August 2014 Summaries

Graph databases have the potential to revolutionize the recruitment industry by providing a more efficient and effective way of managing and analyzing large amounts of data, including candidate information and relationships. Traditional relational databases are not designed to show relationships and patterns between records, making it difficult for recruiters to identify top candidates. Graph databases, on the other hand, can track relationships and perform tasks that were previously impossible with older tech. By creating comprehensive graph databases from existing data sets, recruitment sites can quickly understand and classify candidates based on their connections, skills, interests, and background. This approach allows recruiters to find better matches for roles and increases the likelihood of happy candidates, ultimately making the industry more effective at identifying top talent.

Our community is actively creating and sharing valuable content through the GraphGist function, a great way to learn about cypher, data models, and Neo4j. The platform allows users to share their visualizations of graph queries, with some standout examples being featured as "GraphGist of the Week". Users can get started by following provided resources, submitting their work to Twitter contests for prizes, or learning more through free ebooks like O'Reilly's Graph Databases guide.

The text discusses the application of graph databases in analyzing data from a science fiction show, Doctor Who. The database contains information on characters, locations, and connections between them, making it suitable for graph-based analysis. By examining the relationships between characters and enemies, the authors found interesting insights such as the Master being the biggest thorn in the Doctor's side with 33 appearances and nine incarnations. Graph databases also have a significant impact on businesses by enabling new kinds of applications and providing unique insights from established data-sets, particularly in areas like route optimization and customer relationships. Companies like Shutl are using graph databases to improve their operations, such as determining the quickest possible delivery routes, which can save time and provide better customer experiences. Graph databases offer a scalable alternative to conventional relational databases, allowing for faster performance and more efficient analysis of complex data-sets.

Aseem Kishore, co-founder of a social network and recommendation website, chose Neo4j as the technology to power his startup, Thingdom. He shared lessons learned from using Neo4j at both Thingdom and FiftyThree in a video from GraphConnect 2013. The conference, focused on graph databases and applications, brings together over 700 attendees to share experiences and hear stories of startups using graph databases. Aseem's experience highlights best practices for startups using graph databases, making the technology accessible to those looking to improve their data modeling skills.

Graph databases, such as Neo4j, play a crucial role in various applications at Gamesys, including mapping social relationships and detecting fraud. The company began using Neo4j to build a friend-of-friend referral rewards system, which helped them track fraudulent activity. They also used it to analyze quests and battles in a game centered around a fictional economy, optimizing the game's difficulty levels. This approach allowed engineers to identify and address issues more efficiently, reducing the time and effort required to balance game content.

GraphAlchemist, a Neo Technology partner providing data science and visualization services, is sponsoring GraphConnect 2014 SF to demonstrate its latest Alchemy.js release. The new features include edge captions, node and edge editing interfaces, API for exporting and importing edited data, directed edges, curved edges, and CDNs for easy setup. These enhancements improve the usability of Alchemy.js, a graph visualization tool, allowing developers to work with graphs more efficiently. GraphConnect 2014 SF is an event where attendees can learn about graph databases and discover how to use graph technologies in their applications. By attending this event, developers can gain insights into the latest advancements in graph databases and network science.

Today marks the 100th anniversary of World War I, a pivotal event in modern history that has had a profound impact on global politics and international relations. The Correlates of War website provides a structured dataset of wars and disputes since the early 1800s, which can be analyzed using graph models like Neo4j. By importing this data into Neo4j, we can create a visual representation of war patterns, including country metadata such as economic and military capabilities, outcomes, settlements, and fatalities levels. The WarGraph model allows us to query the dataset for various insights, including countries involved in the most disputes, disputes per capita, and relationships between countries. By exploring these queries, we gain a deeper understanding of the complex dynamics driving global conflicts.

The Neo4j company launched a Twitter contest called "Show Me Your Graph" in preparation for the GraphConnect conference in San Francisco. The contest encouraged users to share their graph visualizations, which were created using various tools and technologies. Examples of submitted graphs include a 3D visualization of a pattern recognition algorithm training into a massive binary decision tree, a social graph of the OSCON Twitter feed rendered by vivagraph, and a Marvel Universe graph. The contest aimed to showcase the versatility and creativity of graph visualizations in data representation and exploration.

The articles and blog posts section features a diverse range of topics related to graph databases, including Cypher, Neo4j, and graph modeling. The GraphGists and GitHub section showcases various projects and repositories on these platforms, while the Videos and Presentations section offers tutorials and talks on working with graph databases using different programming languages. Additionally, there is an awards section highlighting notable achievements in the adoption of Neo4j technology, including a 2014 award for a public transportation project in Manchester.

The banking and finance sector can learn from the online dating industry, particularly in using graph databases to model social relationships and detect fraud. Graph databases are better at identifying connections between multiple data points than relational databases, making them ideal for analyzing complex data such as those involved in financial transactions. By applying social network analysis, financial institutions can identify potential fraud rings and flag advanced scenarios in real-time, saving time and money while offering a competitive advantage. The same graph database technology used to find matches on dating sites can also be applied to other business applications, such as recommendation engines and customer relationship management tools, providing a unique ability to discover new patterns within complex data volumes.