Kineviz

Hanging out at Data Day Texas, Amy Hodler and Weidong Yang geek out on the origin of GraphGeeks - a growing, close-knit community holding discussions on data modeling, graph machine learning, and knowledge graphs. In this interview by Neo4j, they also dive into their latest interests when it comes to graph-powered LLM workflows, causal graphs, interoperability between different graph models, and much more. Watch here: https://lnkd.in/ezJMNVSz

How can you gain a clear, shared view of what's happening across your supply chain? We show you how to map a sample supply chain dataset with PuppyGraph and use #GraphXR to visualize the intermediary connections—such as customers, locations, and product orders—between two factories. What other insights does visualization help you uncover by drilling down through connected big data? And how does Puppygraph make it easier to query large relational data? Learn more today: https://lnkd.in/eBgfj-u5  #SupplyChain #Visualization #GraphAnalytics

Exploring supply chain data just got easier. PuppyGraph’s high-performance query engine transforms relational data into a graph in under 10 minutes—no need for a graph database. When combined with #GraphXR’s advanced visualization and analytics, this powerful collaboration unlocks rapid insights, enabling faster decision-making and deeper exploration of your data. Learn more in our blog: https://lnkd.in/eBgfj-u5 #SupplyChain #Manufacturing #GraphData #DataAnalysis #VisualInsights #DataProducts

Exciting news: Google Cloud’s Spanner Graph is now available, and we’re thrilled to be an official visualization partner! Our #GraphXR platform now integrates with Spanner Graph’s globally scalable database, giving organizations the power to explore big data and make more informed decisions, faster. With improved search and built-in AI features, Spanner Graph can transform how businesses leverage connected data—whether in financial investing, fraud detection, or customer 360. Head to their blog to see what’s possible and get hands-on with their sample applications today: https://lnkd.in/eWJcb5kD  #googlecloud #googlecloudpartners #graph #spanner #graphrag #graphanalytics #datavisualization

Data Day Texas 2025 sparked countless great conversations, with Data Discussions on the second-day being a particular highlight. ✨ David Hughes session on hyperdimensional computing (HDC) and neuromorphic cognitive computing left us scratching our heads in the best way. He charged into the intersection of AI and neuroscience with a talk about how brain-inspired architectures can transform data representation and graph-based analytics. Vaibhav Gupta made an inspiring deep dive into #BAML that showed how GenAI can fuel lighting speed product development. It was also a real treat to reconnect with Amy Hodler, Michelle Yi, and the GraphGeeks community in person. Heartfelt thanks to the AT&T Hotel and Conference Center staff for their warm hospitality and delicious food, who made everyone feel right at home, and of course, shoutout to Lynn Bender and Alex Law for orchestrating such a fantastic event. Data Day Texas never fails to impress!

I fully support the comments that Jackie O'Dowd has made on the excellent work being undertaken by the Kwinana Industries Council (KIC). This model was the result of many discussions with Stephen McGurk at Circular Ecosystems and I hope highlights the power of data visualisation in conveying the complex network of material interchanges that were taking place.

Graph BI with Weidong Yang at Data Day Texas. Combining graph, GenAI and BI to next gen analytics, obviously a topic close to my heart. What wisdom did he share? - Tabular data and graph data are two sides of the same coin. It’s the same thing represented differently. - Weidong draws an analogy between this topic and the time vs frequency domain of music. Two ways to represent the same thing. Great stuff. - Graph is just a more efficient way to represent relationships than tables. - For attributes with very few variables graph is less efficient, but as the number of unique values grows the value of graph grows. - Graph never took off as expected until AI came out, because AI can interpret unstructured data and can interpret knowledge graphs efficiently. - Making Hegel jokes is a sure fire way to my heart 🔥 - Roping in Aristotle and The Dao too. ‘If nothing can be defined why bother?’ - Knowledge graph in great when you can define things precisely but it’s hard to define things precisely. - Knowledge map attempts to better capture the imprecise nature of our knowledge, and can be translated to knowledge graph. - Many types of graph are necessary to accurately map reality for AI. - Larger context windows for LLMs are good but they don’t help with signal to noise. Stuffing more stuff in doesn’t help. Think better not more. - Graph BI will unlock analytics over both structured and unstructured data at once, and enable real search for data. This was a super interesting presentation with a ton of huge ideas, really really interesting stuff. Weidong is a real expert in this field. -

We're thrilled to connect at Data Day Texas this weekend! Check out this incredible line-up of talks and see you soon. 👇👇👇

See how to analyze your graphs with Kineviz and Spanner Graph: https://lnkd.in/gi7B-xH4 The integration brings humans into the loop by providing powerful no-code tools for real-time data visualization and communication. To get started, visit: https://lnkd.in/ge3PG2Qm Great partnership Weidong Yang, Sony Green!

Harnessing Big Data for Real-Time Threat Detection When an online gaming platform needed to analyze a massive 40 million events per day, standard BI tools were overwhelmed—missing subtle signs of collusion and fraud. By integrating a real-time detection system with advanced big data analytics, they were able to quickly identify evolving threats and take action before it was too late. Read the case study to learn how advanced analytics and proactive detection helped this platform protect its players—and its bottom line. https://lnkd.in/euuKXfES #BigData #DataAnalytics #RealTimeDetection #GraphAnalytics #FraudPrevention #Gaming