The great thing about running the Neo4j blog is that there is NO lack of things to talk about. The world of graphs is a treasure trove of use cases, announcements, bona fide news items, community graph hacks, smart partner solutions and invaluable tips and tricks (and on and on).
As always, it was really difficult to select only a handful of blogs from 2020. Everyone who contributed to the blog this past year deserves a big round of applause!
And with that, here’s the best 11 Neo4j blogs of this past year.
#1. Announcing New Neo4j Online Training Courses!
Learning to use graph technology is always an exciting journey. This year, Neo4j launched 3 new online training courses in GraphAcademy: Introduction to Neo4j 4.0, Graph Data Modeling for Neo4j and Basic Neo4j 4.0 Administration. From the basics of graph databases to data modeling to using Neo4j 4.x in production, these courses teach you the essentials of graph technology and are the perfect place to start your graph journey.
#2. Analyzing the FinCEN Files with Neo4j
The International Consortium of Investigative Journalists (ICIJ) strikes again! At the tail end of September, they dropped the FinCEN Files, a global investigation that exposed a vast network of industrial-scale money laundering running through Western banks and generally ignored by U.S. regulators. And as with the Panama Papers and the Paradise Papers (and others), they used Neo4j as a tool to help crack the case wide open. In a word: badass.
#3. Introducing Neo4j Graph Database 4.0 [GA Release]
We’ll just let Jim Webber say it in his words: “I’ve been with the Neo4j codebase since 2009 and have to tell you: 2009 Jim Webber couldn’t imagine the way 2020 Neo4j would look. “2009 me” was building a REST API (if you’ve ever seen such a thing) so that the database could become a server. Now I look at 2020 Neo4j, and it’s an incredible leap forward that is astonishing to me.
“Neo4j 4.0 is the culmination of more than a year’s worth of our work, from the biggest engineering team ever invested in graph technology. To put that in more developer-friendly terms, we’ve invested around a century’s worth of human effort into this release.”
#4. Graphs and the Strategic Response Efforts to COVID-19
Without a doubt, COVID-19 crowns the news stories of 2020. In our battle against the pandemic, graph technology is the power we need to get an edge on the virus. With a network structure, graphs are the natural way to not only trace the connections between people but also understand the relationships between genes and identify existing drugs that would be beneficial.
#5. Pokégraph: Gotta Graph ‘Em All!
Whether you watch the TV show or play the games, Pokémon is something you can’t resist. In this blog post, Joe Depeau shows you how to model your Pokégraph in Neo4j, and analyze and relate all different aspects of a Pokemon to another, including their Generations, Abilities, Types and Moves. Start graphing ’em all!
#6. Knowledge Graphs & Navigating the Future of AI: An Interview with Charlie Beveridge of Accenture
Knowledge graphs are the essential part of living in the big data era. In this 5-minute interview, Charlie Beveridge, Senior Consulting Manager at Accenture, describes the future of knowledge graphs and artificial intelligence. “In a sentence, graphs are doing for AI what electricity did for the world,” he says.
#7. Machine Learning Algorithms
This blog performed really well this year, and that’s likely because Lauren Shin starts by explaining the concept of machine learning, the differences between human and machine learning (through the lens of the classic iris classification data set) and three approaches to better data analysis through machine learning with the wonderful world of graphs. ML and graphs remain (and will remain) an exciting topic, as an intelligent tool that helps us make insights we otherwise wouldn’t be able to.
#8. Building the Enterprise Knowledge Graph
Enterprises today need to leverage the power of knowledge graphs coupled with AI/ML-based predictive capabilities to retain and reuse information efficiently. Henry Ball, Solutions Engineer at Neo4j, walks you through building a knowledge graph for your enterprise from the beginning to the end with a demo.
#9. Lean Graph Data Models Drive Fast Innovation: A Fireside Chat with David Fox, Senior Software Engineer at Adobe
This in-depth interview with David Fox focuses on how he discovered Neo4j, and made a graph use case for fixing the scaling and performance issues of Adobe’s activity feed called Behance. Over the years, Fox has watched his colleagues find new use case implementations for a graph database to drive innovation, build better infrastructure and, in the end, provide notable cost savings. In this interview, you’ll see how graph use cases kept naturally surfacing, how surprisingly lean their graph database models could be, and what development and implementation was like throughout.
#10. Financial Fraud Detection with Graph Data Science: Analytics and Feature Engineering
2020 is the year the term “graph data science” took a strong foothold in the graph community. In this blog, Amy Hodler, Neo4j’s Graph Analytics & AI Program Director, takes a look at the true power of graph data science to increase accuracy and viability of fraud detection methods.
#11. GraphConnect 2020 Agenda: Everything You Need to Know
Sooo… the GraphConnect we were planning for 2020 was set to be the biggest and best Neo4j event yet! That was, until about March 11th when the World Health Organization announced COVID-19 was a global pandemic and we had to cancel the event. 🙁 Stay safe and healthy, y’all! And here’s to meeting again at a future GraphConnect!