We’ve seen a lot of discussion around common hot topics such as cybercrime, big data, supply chain, and more. However, we’ve also noticed a lot more discussion in emerging areas like cryptocurrency (are you surprised?), digital twin, fraud, and graph data science, with the recent launch of Neo4j Graph Data Science. We took the opportunity to jump in on the ongoing discussions and speak about how graphs fit in and play an important role in supporting each field.
No doubt, there are many great articles, videos, and podcasts that have been published over the last six months, but to give you a taste, let’s take a look at the ones featured below!
Using Graph Technology to Achieve Cryptocurrency Success“The positive experiences of challenger financial institutions, PwC Germany, and other crypto-graph users show the huge potential for graph databases in crypto-finance. Graphs can encode blockchain in ways that make it safer, more transparent, and more monetisable. Whether you’re a brand wanting to offer Bitcoin as a payment mechanism or a fintech looking to enter the cryptocurrency market, now is a great time to investigate how you can do so safely, efficiently and with the ability to scale using graph technology.” Dan McGary, Senior Sales Executive at Neo4j, in a contributed article to Information Age. Read the article.
Knowledge Graphs & Digital Twins: Powerful Ways to Optimize Your Supply Chain“Graph-base digital twin knowledge graphs that bring data together and create a connected virtual supply chain give brands what they really need right now. Brands get a trackable, highly granular picture of all the products, suppliers and facilities in that supply chain, and the relationships between them. Putting a supply chain into a graph gives you real-world fidelity in everything from the oil and gas sector to nationwide retail distribution.” Maya Natarajan, Senior Director of Product Marketing at Neo4j, in a contributed article to IT Supply Chain. Read the article.
How Graph Technologies Can Help Platforms Detect Fraud“Graphs can therefore be effective to track the interconnected nature of fraud, crime, and anomalies. By leveraging connections to detect the undetectable, graph algorithms and graph machine learning enable organizations to stay ahead of new forms of fraud and crime.” Rahul Tenglikar, India Regional Director India at Neo4j, in a contributed article to Tech Circle. Read the article.
Graph Technology: Joining the Dots“Whether it’s in uncovering the connections of Putin and his enablers or helping bolster banks and governments’ security efforts, graphs play an essential role in solving future data and relationship problems at scale. Any money laundering stakeholders serious about automating the fight should be considering how they can start using graphs.” Alicia Frame, Senior Director – Graph Data Science at Neo4j, in a contributed article to Money Laundering Bulletin. Read the article.
Neo4j Drives Simplicity with Graph Data Science Refresh“Knowing how to drive a car is not the same as being a mechanic. Knowing how to do graph data science is not the same as being a DBA. Up until this point, you really did have to know both.” Alicia Frame, Senior Director – Graph Data Science at Neo4j, in an interview with Datanami. Read the article.
Graph Data Science Is Moving One Step Closer to the Mainstream“Graph data science is when you want to answer questions, not just with your data, but with the connections between your data points – that’s the 30-second explanation.” Alicia Frame, Senior Director – Graph Data Science at Neo4j, in a live interview with George Anadiotis in Orchestrate all the Things podcast. Listen to the podcast.
As we settle into our summer holiday plans, I want to take a moment to thank all the incredible journalists and publications for the ongoing collaboration. We wish everyone a relaxing summer holiday season and look forward to building more stories to share throughout the remaining half of 2022!