Join us for three days of the best analytics and data presentations on the web.
October 13–15, 2020
Fast, furious, and informative these sessions will be dynamic and increase your knowledge, all from the comfort of your desk. Attend one session or all three days, we look forward to seeing you.
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January 26-28, 2021
AnDOUC TechCast Days – Winter
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Note: If you wish to attend multiple days, you must register for each day separately.
Predicting Skier Days – An Introduction into Oracle Data Mining
Jasmin Fluri, Schaltstelle GmbH
Fraud Journey: Human Expert and Machine Learning working together
Dr. Abi Giles-Haigh, Vertice
Charlie Berger, Oracle
OCI Data Science Deep Dive Demo
Darren Race, Oracle
What are graph technologies and why would I use them?
Gianni Ceresa, DATAlysis
Emma Thomas, Oracle
Hans Viehmann, Oracle
Detecting social relationship clusters using graphs
Alberto Iriarte Lanas, Caixabank
Adding Graphs to ML
Melliyal Annamalai, Oracle
Building Rule-Based OLTP Systems Using Oracle RDF
Phil Cannata, Oracle
Nigel Jacobs, Oracle
Oracle Analytics Cloud Implementation at Hartford Healthcare
Ravi Murikipudi, Hartford Healthcare
Hyder Mehtawala, Deloitte Consulting
Using Oracle Analytics to Predict Fraud
Eric Probst, Certegy
Cathey Pendley, Vlamis
Embedding Oracle Analytics into Public Websites – Democratize Your Data and Make it Transparent for All
Rich Clayton, Oracle
Brendan Doyle, Oracle
Applied Analytics from Ward to Board
Roger Cressey, Qubix
In winter skiing is a popular sport in Switzerland. But not on all winter days the skiing regions are used to capacity. There are slow days as well as busy days. To plan, skiing areas need to know how many skiers they have to expect on which day during the season. This information allows planning the number of employees in restaurants as well as the staffing of their lifts. This talk discusses the first steps with Oracle Data Mining Features in a research project with a Swiss Skiing Region, entry obstacles, and how to build a prediction model on Oracle Autonomous Cloud as a beginner.
Rossi Bank think they have a problem with fraudulent transactions, they have no idea how much it’s costing, and we need lots of experts to investigate every transaction. The problem is that the knowledge of these fraudulent transactions is stuck inside the expert’s head!
Join us as we show you how to combine the Oracle Autonomous data warehouse with APEX to capture that knowledge and help fight the fraudsters!
From this knowledge, we’ll show you how to build Machine learning models to identify fraud and help combat future fraudulent transactions. In addition to this, we’ll explore how this can be combined with OAC to help the wider business understand the machine learning models.
This session is for developers, data scientists, and analysts searching for complex patterns in data.
Oracle Cloud Infrastructure Data Science is a fully managed and serverless platform for data science teams to build, train, and manage machine learning models using Oracle Cloud Infrastructure. This very demo-heavy interactive deep dive will walk the audience through the steps of machine learning: accessing data in a variety of formats, understanding data, visualizing data, building machine learning models to understand driving “forces” in data, applying models and performing what-if analysis. Come see OCI Data Science in action and bring your questions.
According to Gartner, graph technologies are currently among the ‘Top 10 Data and Analytics Technology Trends’. In this introductory presentation, we will explain what this excitement is all about, which kinds of use cases we have come across, and how the graph features, which are now free with every edition of the Oracle Database, can help to address these use cases. We will be covering both property graphs and graph analytics, as well as knowledge graphs based on the Resource Description Framework (RDF). If you are new to either or both of these graph models, you should have an understanding of their respective benefits after this session and should be all set for the remaining talks in the track.
The RDF graph model can be leveraged to create applications that are easy to build and easy to maintain. The flexible schema of RDF makes schema management easy. Rules can be managed in the database, without complex embedding in application logic, making applications reusable in multiple contexts. This session will showcase a sample application for housing management built using Oracle RDF Graph technology, with SPARQL, SQL, and PL/SQL, and ORDS to communicate via REST. Rules and logic are all in the database, making it easy to develop, manage, and maintain.
Hartford HealthCare Corporation (HHC), Connecticut’s most comprehensive integrated healthcare system, embarked on the journey of Oracle Analytics Cloud (OAC) after running the Oracle BI Applications on-premise for more than a couple of years. In today’s session, we will focus on the following areas and share some of the lessons learned as part of the implementation:
- High-Level Architecture – OAC with on-premise data warehouse
- Security Migration to IDCS
- Custom Plugin framework – Leverage Oracle provided SDK to extend the capabilities of the data visualization platform
- Sizing of PROD environments – Considerations while sizing the production environment
- ML capabilities – Implementation of Employee Attrition Prediction use case using Oracle Data Miner
How do you use Oracle Analytics to predict bad checks and protect a retailer from fraudulent customers writing bad checks?
Certegy is a leader in traditional check acceptance and Automated Clearing House (ACH) payment solutions, risk management, and return check warranty. Come to this session to learn how Certegy is using Oracle Analytics Cloud along with the Machine Learning capabilities of the Oracle database to help its customers combat fraud.
Topics to be covered include:
- Certegy’s migration from dumping data to excel to Oracle Analytical Cloud usage for client presentations and data analytics.
- Considerations in using OAC Subject areas instead of relying exclusively on data sets
- Certegy Risk Department – 3 areas that make up the department and their interdependence
- Data Science – creates the tools
- Risk Analytics – uses the tools to block potential fraudulent activity
- Investigations – works with law enforcement to arrest and prosecute fraudsters
- Techniques for sharing analytic results with others in the organization
- Automation of Investigation reports used as evidence in the prosecution of fraudster
- Certegy’s experience with Machine Learning, from Random Forest to Neural Networks and how they will impact Certegy’s bottom line.
The ability to embed Oracle Analytics content directly into public websites allows the public to view this content without logging into Oracle Analytics. In turn, making analyses available for public consumption makes insights much more comprehensive for all.
Learn some best practices in embedding Oracle analytics and making insights readily available to your community.
The National Health Service (NHS) is the publicly funded national healthcare system for England and one of the four National Health Services for each constituent country of the United Kingdom. It is the largest single-payer healthcare system in the world. Primarily funded through the government funding and overseen by the Department of Health and Social Care, NHS England provides healthcare to all legal English residents, with most services free at the point of use. Some services, such as emergency treatment and treatment of infectious diseases, are free for everyone, including visitors.
Qubix work closely with the NEP who provide a shared services hub for many of the NHS trusts to provide templated solutions which will enable participating trusts the ability to quickly get up and running with the ability to provide compliant reporting as mandated by the government. The trusts do this on a subscription basis.
One of these templated solutions provides the ability to analyze patient treatment data at a granular level. This presentation will focus on one of the main aspects that NHS treatment units are required to report on. Anyone receiving attention at one of the NHS treatment units should be seen within a four hour window of time. If a patient is not attended to within that time, it is known as a “4 hour breach”.
This presentation will describe the technology employed to underpin the solution, the implementation methodology (taking into account the template approach), and demonstrate use of the tool to track 4-hour breach contributing factors.
Why Is This Topic Important to attendees?
The solution provides a real-life working example of how to employ and use out of the box Oracle technology functionality.
It will describe how templated solutions can be built encompassing a core set of requirements, and yet provide flexibility for the unique analytics of a particular trust to be pursued.
A description of the way in which the software and services can be bundled to remove barriers for organizations participating in the use of the solution will be provided.