichtigsten daten-wissenschaftliche Funktionen, die durch Graph Analytics ermöglicht werden -mehr über Anwendungsfälle wie Customer 360, Entity Resolution, Betrugserkennung, maschinelles Lernen und...

TigerGraph Testimonial - Yuli Ye, Wish.com

Yuli Ye, Head of Machine Learning at mobile commerce platform Wish.com, describes why TigerGraph (GraphSQL) is a fantastic technology due to a combination of speed, scale and the ability to do relationship based modeling. TigerGraph is the world’s first Real-Time Graph Analytics Platform powered by Native Parallel Graph (NPG) technology....

BOOK