Revolutionize your sales and operations planning. Find what matters in your data, align stakeholders, explore issues and proactively what-if alternatives.
Building data products in your organization to realize data science ROI and never before seen data insights.
Tuning JanusGraph is not for the faint of heart, read these tips and tricks to help you get the most out of your JanusGraph project.
Data products are the deployed scalable, reproducible outcomes from a data science initiative. Realize ROI from data science and deliver value to end-users.
Utilizing real time optimization with an event streaming platform.
A native parallel graph enables manufacturers to identify and manage product delays, shipment status, and other quality control and risk issues, at massive scale in real-time.
Use Machine Learning to increase volume, maintain profits and meet the needs of customers while maintaining a simple business policy.
Combining traditional search techniques with graph algorithms to efficiently find subgroups within data.
Avoid bugs & gain confidence when refactoring code by writing tests for your React code using Jest, React Testing Library & a Test Driven Development approach.
What makes Svelte a different UI framework and why you should give it a try.
Predict, identify, and intervene using graph technology and Moove.ai Machine Learning Analytics.
Fault tolerant and durable data transmission plus system integration sourcing data for graph analysis.
Understand the differences between supply chain visibility, traceability, and transparency.
Automating multifaceted, complex workflows requires hybrid solutions like streaming analytics of IoT data, batch analytics like machine learning solutions, and real-time visualizations.
15 Minute Lightning Talks + Q&A. Powerful Data, Storage & Search & Graph Technology in 1 platform - Cassandra.
Learn more about JanusGraph and its capabilities in this online meetup.
The three types of graph machine learning (graphML) are smart data extraction, data structure analysis, and full graphML. This article explains all three.
Do all of your users speak the same language? If so, are you simply ignoring or preventing users that speak different languages?
Learn how Graph Technology can help to identify risk and fraud patterns in order to quickly respond to threats and anomalies. Many new fraud rings use sophisticated measures for credit card and other methods of fraud. Utilizing Graph and ML will allow you to see beyond individual data points and uncover difficult-to-detect patterns. Join us to learn how to maximize time and resources with Graph vs. traditional relational database platforms. Predict, Identify, and Intervene Fraud with Graph & ML Analytics.
A machine learning system tells heated stories about commercial real estate auctions it watches, encouraging customer reengagement and new customer acquisition.
Join Scylla and Expero to learn how to use JanusGraph and Scylla to architect a corporate compliance platform.
Supporting multiple languages is about more than just translating some text.
Avoid bugs and gain confidence when refactoring code by writing tests for React code using Jest, React Testing Library and a Test Driven Development approach.
Learn how Graph & Machine Learning Technology will increase customer loyalty, identify and resolve customer issues and provide strategic up-selling capabilities. Expero will demonstrate how visualizing customer journeys can provide your users with meaningful interactions and increase overall customer satisfaction. Join us to learn how to maximize resources with Graph and finally get an all encompassing view of your customer.
A sequel to “Bush Pilots in the Outback”, we explore using reinforcement learning to schedule thousands at scale.
Cut Costs & Manage Entitlements with Graph Technology & ML Analytics.
Cut Costs & Optimize Revenue with Supply Chain Technology.
Learn why a graph database is ideally suited for managing, enforcing and navigating the rich semantic relationships required for Authorization Master Data.
Learn how to protect your resources by setting up serverless authentication with Auth0 and AWS Lambda@Edge.
Don’t guess how much your future spend on infrastructure will be! Load test to find out for sure.
Trading Alternative Investments using Connected Data & Machine Learning
Understand the differences between supply chain visibility, traceability, and transparency. Learn what graph is and how it can create a unified view across digital and physical supply chain processes, yielding more prescriptive supply chain decision making. Use Graph + ML to improve demand forecasting and production planning, while reducing inventory and operating costs. Focus areas include, inventory, routing, predictive analytics, device & fleet management, materials, and more.
Expressive Data Models with JanusGraph - High Performance JanusGraph Data Load
Learn how you can build a flexible data ingestion pipeline to handle highly varying data sources into your distributed NoSQL ecosystem.
Structured Finance investors often miss opportunities to maximize portfolios due to a lack of state of the art tools and processes.
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Using recurrent neural networks, we predict the spread of illness in the United States.
Have you ever stopped to understand what graph databases are and what they can do for you? Graph databases and graph processing frameworks are all the hype in the NoSQL world at the moment. The ecosystem is constantly evolving and different datastores of processing frameworks are coming out what seems like weekly. The truth is that graph databases are a great way to solve certain application problems in areas such as personalization and recommendation, logistics, master data management, social networks, fraud or IoT but many people are completely lost when they step foot into the exosystem. In this session we will help you make sense of the graph ecosystem with an examination of a variety of graph datastores (e.g. Neo4j, DSE Graph, Titan, OrientDB, etc.) and graph processing frameworks (e.g. Giraph, GraphX, Elasticsearch Graph, GraphQL, Pregel, etc.). We will then discussing how you might use these technologies to augment or replace complex portions of your applications. In the end you will walk away with a better appreciation for the practical aspects of the graph ecosystem and you might even find out how to remove that complex recursive SQL CTE that gives you nightmares.
Wireframes call out key moments in design in order to clarify how something should look, feel, and function.
Use graph and machine learning to optimize routing, inventory, predictive analytics, and fleet management of your supply chain while cutting costs and making your dollar go further.
As of late Q2 of 2018, there’s a new entry into the graph database marketplace, Amazon Neptune.
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One of Expero’s fraud detection techniques applied to the false prescription of opioids in clinical settings.
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Learn how Google Cloud Bigtable, Pub/Sub, and BigQuery with JanusGraph can help to identify risk and fraud patterns in order to quickly respond. Many new fraud rings use sophisticated measures for credit card and other methods of fraud. Utilizing Google Cloud Platform products and services with JanusGraph will allow you to see beyond individual data points and uncover difficult-to-detect patterns. Join us to learn how to maximize time and resources with Graph.
Learn how Google Cloud Bigtable, Pub/Sub, and BigQuery with JanusGraph will increase customer loyalty, identify and resolve customer issues and provide strategic up-selling capabilities. Utilizing Google Cloud Platform products and services with JanusGraph will allow you to visualize the customer journey, increasing customer satisfaction by providing meaningful interactions. Watch to learn how to maximize resources with Graph and finally get an all encompassing view of your customer.
A sneak peak of this year's Graph Day SF talk on ACID.
Accelerating IoT, Finserv, and Supply Chains with JanusGraph and Cloud Bigtable
The graph database space is rapidly expanding as more and more companies identify potential use cases that require the traversal of highly connected data sets.
Data Management for Oil and Gas - Predictive Maintenance Intelligence
Data Management for Oil and Gas using IOT and Machine Learning for Asset Management
Use Graph Technology and Machine Learning to finally get a usable all encompassing view of your customers to stop churn and drive revenue.
Use Machine Learning and Graph to Stop Fraud Before it Happens
Don't be in the dark when the next natural disaster happens. Visualize your data with real-time supply-chain mapping powered by Graph Technology.
Speed up your JanusGraph queries with these tuning tips and the new CQL storage adapter.
Discover why an Angular programmer would use Vue over Angular any day of the week.
Use Keylines to increase customer loyalty from within your graph database.
Don't be in the dark when the next natural disaster happens. Visualize your data with real-time supply-chain mapping powered by Graph Technology.
See how Reinforcement Learning can be used to optimize pickup and delivery schedules in an unpredictable environment.
Lock Down Funding for Intelligent, Graph-Enhanced Fraud Solutions
Find dissatisfied customer cohorts and evaluate intervention measures using graph machine learning.
A practical guide on some of the main players in the graph database marketplace.
So many options in fast moving the graph database world, which one should you choose?
Use Machine Learning and Graph to Stop Fraud Before it Starts
How to detect both credit card fraud and money laundering using graph and machine learning.
The property graph database space has been dominated by a handful of names who on balance are not that big in the software marketplace generally speaking.
Leveraging the natural structure of data, graph convolutional networks produce optimal predictions of node properties.
A method of classifying nodes in an information network by application of a non-Euclidean convolutional neural network
Ted Wilmes discusses the state of JanusGraph in the year 2018. Throughout the session he touches on where we are in the world of graph, what is new, and where JanusGraph and Apache Tinkerpop are headed.
Explore your tuning options for increasing JanusGraph write throughput and lowering latencies.
Identify ROI and business case costs at a high level. Increase delivery with real-time impact and transport analysis.Learn how Graph Technology + Machine Learning will improve delivery times, minimize transport risk through data analysis and increase product satisfaction. Use predictive analytics to reduce operational bottle necks and discover areas of concern affecting supply. Using Graph + ML allows you to increase customer satisfaction through visualization of supply and demand impacts.
FBI’s use of machine learning based entity resolution to catch criminals and fraudulent activity.
Increase delivery with real-time impact and transport analysis. Learn how DataStax Graph Technology will improve delivery times, minimize transport risk through data analysis and increase product satisfaction. Use predictive analytics to reduce operational bottle necks and discover areas of concern affecting supply. Using DataStax Graph Technology allows you to increase customer satisfaction through visualization of supply and demand impacts. Don't be in the dark when the next natural disaster happens. Visualize your data with real-time supply-chain mapping powered by DataStax Graph Technology. What You'll Learn Source management -- OptimizationMaterials, transport, regulation/compliance and customer optimizationIssue Resolution and identification -- discuss ROI and time -- Value of supply, manufacturing, transport and end product satisfactionVisualize Part impacts -- Timelines and event correlation. View of customer journey and increasing customer satisfactions.Dependencies and Workarounds - Identify how and where pinch points and concern areas exist with predictive analytics.Scoring and Use of Algorithms - The ability to score and create usable information for executive dashboards from multiple sources. Creation of scorecards and risk calculations for indicating to users what to spend time on and dive in deeper with.
Learn how DataStax Graph Technology can help to identify risk and fraud patterns in order to quickly respond. Many new fraud rings use sophisticated measures for credit card and other methods of fraud. Utilizing DataStax Graph Technology will allow you to see beyond individual data points and uncover difficult-to-detect patterns. Join us to learn how to maximize time and resources with Graph Technology vs. traditional relational database platforms. If there are new ways to commit fraud these days, shouldn't your company have new ways to prevent it? What You'll Learn Detection and anomaly identification - discuss ROI and time: the value of early detection.Progressive Disclosure - The ability to drill in as items are presented as requiring interaction. Create the ability to allow large data viewing without overwhelming users with millions of data points.Scoring and use of algorithms - The ability to score and create usable information from multiple sources. Creation of scorecards and risk calculations for indicating to users what to spend time on and look at more closely.Visual representation of risks, anomalies, hot spots and heat maps and need for human interaction. Creation of easy to identify visual screens and dashboards for key decision makers that allows for real time diagnostics.
Messages coming into your Spark stream processor may not arrive in the order you expect. Learn how to handle the unexpected.
Learn how DataStax Graph Technology will increase customer loyalty, identify and resolve customer issues and provide strategic up-selling capabilities. Utilizing DataStax Graph Technology will allow you to visualize the customer journey increasing customer satisfaction by providing meaningful interactions. Join us to learn how to maximize resources with Graph Technology and finally get an all encompassing view of your customer.
