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Supply chain superheroes manage disruption and manufacture products cheaper and faster. This crisis has shown us all how fragile the global supply chain actually is and why we need these superheroes more than ever before.

Demonstration of Expero workbench for detecting and investigating fraudulent activity such as AML, credit card transactions and internal threats.

Data Products Strategy and Implementation

Healthcare with Graph and Kafka

How capacity modeling can offer the best protection against erratic market demand

Explore building and connecting applications in Astra Cloud that connect to Cassandra via a sample traditional supply chain application demo that visualizes supply, demand, risk, and more.

Complex Manufacturing & Supply Chain Round Table with TirgerGraph

Financial Services Round Table with TigerGraph

Fist impressions of Astra, the new DBaaS from DataStax.

Data Products: What Product Managers Need to Know about Productizing Data Science

Energy Round Table with TigerGraph

Learn about fighting fraud with Graph and Machine Learning Experts

Learn more about the technology behind Data Products

Netflix open-sourced Metaflow for performing data science and machine learning on cloud providers such as Amazon Web Services (AWS), Microsoft Azure and Google Cloud (GCP) - although optimized for AWS. What features does it provide?

Getting your graph to scale is only half the battle. Learn here how Expero helps businesses understand their data and make real time decisions using custom visualizations and UX.

Advances in automation of data analysis, graph analytics, data lineage, conversational queries and IoT analytics are widely predicted for 2020. Expero has capabilities and assets already in place.

Deep dimensionality exchange is a new deep learning protocol developed at Expero for performing domain transfer between domains of different dimensions.

Natural language processing is a powerful tool in building investigatory user interfaces for data exploration. See how conversation UI can be used to interrogate highly connected data to produce context driven data visualization and analytics.

Learn how Software Craftsmanship powers up Agile methods to move fast in complex projects.

Technology for deploying scalable machine learning-based products otherwise known as data products.

Build a single view of your corporate security model using new capabilities in graph and streaming technology through which you can funnel all your access attempts to critical data.

Building data products in your organization to realize data science ROI and never before seen data insights.

Revolutionize your sales and operations planning. Find what matters in your data, align stakeholders, explore issues and proactively what-if alternatives.

JanusGraph tuning and performance best practices

Data products are productized versions of data science and machine learning initiatives that deliver value to end-users.

Utilizing real time optimization with an event streaming platform.

With Confluent and TigerGraph quickly emerging as high-quality enterprise software, learn how you can take your LDAP data, RBACs, and ACLs and quickly model and mirror them in a graph database using Kafka, a real-time streaming software.

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.

Given a large batch of healthcare data, we efficiently find similar patients to determine what remedies to recommend using traditional search methods and graph algorithms.

Learn how to avoid bugs and gain confidence when refactoring code by writing tests for your React code using Jest, React Testing Library and a Test Driven Development approach.

Join us for this quick deep dive on how machine learning and analytics can be used to get insights into your data & scheduling/managing fleets.

What makes Svelte a different UI framework and why you should give it a try. In this article you will learn the benefits of using Svelte, the new (and different) UI framework, as opposed to others like React, and Vue.

Predict, identify, and intervene using graph technology and Moove.ai Machine Learning Analytics.

See how compiled data sources allow for real-time mapping of road safety and current conditions.

Supply chain planning demo showing real-time visibility into demand and capacity planning.

Supply Chain planning and analytics dashboard showing risk visibility, real-time data and time series.

System Integration sourcing data for Graph Analysis.

Understand the differences between supply chain visibility, traceability, and transparency.

Customer 360 in financial services showing segmentation and churn avoidance, sentiment score, and best next conversation.

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.

Graph machine learning (graphML) is a subset of deep learning with much higher accuracy because big data records are linked together by their relationships.

Globalization (G11n) of an application involves more than just translating text. Internationalization (I18n) is the process of enabling your application to be used in different languages and culture. Localization (L10n) covers the work to provide the application in one specific language and culture. Selected locales can help in providing translated text, but some information needs to be converted (times, dates, currencies).

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. ‍

This demo explores Portfolio Optimization for Alternative Investments

#NLP #MachineLearning #algorithm learns to tell #stories by summarizing #commercial #RealEstate #data, #earning #profits and spurring #CustomerRetention. #BINGO!

Join Scylla and Expero to learn how to use JanusGraph and Scylla to architect a corporate compliance platform.

When localizing an application, treat the capabilities as features. Consider the specific use cases and work with the users to refine the approach. There may be design and layout adjustments needed per language. If the application is a CMS, content as well as application resources may need translations.

Learn how to avoid bugs and gain confidence when refactoring code by writing tests for your React code using Jest, React Testing Library and a Test Driven Development approach.

See why accumulators help TigerGraph’s GSQL query language standout among other native Graph Databases.

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.

Reinforcement Learning at scale; Scheduling thousands of vehicles in multiple environments - how we made it work.

Cut Costs & Manage Entitlements with Graph Technology & ML Analytics.

This demo explores Entitlements & ID Management

Cut Costs & Optimize Revenue with Supply Chain Technology.

This can be like the one sentence description, but the more buzzwords the better. This is what google will pull from when people search.

Learn how to protect your resources by setting up serverless OAuth authentication with Auth0 and AWS Lambda@Edge.

Cassandra, DataStax, ScyllaDB, CosmosDB, RedShift - they all scale horizontally and with you will pay more as you add nodes - even if the SW is free, the compute time is not. Use Gatling to forecast your budget needs so you don’t surprise your CFO.

Watch our online seminar to learn how to unlock patient 360 & prevent opioid fraud with graph & ML technology. We discuss how graph-based Patient 360 breaks silos and enables analytics to discover more efficient operations, better healthcare outcomes, and fraud detection.

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.

15 Minute Lightning Talks + Q&A

Expressive Data Models with JanusGraph - High Performance JanusGraph Data Load

Building a data ingestion pipeline using Spark, Kafka, DataStax, Nifi, and Pentaho.

Structured Finance investors often miss opportunities to maximize portfolios due to a lack of state of the art tools and processes.

Deep learning, specifically recurrent neural networks, forecast nonlinear time series illness signals.

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.

Using unsupervised machine learning, we relate documents together based on their content. This analysis operates directly on the text in the documents, building up clusters of similar context so that an analyst, or another algorithm, can investigate all of their company's data on a single subject.

Wireframes are intended to call out key moments and interactions in software design in order to provide clarity into 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.

Using deep machine learning recommender system technology, Expero detects health care opioid fraud.

Patient 360 Application with claims, care plans & customer journey mapping.

This demo explores fraud prevention in healthcare applications

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.

Customer 360, Customer Journey, Product & Recommendations.

This video is about Healthcare: Opioid Fraud Detection & Avoidance.

A sneak peak of this year's Graph Day San Francisco talk on ACID & integrating JanusGraph with FoundationDB.

Example of how financial institutions can use an all encompassing view of their customer to cross-sell and up-sell.

Take a look at how to optimize your telecom. Visualize points of connectivity, and future connections to be made. Designed to accommodate a back office and on site workers.

Get more insight into your resources. Estimate ahead of time certain needs and gaps in your production line.

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 network and hierarchical data sets in ways that are cumbersome with RDBMSs and NoSQL solutions.

Dashboard showing details regarding infections resistant to antibiotics found in hospitals geographically.

Graph, Enterprise search, and enterprise analytics for financial services. Specific topics include customer 360, best next conversation, cross-sell and up-sell for product recommendation, and churn avoidance.

Transaction investigation and treasure mapping with KPIs using graph technology, high performance search, and high performance analytics.

Data Management for Oil and Gas - Predictive Maintenance Intelligence

Data Management for Oil and Gas using IOT and Machine Learning for Asset Management

Dashboard screens from an application showing detection of weather anomalies and other interferences in supply-chain. Includes user friendly abilities to reroute shipments, allowing companies to save money by limiting lost or late shipments and and changing plans at a moments notice.

Case Study

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.

Follow these tips to speed up your JanusGraph queries when running against a variety of storage backends including Apache Cassandra, ScyllaDB, Apache HBase, and Google Cloud Bigtable.

Angular, React, Ember, Vue… There are a lot of javascript frameworks out there. 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.