On-Demand Webinars
Neue Lösungen für Life Sciences und die Pharmaindustrie mit Graphdatenbanken
In diesem Webinar wollen wir die Grundlagen der Neo4j Graph-Plattform erklären und auf einige ausgewählte Anwendungsfälle eingehen. Dabei soll der Folus insbesondere auf den Herausforderungen in der Pharma- oder Chemiebranche als auch in Life Sciences Unternehmen liegen und es wird aufgezeigt, wie diese mit Graphdatenbanken gelöst werden können. Neben diesem allgemeinen Überblick stellen wir auch einige auswählte Anwendunsgfälle von Kunden (wie z.B. dem Deutschen Zentrum für Diabetesforschung) vor.
Maintaining your Data Lineage in a Graph
Lju Lazarevic, Neo4j Data lineage is an important component in many projects, including master data management, customer journey tracking, and regulatory compliance. It also presents many challenges in its implementation. In this webinar we will explore how and why Neo4j is a natural fit for your data lineage challenges. #DataLineage #GraphDatabase #MDM
Future-Proof Your Risk Management and Compliance with Graph Technology
Nav Mathur, Senior Director - Global Solutions - Neo4j In the aftermath of the Lehman crisis of 2008, financial services firms face a number of new regulations and risk management challenges. One key regulation is the Fundamental Review of the Trading Book (FRTB), which is part of the upcoming Basel IV set of reforms. The new regulations require banks to reserve sufficient capital to maintain solvency through market downturns and avoid the need for government bailouts. However, in this challenge lies an opportunity
POLE Investigations with Neo4j
The POLE data model - Person, Object, Location, Event - is commonly applied to security and investigative use cases such as policing, anti-terrorism, border control, and social services. It’s also a great fit for the graph and graph algorithms. Joe Depeau demonstrates how Neo4j, graph algorithms, and the POLE data model can support police and social services investigations and generate real-time insights using the Neo4j browser as well as some sample Tableau visualisations.
Graph Solutions for Telecoms
Telecommunications is all about connections. Graph databases are, therefore, an excellent fit for modelling, storing and querying telecommunications data of all kinds. Whether managing increasingly complex network structures, ever-more-diverse product lines and bundles, or customer satisfaction and retention in today’s competitive environments, graph databases enable businesses to become more agile by leveraging their connected data.
Neo4j 3.3 Release
This webinar details the Neo4j 3.3 release. In 3.3 we focused on improving write and import performance in Community Edition, and cluster throughput and security in the Enterprise Edition. The result is that 3.3 writes are more than 50% faster than 3.2 and twice as fast as 3.1 Speaker
Solving GDPR with Neo4j and CluedIn
The most critical step for companies to have a GDPR solution is having all their data connected and available in one place. We take the viewers through how 95% of companies can reach quick and low-cost compliance utilizing the graph as the connection foundation and CluedIn as the data integration platform that automatically gives companies their single point of customer truth.
How to Make your Graph DB Project Successful with Neo4j Services
Neo4j is widely used across many industries to tackle a multitude of modern-day business challenges. From powering Walmart’s retail recommendation system, to detecting fraud at Fortune 500 financial institutions, to optimizing delivery service routing at eBay, the Neo4j team has helped implement projects across a wide spectrum of industries and use-cases. Hear how other top organisations have quickly and successfully launched their graph database projects by leveraging Neo4j Consulting Services and learn more about the different offerings available.
Native vs Non Native Graphs
In this recorded webinar, Dr. Jim Webber, Chief Scientist at Neo4j, surveys some of the non-native graph approaches on the market today and shows where they fall short of the native graph approach of Neo4j in terms of efficiency, performance, safety and agility.
