Jetpack for Wealth Screener
Connected Jetpack: An AI-assisted analytics module for navigating complex data and generating actionable insights!
Understanding the Digital Twin
Digital Twins are the next logical step in an IoT implementation. Data storage for a digital twin can include a property graph database such as JanusGraph or DSE Graph, a time series database like TimescaleDB, and an analytical database like Redshift, Google Bigquery, or HP Vertica.
2023 Technology Trends in Supply Chain
Join Expero and Neo4j in a discussion about improving visibility into your supply chain, and better use of the data you've collected to greatly improve your supply chain and chain of custody tracking.
Radiant Path Demo
Take a deeper look into Expero's Radiant Path Software, which allows users to check the feasibility of their manufacturing plans by looking at the demand versus production delta in detail.
Pharma Supply Chain Round Table
During this webinar, we will show Supply Chain managers and planners how to utilize Graph technology to ensure organizational compliance with DSCSA.
2021 Trends in Supply Chain
The focus of this webinar is to show you how new Visualizations and Graph technology trends in 2021 can increase the usability and accuracy of your supply chain.
Airlines, Logistics, & Transport Optimization Toolkit
Take a look into Expero's Network Analytics Toolkit which optimizes core elements in airlines, logistics, or transport through filtering and advanced visualizations of key performance indicators capable of running 'What If' scenarios.
Solving Supply Chain Use Cases With Confluent, ML & Visualization
The focus of this webinar is to identify how Machine Learning, Visualizations, and streaming technology can directly increase the accuracy and output of systems to drive revenue, cut costs, and include 'Human in the Loop.’ During this online meetup, you'll learn from our Confluent & Expero experts how to unlock the potential in your organization.
Supply Chain ML, Visualization & TigerGraph RoundTable
The focus of this webinar is to identify how Machine Learning, Visualizations, and Graph technology can directly increase the accuracy and output of systems to drive revenue and cut costs and include 'Human in the Loop.'
Supply Chain Planning With Active Scenario Modeling
With disruption as the new normal, plans need to constantly realign and adapt. Managing flow across multiple tiers of suppliers is difficult under normal circumstances, but with changing lead times and supplier disruption, there is an increasing need to improve supply visibility. This webinar discusses strategies to map flows and improve plan feasibility and reliability for Supply Chain planners around the globe.
Transportation & Logistics with Graph & ML Round Table
The key use cases to be illustrated in this webinar are: payload and route optimization, asset and driver optimization, warehouse location, multi-mode transportation options, higher more profitable miles, lower driver turnover, increased safety, demand and capacity planning, and the ability to 'What If' all parts of the logistics process in real time.
Moving Beyond Node Views
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.
Deploying Data Products
Building data products in your organization to realize data science ROI and never before seen data insights.
S&OP 5 Step Process + Toolkit
Revolutionize your sales and operations planning. Find what matters in your data, align stakeholders, explore issues and proactively what-if alternatives.
Fleet Management & Scheduling
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.
Supply Chain Solutions using Kafka + ML
Automating multifaceted, complex workflows requires hybrid solutions like streaming analytics of IoT data, batch analytics like machine learning solutions, and real-time visualizations.
Speed Dating with Cassandra
15 Minute Lightning Talks + Q&A. Powerful Data, Storage & Search & Graph Technology in 1 platform - Cassandra.
Supply Chain Online Seminar
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.
Supply Chain Optimization
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.
Supply Chain: From Order to Fulfillment
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.
Graph & ML for Supply Chain
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.
Supply Chain: Routing Optimization
Use case modeling timeline and possible future events that could interfere with supply chain. Allows user to see all options for rerouting and the implications of each decision.
Optimizing Logistics & Supply-Chain With Graph
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.
What Machine Learning Can Learn from Graph
Graphs and graph datasets are rich data structures that can be used uniquely to improve the accuracy and effectiveness of machine learning workflows. Some of the key interactions are graph analytics as features, semi supervised learning, graph based deep learning, and machine learning approaches to hard graph problems.
Predictive Analytics for Kinsa Health
Can you predict and plan for the flu? Expero built a data product including a long term forecast for modeling the spread of influenza-like illness across the United States using a cutting edge deep learning model.