October 2014 Summaries

The Neo4j Graphies recognize and celebrate innovative solutions to challenges related to connected data. The CEO of Neo Technology, Emil Eifrem, acknowledges the outstanding work being done by the Neo4j community members. The Graphies provide an opportunity for future applications and projects to be explored and encouraged. FiftyThree won awards for Best Mobile Graph App and Download My Ebook won Best Master Data Management App, while UBS took home Best Identity and Access Management App, and FiftyThree also won Best Supply Chain Graph App.

The event was the GraphConnect conference, a gathering of professionals in the field of graph databases, where attendees shared their experiences and learned about new developments in the industry. The conference featured various talks on innovative applications of graph databases, including those from notable companies such as eBay and Pitney Bowes. Notable awards were given to individuals who made significant contributions to the community, with one winner being a team representing the open-source project Alchemy.js. The event also provided opportunities for attendees to network and learn from diverse professionals in the field, resulting in a sense of inspiration and motivation among participants.

Mix, a social collaboration platform from the makers of Paper, is coming to GraphConnect 2014 with full force, allowing users to share and remix their creations using a backend powered by Neo4j. The conference will feature interactive sketch-noting throughout, where attendees can use their iPads to remix designs or create new ones, with the most favored remix winning a free Pencil from FiftyThree. Aseem Kishore, engineer at FiftyThree, will explain the backend of Mix and share lessons learned during his keynote speech at 2:00 PM.

GraphConnect is a conference focused on graph databases and applications, taking place soon with limited registration spots available. The transformative power of the Graph has led to disruptions in various industries, and organizations are using graph databases to power new products, services, and upgrades to existing business applications. This year's conference features luminaries as speakers and panelists from startups and Fortune 500 companies, offering a unique opportunity for networking with practitioners, visionaries, analysts, and the press. The event also includes a Neo4j learning track, providing a one-day kick-start to graph database implementation, and is held at the iconic SFJAZZ Center in San Francisco.

Pieter Cailliau, a software engineer at TomTom, will be speaking at GraphConnect 2014 SF about how the company uses Neo4j to power their map quality assurance testing and troubleshoot geospatial logistical issues.

You can use Neo4j's Batch Inserter API to efficiently create nodes and relationships from CSV data, even with large datasets. The process involves creating a batch-inserter instance, reading the CSV file, and using it to create nodes and relationships according to specific requirements such as not indexing properties that are only needed for connecting data, creating schema indexes, skipping certain columns, renaming properties, and converting column values into Neo4j types. To ensure efficient processing, it's essential to shut down the batch-inserter instance at the end of the process. The example code demonstrates how to use the Batch Inserter API with Groovy, handling cases where authors need to be created only once, even if they appear on multiple lines in the CSV data.

Graph modelling in relational databases shares similarities with graph modelling, where the process of deriving a model is similar but implementation details are often blurred. A conceptual model maps closely to a graph model, with entities mapped to nodes/labels, attributes to properties, relationships to relationships, and identifiers to unique constraints. The example provided shows how foreign keys replace relationship types in a relational database, whereas in a graph model, the relationships would be maintained closer to the conceptual level. The author is exploring data modelling further, looking into normal forms and data redundancy in graphs, and recommends learning about graph databases with O'Reilly's free ebook.

The concept of Master Data Management (MDM) is evolving from a traditional system-based approach to a more intuitive, analytic, and intelligent view by leveraging graph databases. This shift in mindset enables MDM to sit between systems of record and systems of engagement, providing a hub for context in customer experience. By analyzing metadata from various sources, MDM can translate and evolve dynamically the full fidelity of customer identity through interactions, potentially leading to thousands of customer markers that define identifies. Graph databases offer dimensionality beyond relational database repositories, requiring little to no translation of how we view people based on data, providing a more semantic - human-centric approach. Innovative companies are adopting graph-based MDM solutions, such as Pitney Bowes Spectrum MDM, and leveraging tools like Neo Technology and Global IDs for data profiling and discovery. However, challenges persist, including scalability limitations, the need for semantic and graph skills, and the development of in-Graph MDM tools.

GraphConnect 2014 is a conference that focuses on the rapidly growing world of graph databases and applications, where three graph visualization partners will be presenting to highlight the nuances between each visualization method. Cambridge Intelligence has released KeyLines 2.0, which introduces the Time Bar for an unprecedented look at data changes over time, while GraphAlchemist showcases their newest version of Alchemy.js. Tom Sawyer Perspectives offers enterprise-class data relationship visualization and analysis, enabling teams to quickly develop production-quality applications. Linkurious provides unparalleled access to Neo4j data insights with its web-based application, allowing users to search and edit the graph. The conference aims to bring together over 700 graph experts and enthusiasts in San Francisco on October 22 to explore how graphs power business.

Swig is a mobile app that allows users to explore new drinks, share them with others, earn rewards, and gameify their experiences. The app's team consists of two people, the sole engineer and his partner, who initially used Ruby on Rails and Postgres for hosting, but later switched to MongoDB due to its flexibility and schemaless design, which allowed for faster development and integration with Rails. However, as the user base grew, performance issues arose, and the team had to denormalize their data and use Redis for caching, leading to increased complexity and maintenance costs. To mitigate these issues, the team switched to Neo4j, a schemaless graph database that provided flexibility, ease of querying complex relationships, and a simpler persistence layer, resulting in a reduced codebase and improved performance.

The author of the text, Mark Needham, conducted an experiment to compare the performance of different approaches when querying a Neo4j graph database. He created four databases with one node having 60,000 outgoing relationships, and then modeled the 'relationship' in four different ways: using a specific relationship type, using a generic relationship type and then filtering by end node label, using a generic relationship type and then filtering by relationship property, and using a generic relationship type and then filtering by end node property. The author measured how long it took to retrieve the 'has address' relationships in each approach, and found that using a specific relationship type was significantly faster than the other approaches. This is because using a specific relationship type only loads the necessary data, whereas the other approaches load more data before filtering it out. The performance differences were observed through profiling of the equivalent Cypher queries, which showed that the generic relationship type and end node label approach loaded 70,000 nodes, while the generic relationship type and relationship property approach loaded 120,000 nodes.

The Graph Visualization Twitter Contest was a contest where participants were encouraged to submit their graph visualizations on Twitter, with the goal of showcasing creativity and innovation in graph visualization. The winners of the contest were Aru Sahni, Peterson Junior, and John Swain, who each received a free pass to GraphConnect 2014 SF, an iPad Air, and a pencil made by FiftyThree. GraphConnect is a conference focused on graph databases and applications, where attendees can learn from hot startups and Global 2000 companies about how they use Neo4j to power their businesses. The conference aims to discuss best practices and lessons learned in the field of graph databases and applications. Additionally, participants can download a free copy of O'Reilly's Graph Databases ebook to discover how to use graph technologies for their application.

Neo4j, a graph database, has been featured in various articles and blog posts discussing its applications, development, and performance optimization techniques. Topics include deep learning sentiment analysis, detecting immutable objects, iOS integration, generic relationship names, graph visualization tools, uploading data from Last.fm to Neo4j, new versions of the Neo4j.rb driver, tracking user paths in IVR systems, and relationships in the Middle East. Additionally, video presentations showcase hands-on development with Neo4j, exploring its capabilities through various examples and use cases. The resource also provides a free copy of O'Reilly's Graph Databases ebook for those interested in learning more about graph databases and their applications.

Graph databases are becoming increasingly important in marketing as they allow companies to store and access data in a more connected and meaningful way, enabling marketers to ask better questions and generate more valuable insights. By leveraging graph databases, marketers can identify complex relationships within their customer data and create personalized recommendations, drive loyalty by offering products and services that customers want, and provide quicker customer service through the identification of closest product matches and quick issue resolution.

GraphConnect 2014 is a conference focused on graph databases, covering various aspects of the field. The event features talks and presentations from Neo4j customers such as UBS, Elementum, and Polyvore, as well as visualization tools like Linkurious and Tom Sawyer, and experts like Ian Robinson and Jim Webber. Sessions include discussions on scaling up and out with Neo4j, same-day delivery using eBay, the business graph with CrunchBase, next-gen master data management with Pitney Bowes, and supply chain management with Elementum. The conference aims to help attendees learn best practices and lessons learned in using graph technologies for their applications.

The speaker presented a talk at the Brussels Data Science meetup about how graph databases like Neo4j can contribute to HR Analytics. They emphasized that HR functions could benefit from understanding information flow in their organization through social network analysis, which can be integrated into recruitment processes and competence management. Graph databases can help with complex pattern matches, pathfinding queries, and graph metrics such as degree centrality and pagerank. The speaker provided examples of these queries using Neo4j cypher syntax and demonstrated how they can be applied to HR Analytics, including a sample dataset and a short movie about it.