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Join Scylla and Expero to learn how to use JanusGraph and Scylla to architect a corporate compliance platform. In this talk, you’ll learn how to:

- Create a dynamic graph-enabled approach to building a flexible entitlements system

- Design the underlying data model and data infrastructure you need to support this system

- Architect real-time data connections to integrate this system successfully into your enterprise

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.

Cut Costs & Prevent Churn with Graph Technology & ML Analytics

What You Will Learn

  • Technology - Discuss how to quickly integrate Graph & Machine learning into your existing technology platform stack.
  • Customer Acquisition - How to use graph to target, segment and recommend.
  • Retention - Identify, score and intervene with customer journeys to better understand and predict behavior.
  • Growth & Loyalty - Target and personalize up-sell and cross-sell opportunities to maximize “Best Next Conversation” with customers.
  • Churn & Sentiment - Utilize sentiment analysis with Machine Learning & Graph to identify and mitigate churn.
  • Personalization - Optimize by customers, products, & relationships.
  • Analytics & Predictive - Pattern matching, ML algorithms, ‘treasure mapping’ for correlations of historic data, and recommendations with Graph & Machine Learning.

Congratulations, you have Active Directory, 27 different systems with complicated group and role permissions.  Or even better, maybe you’ve got some of that logic written directly into your application…more than once!

And now you’ve got your regulatory compliance auditor asking for reports about who can access that piece of data from last quarter! And your development director turns to your devops lead and says “When did we deploy that code patch?”

Moreover, how well do you know all those new hires? How can you be sure no one’s snooping around in the sensitive accounting data?

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.

What You Will Learn

  • Full Patient 360 - Tie all aspects of the patient together and identify relationships. Use Graph & Time Series to view history and identify with ML patterns.
  • Churn Prevention - Data segmentation, analytics for historical data and pattern views.
  • Sentiment Tracking & Patient Care Analysis - Analytics to navigate your data and track patient care.
  • Identification of Claim Anomalies - Fast, impactful analysis of data for anomaly detection.
  • Member Care & Doctor Abuse Detection - Intervention and Graph relationship management for cause and case tracking.
  • Influence Analysis - Most influential doctors + pharmacies;  most influential financial analysts.
  • Network Efficiency - Using graph to determine which networks are most efficient.
  • Working Prototypes - See graph and ML in action

What You Will Learn

  • Multi-tiered compliance workflow to ensure clearance of trades.
  • Routing Optimization
  • The iteration between "what-if" trade scenarios and compliance scoring.
  • Machine learning algorithms that can assist in scoring strategy, and dramatically increase efficiency.
  • Recommend best possible strategic portfolio moves to increase efficiency.
  • How real-time data visualization can simplify trading alternative assets
  • How to convey complex information to constituents in a way that is timely, comprehensible and actionable

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

March 26, 2019 - 1 PM CST // 11 AM PST

Session 1 - One Platform to Rule the Business  
Phil Bayliss - Account Executive; DataStax
(15 Mins + 5 Mins Q&A)

Session 2 - Cassandra: Cloud, Multi-cloud, & Hybrid - Performance topics & Demo
Marco Collazos - Account Executive; DataStax
(15 Mins + 5 Mins Q&A)

Session 3 - The Art of the Possible: Use Cases in Supply Chain, Customer 360, & Fraud Detection
Scott Heath - Executive Team; Expero
(15 Mins + 5 Mins Q&A)

Session 4 - How to Reconcile with Eventual Consistency
Brian Hall - Graph and Analytics Practice Lead; Expero
(15 Mins + 5 Mins Q&A)

Session 1 - The State of JanusGraph 2019
During this session, we'll discuss the future of JanusGraph during 2019 and beyond.
Chris Hupman - Systems Engineer, IBM
(20 Mins + 10 Mins Q&A)

Session 2 - Creating Expressive Graph Data Models with JanusGraph
We will walk through the process of iteratively building a data model, discuss some pitfalls to avoid, and check out how to improve the data model in a working database, without a full rebuild.
Ryan Stauffer - Enharmonic
(20 Mins + 10 Mins Q&A)

Session 3 - A Gremlin DSL for JanusGraph Schema Management
During this talk, we'll discuss a potential approach for replacing the current JanusGraph schema management approach with a Gremlin DSL.
Jan Jansen - Developer, G DATA
(20 Mins + 10 Mins Q&A)

Session 4 - The New ODPi - A Home for Vendor-neutral Big Data Open Source
The ODPi Egeria project was founded in 2018 with the goal of driving collaboration between vendors, end-users, solution providers, and developers.
John Mertic - Director of Project Management, The Linux Foundation
(20 Mins + 10 Mins Q&A)

Session 5 - High Performance JanusGraph Data Loading
We will discuss common JanusGraph data loading pitfalls and provide a set of helpful tips and patterns to follow.
Ted Wilmes - Data Architect, Expero
(20 Mins + 10 Mins Q&A)

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

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.

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.

Faced with an ever increasing amount of data, the modern enterprise features the complex task of leveraging this data to extract maximum value. On the one hand, much of the value arises from a better understanding of the relationships between entities in the domain under question, a task ideally suited to the popular open source property graph database, JanusGraph. On the other hand, time series data, by its nature, drives much of this growth, whether it be pressure sensors reporting from thousands of natural gas wells to system metrics being collected by any of the many popular infrastructure monitoring solutions, or stock ticks coming in from the NYSE. Time series data is incredibly valuable but can be improved upon when the wider context is joined in through the pairing with the graph database. For this talk, we’ll propose an architecture of JanusGraph and OpenTSDB, both relying on Cloud Bigtable to tackle these classes of problems. Concrete use cases will be covered along with the benefits of running these workloads on a combined platform with Cloud Bigtable backing graph and time series storage.

Learn how DataStax Graph Technology will increase customer loyalty, identify and resolve customer issues and provide strategic up-selling capabilities.  Utilizing DataStax 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 and finally get an all encompassing view of your customer.

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 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 Database vs. traditional relational database platforms.

For the slide deck please email - info@experoinc.com

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 allows you to increase customer satisfaction through visualization of supply and demand impacts. 

Learn how Graph Visualization Technology will increase customer loyalty, identify and resolve customer issues and provide strategic up-selling capabilities. Utilizing Graph will allow you to visualize customer touch-points and the whole customer journey, providing more meaningful interactions and increasing customer satisfaction. Join us to learn how to maximize resources with Graph technologies and finally get an all encompassing view of your customer.

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.

Intelligent applications to deal with fraud and money laundering are essential for modern risk management in financial services, banking and retail. However, AI projects dealing with fraud often miss out on funding because stakeholders span many organizations and need very different levels and types of information; from technical to financial evaluation, nuanced details can accelerate or stall a projects depending on how they are presented.

Learn how Graph Technology + Machine Learning will increase customer loyalty, identify and resolve customer issues and provide strategic up-selling capabilities.  Utilizing Graph + ML 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 and finally get an all encompassing view of your customer.

Increase customer satisfaction and decrease support costs with faster response times.       

Why Graph?

Learn how Graph Technology + Machine Learning 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 Graph + 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 Database vs. traditional relational database platforms.

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.

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 -- Optimization
  • Materials, transport, regulation/compliance and customer optimization
  • Issue Resolution and identification -- discuss ROI and time -- Value of supply, manufacturing, transport and end product satisfaction
  • Visualize 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.

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.

What You'll Learn

  • Demonstrations of Customer-360 applications
  • Technology Review: Discuss DataStax Enterprise and Graph platform stack.
  • The ROI of a positive customer journey with meaningful data-backed interactions
  • How customer journey visualization identifies and resolves customer issues, improves customer interaction time, increases customer satisfaction and provides detailed views of customer history
  • How to Identify customer behavior trends and purchasing patterns 
  • Position strategic upsells and cross-sells by correlating sales data to customer history and product categories 
  • Graph Principles: Clustering, Networks, Proximity and Progressive Disclosure -  the ability to drill in as information is presented and requiring interaction, allow large data viewing without overwhelming users with millions of data points 
  • The ability to score and create usable information from multiple sources. Construction of scorecards and risk calculations which indicate how users should prioritize their customer-facing time, and on which topics or products to dive deeper.

Stay ahead of the fast moving threat of fraud with Graph Technology.

Learn how 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 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? 

Topics for this webinar include: 

  • Fraud and associated losses - statistics and why you need to act 
  • Business case of fraud and why executives need to know
  • Current methods and technology are outdated and lagging
  • 5 methods and ways to get ramped up to fight fraud

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.

Updating a legacy application is a journey with many complex moving parts, however, determining if your software is worth modernizing and planning a path forward can be done relatively quickly. The key to successful software modernization (and squelching feelings of dread on the topic) is having a sound plan that addresses all aspects of modernizing an application from technology to business case to user experience. 

In this session of our client-server to cloud seminar series, we share proven methods for determining if modernizing makes sense for your application, a checklist of considerations, and a Lean process for creating a sound modernization strategy.

Updating a legacy application is a journey with many complex moving parts, however, determining if your software is worth modernizing and planning a path forward can be done relatively quickly. The key to successful software modernization (and squelching feelings of dread on the topic) is having a sound plan that addresses all aspects of modernizing an application from technology to business case to user experience. In this session of our client-server to cloud seminar series, we share proven methods for determining if modernizing makes sense for your application, a checklist of considerations, and a Lean process for creating a sound modernization strategy.

Companies across a variety of industries are trying to attain a holistic view of their customers.  From creating a more personalized experience, to creating more timely and relevant support, to simply marketing to them more efficiently and effectively, there are tremendous gains to be had with a 360-degree view.  

However, achieving this 360-degree view requires serious data — or more accurately, serious crunching and analyzing of data to understand customer relationships across every touchpoint and multiple business units.

Sound challenging? It was. Until graph databases.

Traditional data stores and algorithms can’t handle interactions across multiple touch points in real-time —these days your customers will not wait for your batch job to complete.  However, new graph technologies provide unique benefits for getting that all-important Customer 360 view.

What you'll learn:

  • Leverage a graph database to support your 360 project
  • Manage customers through multiple client channels and gather a complete timeline of their interactions
  • Identify actionable user behaviors
  • Create a real-time comprehensive, 360 view of your customers

What do my users want to do with Big Data? How do they want to visualize it, interact with it and manage it? How big is my data, really? How much data can a human deal with at one time, and how much data should we process at one time? How can the UX accommodate data sources that respond at different rates?

If these questions resonate with you, then check out this tag-team webinar by Expero co-principal and UX designer Lynn Pausic and Expero President and software engineer Sebastian Good.

On the user side, Lynn discusses how to envision useful, usable interface solutions for serious Big Data problems, while Sebastian tackles the technical side of Big Data’s back end.

Are you a Product Manager looking to show some early design directions to stakeholders and end-users? Are you a Developer needing a little more direction from the design team? Or a UX Designer or Researcher trying to figure out how detailed your designs need to be to communicate your intentions and get valuable feedback from users?

In this webinar, Expero highlights the major differences between static wireframes and interactive prototypes, shows examples of the design fidelity spectrum, and outlines the best ways to leverage wireframes and prototypes throughout the product design life cycle. At the end of the webinar, you’ll even experience a wireframe-v-prototype battle royale through a series of mini user tests on a product designed specifically for this session!

Ever wonder about the best way to visualize your application’s data sets? Is a tree map the way to go? Maybe a bubble chart? Are there certain visual mechanisms that lend themselves naturally to certain data types? Do your users even understand common visualizations? This webinar can help.

Expero's Lynn Pausic and Chad Huff present best practices for creating useful and usable interactive visualizations for complex data sets, starting with ascertaining what your users will do with the data. The presenters show examples of battle-tested data visualization types and help you figure out how to make sure your users get the most out of the visualizations you create.

Using UI design patterns can lead to a 50% increase in product development efficiency, and it can dramatically improve usability and user adoption. This webinar discusses 10 patterns that help users interact with data tables and navigate large data sets.