Graph All The Things! and Visualize Date and Time Data with Graphs

Join us for this exciting session at NoSQL Now! featuring presentations by Neo4j Developer Evangelist Kenny Bastani and Corey Lanum, US Manager for Cambridge Intelligence, creators of the KeyLines visualization software.

Kenny will present an introduction to graph databases and Neo4j followed by Corey presenting KeyLines and the capabilities of Time Bar, KeyLines 2.0's latest feature. Corey will discuss real-world use cases for Time Bar and how Time Bar can interact with other features of KeyLines to make a fully functioning Neo4j visualization application.

Save $300 on NoSQL Now! registration with the code NEO4J or get a free Expo Hall pass with the code DATAVERSITY

NoSQL Now! registration is available here: http://nosql2014.dataversity.net/reg.cfm

AGENDA:

6:30-7:00 - Networking in NoSQL Now! Expo Hall

7:00-7:40 - Graph All The Things!!! with Kenny Bastani

7:40-8:20 - Presentation: Visualize Date and Time Data with Graphs with Corey Lanum

8:20-8:45 - Q&A and more networking

ABSTRACT: Graph All The Things!!!

Hey, so did you know that graph databases are the fastest growing category in databases today? No? Don’t worry, most don’t.

Graph databases have been popularized by leading social web properties like Facebook and LinkedIn. So it’s only natural that most geeks out there equate graphs with social, but that’s only part of the story. Thousands of companies in a wide range of industries have quietly adopted Neo4j across a broad range of business critical uses. Forrester Research now predicts that by 2017, over 25% of enterprises will be using a graph database. So if you haven’t already encountered one, chances are you might soon!

Neo4j is mostly written in Java (some Scala!), but usable across all of the popular languages. This session will introduce fundamental graph database concepts and then dive into a hands-on code-centric introduction to Neo4j. We will cover the declarative query language Cypher (http://www.neo4j.org/learn/cypher), introduce operational concerns such as clustering and horizontal scalability, and describe popular graph database use cases.

You will leave with a solid understanding of graph database fundamentals and an appreciation for when graph databases are a good fit in the real world.

SPEAKER: Kenny Bastani, Developer Evangelist, Neo4j

Kenny Bastani is an accomplished software development consultant and entrepreneur with 10+ years of industry experience as a front-end and back-end engineer. Kenny has demonstrated leadership in designing and developing enterprise-grade web applications for high-volume, high-availability environments, with innovative focuses on solving unsupervised machine learning problems that enable businesses to better manage their institutional memory. As both an entrepreneur and software designer based in the SF Bay Area, Kenny has gained valuable experience leading teams in both product design and software architecture. Tweet Kenny at @kennybastani.

ABSTRACT: Visualize Date and Time Data with Graphs

Many Neo4j users are storing date and time data as properties of their graph elements. This can range from something as simple as the date that the data element was created to the date/time that a financial transaction occurred. Until now, the graph visualization tools were limited in the way they could show patterns in date/time data, often limited to reading the date/time like any other property. With the recent release of KeyLines 2.0 from Cambridge Intelligence and the introduction of the time bar element, application designers can display patterns across time in your graph data, from decades down to seconds.

SPEAKER: Corey Lanum, US Manager for Cambridge Intelligence,

Corey has managed the technical and business relationships with dozens of the largest defense and intelligence agencies in North America, in addition to working with many security and anti-fraud organizations in private industry. With 14 years of data visualization and data analytics experience, Corey has a diverse background working on big data initiatives and implementing proven solutions that provide customers with key insights into their data.