Discover KronoGraph's interactive timeline visualization
Your World Seen through Your Eyes with Neo4j Bloom – Andreas Kollegger
We’ll take a walking tour of data using Neo4j Bloom, our new graph visualization environment. For company we’ll bring representatives from across the organization, each with different goals in mind but all looking to Neo4j for the information they need. Using natural phrases to describe what we’re looking for, Bloom will search through the graph to show us the relevant parts. From there we’ll dig into the details and explore information patterns to extend from what we know to what we can learn. Andreas Kollegger, Product Manager, Neo4j #DataVisualization #GraphDatabases #GraphConnect
Neo4j Bloom for Project Teams Browser Based and Multi User Enabled
Neo4j Bloom is a graph visualization and exploration product. It offers a code-less search to graph insight experience suitable for end users of a graph-powered application. This enables graph novices and experts, technology and business side to easily collaborate and communicate. In addition, Bloom interprets and runs near natural language queries. Neo4j Bloom 1.1 is the next browser-based version of Bloom. Host it centrally on a server and allow access via a web browser, without the need for a desktop installation. With this update, Bloom makes it easy for project teams to collaborate and communicate using shared views of the same graph. What’s new in version 1.1: Enables Bloom for use by project teams Zero footprint access via modern HTML5 browsers - no local installation necessary Link Bloom to an external application and pass-in context for graph exploration Allow a graph admin to create separate perspectives for different user roles in the team
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 Empfehlungssysteme, die sich ideal für die Graph-Analyse eignen. -wie Unternehmen jeglicher Größe in den Bereichen E-Commerce, Energiemanagement, Finanzdienstleistungen, Gesundheitswesen und anderen Bereichen von der Graphanalyse profitieren
Making Advanced Analytics Better With Graph: An Introduction To TigerGraph (EMEA) - May 2020
Gartner Research has identified graph analytics as a key technology in its Top 10 Data and Analytics Technology Trends That Will Change Your Business report. By organising data in a graph format, graph databases overcome the big and complex data challenges that other databases, such as relational and NoSQL, cannot. By attending this online event on May 5th you will learn: Seven key data science capabilities which are enabled by graph analytics Use cases, such as customer 360, entity resolution, fraud detection, machine learning, and recommendation systems, that are ideally suited to graph analytics. Companies of all sizes in e-commerce, energy management, financial services, healthcare and others, which are benefiting from graph analytics We will finish with a short demo of TigerGraph.
How the University of Washington uses Neo4j in its MDM solution
Pieter Visser, Solutions Architect at University of Washington, talks about the power of Neo4j in the context of a Master Data Management (MDM) and Data Governance solution. UW is one of the largest public universities in the US, with an annual operating budget exceeding $6B.
Neo4j 4.0: The Next-Generation Graph Database Built for Unlimited Scale and Development Agility
Neo4j 4.0 is the most significant release in the graph technology market to date. Built on Neo4j's proven native foundation, 4.0 delivers key capabilities: unlimited scalability, granular security, operational agility and reactive architecture.