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This meetup page is for members of the Arizona Oracle User Group. Everyone is encouraged to join and attend scheduled meetups. There is also a discussion forum where we can share information or ask fellow members for help on any Oracle related topic.

Joining this group is a great way to network and make new connections. Any scheduled events will be posted here. Active participation in this group is highly encouraged.

There are some basic rules:

1. Treat everyone with respect

2. This is not a venue to sell goods or services

3. Active recruitment is not allowed. Any job posting belong on LinkedIn page

If you are ready join, click the button!

Thanks, and we look forward to meeting you.

Upcoming events (3)

Secure Flexible Oracle Analytics by Integrating Autonomous Database w/ Data Lake

"Secure and Flexible Oracle Analytics on Any Data by Integrating Autonomous Database with Data Lake" with Holger Friedrich, sumIT AG Nowadays we need to run analytics on all kinds of data. This includes flexible formats and semi-structured data from data lakes as well as curated data from relational databases. A great way to access these different types of data sets and sources with Oracle Analytics is by integrating a flexible, scalable (object) storage layer with the powerful Oracle database engine. This works especially well in the cloud, using OAC on top of the Autonomous Data Warehouse service. The key to all of this is the clever use of (partitioned) Oracle External Tables. In this presentation, we will discuss the integration of OAC, ADB, and Object Storage from an architecture point of view, as well as the technical implementation. Demos will show the elegance of the approach, the great performance, and its security benefits. Register Here: https://register.gotowebinar.com/register/6200224542898793744 Date and Time - Tuesday, October 27, 2020, 12:00 PM - 1:00 PM EDT Please Note: The time zone difference, 12:00 PM – 1:00 PM EDT / 11:00 AM - 12:00 PM CDT / 10:00 AM - 11:00 AM MDT / 9:00 AM – 10:00 AM PDT

Reverse Engineer Machine Learning To Develop Performance Monitoring Rules

If you’re tired of continuously adjusting your performance monitoring and alerting rules, then how about using machine learning to create the rules for you! Of course, we can train a supervised machine learning model to recognize patterns of poor performance. But what if your IT department is not ready to embrace machine learning? A novel solution is to train a supervised machine learning model to recognize patterns of poor performance, but then extract the rules in plain English and then manually enter them into your existing monitoring and alerting platform. Is this possible? Yes, it is! And, I will demonstrate how you can do this. To ensure you can easily do everything I do, I will use industry-standard Python ML libraries, the industry-standard Jupyter notebook, AWR, and support ticket data. You can experiment with the demonstration materials “as is” and then use them to push your ML and rule creation knowledge deeper. Join me for a fascinating presentation about how to use the results of ML as inputs into your existing monitoring and alerting systems. Summary: After a brief machine learning introduction, in this presentation, we begin with learning how to build a supervised machine learning decision tree model using industry-standard Python libraries, a Jupyter notebook, AWR, and support ticket data. I’ll show you where to get the data, how to load it into the model. Then, we’ll focus on training and evaluating the model. Finally, I’ll detail how to extract and convert the machine learning “poor performance” model decision tree internals into rules that we can use in your existing monitoring and alerting systems. Register Here: https://register.gotowebinar.com/register/7496349741127048718 Date and Time: Tuesday, October 27, 2020 | 12:00 PM - 1:00 PM CDT Please Note: The time zone difference, 12:00 PM – 1:00 PM EDT / 11:00 AM - 12:00 PM CDT / 10:00 AM - 11:00 AM MDT / 9:00 AM – 10:00 AM PDT

Analytic Views - the Virtual Cube

Online event

Traditionally to model and analyze your data with dimensions and hierarchies, either you copy your data to a data warehouse and from there to a dimensional cube, or you have to write quite a lot of rather advanced code and SQL to emulate the same directly on your relational data. With analytic views (introduced in Oracle Database version 12.2), you declaratively define the dimensions and hierarchies similar to creating a cube, but it is only stored as a metadata layer on top of your tables; it is a multidimensional view of your relational data. The SQL language has been expanded to allow a simpler query syntax on the analytic views to utilize these metadata and automatically use advanced analytic functions to give you dimensional analysis on real-time data. As SQL is used below the covers, performance can be tuned using query rewrite with materialized views or In-Memory options, or any other option you would normally use for SQL tuning. This session will show code examples covering a lot of the syntax you have for creating and using analytic views. Register Here: https://oappsnet.zoom.us/webinar/register/WN_p81NNJA3Ram79Kx5kTPmqg Date and Time: Wednesday, Oct 28, 2020, 12:00 PM CDT Please Note: The time zone difference, 1:00 PM – 2:00 PM EDT / 12:00 PM - 1:00 PM CDT / 11:00 AM - 12:00 PM MDT / 10:00 AM – 11:00 AM PDT

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