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October 12-14, 2021

Analytics+ Day
Graph Day
Machine Learning Day

Join us for three days of the best analytics and data presentations on the web.

Oct 12-14, 2021

Join us for three days of dynamic demo presentations. Level up your knowledge. Watch the leaders in analytics and data work their magic on Analytics, Machine Learning, and Graph. Ask questions, get real answers, and watch the solutions, all from the comfort of your desk. We’re doing demos! Attend one session or all three days, we look forward to seeing you.

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Fall TechCast Days

If you wish to attend multiple days, you must register for each day separately.

October 12th
Analytics+ Day

Schedule coming soon

October 13th
Graph Day

Melli Annamalai, Oracle
Roger Cressey, Qubix

*Session start times are subject to change.

11am ET
Use Graph Analytics for Product Recommendations with Oracle Autonomous Database
Melli Annamalai, Oracle

11:20am ET – Break

11:25am ET
Dependency Analysis of Legacy Applications with Oracle Graph
Stephan La Rocca, PITSS GmbH

12:15pm ET – Break

12:20pm ET
Modeling and Querying Complex Product Bills of Materials Using Graphs
Florian Siepe, Viessmann IT Service

1:00pm ET – Break

1:05pm ET
Integrating Data Silos with Linked Data and Oracle RDF Graph
Martien Vos, Redforce

1:35pm ET – Break

1:40pm ET
Geographical Graphs: Graph, Meet Map!
Albert Godfrind, Oracle

October 14th
Machine Learning Day

Schedule coming soon

Analytics+ Abstracts

Graph Abstracts

Businesses and services often want to make better product recommendations to customers, such as which movies to watch, for a movie streaming service. Graph analysis is a powerful tool here, to increase customer stickiness and satisfaction with their service. This can now be done easily and quickly by database developers or analysts, even without expertise in graphs.

In this demo session, we will show step-by-step how to do this using the Graph Studio feature of Autonomous Database. Starting with database tables for customers and their movie watching histories, we will create a graph. Since a customer in a cluster is likely to enjoy movies liked by other customers in the same cluster, we will cluster users based on movies they have watched, using the WhomToFollow algorithm. We will also show how to start a notebook, and run graph queries from the notebook.

Speaker Bio:
Melli Annamalai is a distinguished product manager at Oracle. She has 20+ years experience in working with unstructured and semi-structured data in the database, including multimedia data, data in Apache Hadoop platforms, property graphs, and RDF knowledge graphs. Her current focus area is graph database and analytics, in particular on ways to make it easy for developers to use graphs in any application. She enjoys working with developers as they develop and deploy solutions to solve business problems, so that she can better tailor product enhancements to what they need. She is a regular presenter at industry events, Oracle User Group meetings and techcasts, and Oracle Developer events. Melli has a Ph.D. in Computer Science from Purdue University.

Modernizing existing legacy applications is a very complex technical undertaking. Existing fragments of software need to be analyzed, and implicit dependencies between objects, such as those from references in Oracle Database objects, need to be taken into account. You also need to consider dependencies related to implementation, such as those in external scripts, user interfaces, client software, etc., as well as dependencies from business processes and user interaction with the system. This results in a complex, very large, dynamic network of dependencies.

Graph technologies are well suited to modeling such networks, and performing analysis on them. We digitize all this information into our own application datacube. Using the graph features of Oracle Database, we can then analyze, cluster, and reassign components from the legacy application into groups, based on a design pattern called “bounded context”, in order to rearchitect the legacy application into new software frameworks. In this session, we will cover the principles, concepts, ideas and results of this approach.

Speaker Bio
Stephan La Rocca is Director Business Development for PITSS GmbH, and has been working for over 20 years in the Oracle Software Development and Business Intelligence ecosystem. He has been a speaker at various conferences (DOAG, SiOUG) and webcasts. Together with the University of Ulm, he is responsible for a founded Project of the German Government focusing on retrograde analysis of Business Processes in Legacy Applications.

For product manufacturers, it is crucial in B2B e-commerce settings to give customers more insight into your products. Especially if you have a complex product catalog, with long-lasting products such as industrial durable goods, which can be composed of other products, enabling business customers to find the right information within a few clicks is a key factor for customer satisfaction.

Graphs are a useful way to model the complex relationships and dependencies among many different products and parts. To illustrate this, we construct a graph in a multi-catalog environment to model which “Part of”-relationships can be found in bills of materials (BoMs). The type of item is included in the graph: whether they are wear- or spare-parts, or just regular products. We can also perform useful queries such as finding nested spare- or wear-parts, and how a certain product or part has been used. In this example, we use Oracle Database Graph features to store, model, and analyze the BoM data set. We will also show how we use PGQL, a natural and powerful query language, to easily perform various analyses on the graph structures. Here PGQL – the query language used in PGX – here shows its advantages for handling these structures.

Speaker Bio
Florian Siepe, Software Engineer, Viessmann IT Service

Florian is a software engineer at the Viessmann IT Service. After finishing his bachelor’s degree in 2021, he is currently pursuing his Master studies at the University of Marburg (Germany).

His professional areas currently include full-stack development in a B2B e-commerce setting, while focusing on Java-based technologies such as Spring Boot or Quarkus, as well as Angular on the client side. During his bachelor studies, he gained familiarity with NoSQL database solutions and graph analytics technologies such as PGX.

Many organizations face the frustration that several existing data silos, each serving departmental operations, are needed to create a 360 view of their target object. Using data warehouse technology for such federated queries can be difficult. Most data are fetched from the source without ever being queried. Other challenges include uncontrollable data structure drift on the source side.

Linked Data can address this challenge, using the W3C standard technology of RDF Graph. Different data sources, which can contain different data types, such as asset descriptions or geographical information, can be linked in the same graph. Bringing in multiple data sources, different views on this data can be provided – depending on which application is accessing your data.

This session will feature a demo of this in action, using sewage management data from the Netherlands, developed by Redforce, a leading Dutch IT consultancy firm. They will show how Oracle technologies, including their mature RDF Graph Database features, were used in the solution.

Speaker Bio
Martien Vos is currently data architect at Redforce in the Netherlands. Martien has over 25 years experience in GIS, data migration and data integration. During the past 7 years Martien has been working intensively with Oracle RDF Graph, with a focus on RDF with the OGC GeoSPARQL standard. During the past years, Martien has developed a system for manipulating native RDF and Spatial data. This was done using Oracle APEX and Oracle JET in combination with OpenLayers.

The powerful algorithms of Oracle Property Graph combined with the flexibility of the PGQL language allow you to rapidly examine the relationships in your data. But as we all know, “a picture is worth a thousand words”. So viewing the results in a graphical way is important. This is provided by the GraphViz feature for on-premises development, and by the Graph Studio feature of Autonomous Database.

One little known capability of graph visualization is the ability to show a graph on a map. This applies well to graphs with a geographical location perspective: customers, banks, stores, airports, … It means you can highlight flows of money or goods, or flight routes on a global map.

This presentation will show how you can use this capability: enriching your data with locations, mapping locations in tables, and using GraphViz to display and interact with geographical graphs.

Speaker Bio
The session will be covered by Albert Godfrind from Oracle Corporation. Albert has over 25 years of experience in designing, developing, and deploying IT applications. His interest and enthusiasm for spatial information and geographical information systems started at Oracle when he started using the spatial extensions of the Oracle database in 1998. Ever since, Albert has been evangelizing the use of spatial information to GIS and BI communities across Europe, consulting with partners and customers, speaking at conferences, and designing and delivering in-depth technical training.

Albert is one of the authors of the first book on Oracle Spatial, “Pro Oracle Spatial – The essential guide to developing spatially enabled business applications”.

Machine Learning Abstracts

In the first 90-minute Oracle Machine Learning workshop, we will step users through Oracle Machine Learning (SQL) Notebooks while using multiple use case scenarios for analyzing insurance claims data and customer behavior data. Students will run the notebooks themselves to build and apply OML models inside Oracle Autonomous Database and then work with Oracle APEX applications that leverage OML’s insights and predictions.  We will also emphasize OML AutoML User Interface where “citizen data scientists” can easily “click” their way to good ML models and generate notebooks for further customization and deployment.

In the second 90-minute OML workshop, we will step users through the Oracle Machine Learning Notebooks with an emphasis on the new OML4Py support for Python. Students will run the notebooks themselves to build and apply OML models inside Oracle Autonomous Database while leveraging both OML4Py’s in-database functionality and the ability to run open-source Python (pandas, scikit-learn, matplotlib, etc.). Having built OML models, students will then focus on model deployment using both SQL for in-database scoring and REST APIs using Oracle Machine Learning Services.

Register Early for Fall 2021 TechCast Days

Oct 12th–14th

Oct 12th – Analytics+ Day

Oct 13th – Graph Day

Oct 14th – ML Day

Past TechCast Days