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Hands on Lab – Test Drive an Autonomous Data Warehouse Powered by AI/ML

February 20 @ 6:00 pm - 8:00 pm

Hand on Lab -Test Drive an Autonomous Database Warehouse powered by AI/ML

Agenda

6:00 Doors Open, Food & Networking
6:30 Workshop lead by Sai Valluri & Santosh Kumar Ramarathnam
6:45 Registration close

Abstract

Please join us for an Oracle workshop on Autonomous Database Warehouse (ADW). An autonomous database is a cloud database that uses machine learning to eliminate the human labor associated with database tuning, security, backups, updates, and other routine management tasks traditionally performed by database administrators (DBAs).

Autonomous Data Warehouse is built around the market leading database and comes with fully automated data warehouse specific features that deliver outstanding query performance. This lab walks you through the steps to get started using the Oracle ADW.

Learn:
1) How to deploy a data warehouse and run workloads with only a few clicks.
2) How to scale storage and compute resources independently with database services running with no downtime.
3) How to run faster analytics on diverse data sets with fast visual predictive pattern.

This hands-on workshop is for all machine learning experts, data scientists, DBAs, and developers who want to learn how a self-driving, self-repairing, and a self-securing data warehouse works on high performance infrastructure.

Prerequisites: bring Laptop- either Windows/Mac and pre-install:

1. SQL Developer: follow

https://www.oracle.com/technetwork/developer-tools/sql-developer/downloads/index.html

On Windows:
Select the OS for your computer. (This page also has instructions on how to install SQL Developer on Windows, Mac OSX and Linux.)

If you already have SQL Developer installed on your computer please check the minimum version required to connect to an Oracle ADW Cloud is SQL Developer 17.4.

Mac:

https://www.oracle.com/technetwork/developer-tools/sql-developer/downloads/sqldev-install-mac-1969675.html

2. Data Visualization Desktop

Oracle Data Visualization Desktop makes it easy to visualize your data so you can focus on exploring interesting data patterns. Choose from a variety of visualizations to look at data in a specific way. Data Visualization Desktop comes with Oracle ADW.

To download and install Data Visualization Desktop please follow
https://www.oracle.com/technetwork/middleware/oracle-data-visualization/downloads/oracle-data-visualization-desktop-2938957.html

Select the OS for your computer. This page also has instructions on how to install DVD on Windows and Mac OSX.

If you already have Data Visualization Desktop installed on your computer then please check the version. The minimum version that is required to connect to an Oracle ADW Cloud is 12c 12.2.5.0.0.

Workshop instructors:

Sai Valluri – Sai is a Product Marketing Manager with the DB Product Marketing Group at Oracle. In his previous roles, Sai donned multiple hats including Business Development, Alliances, Program Management and Pre-Sales. Sai holds a Master’s in Analytics from Saint Mary’s College of California and Project Management Certificate from University of California, Los Angeles. He spends his spare time with his family, photography, and volunteers with a couple of non-profits in the Bay Area.

Santosh Kumar Ramarathnam- Santosh is Senior Technical Consultant at Oracle and is an OCI certified Associate. He is a Specialist in Oracle Exadata Database Machine and Cloud Application Foundation. He is experienced in engagements creating solutions, covering a wide range of areas including System software, Performance, Capacity and Availability management, Infrastructure Architecture & Design for dedicated applications and shared IT services, Hardware Pre-Sales and Project management.

Details

Date:
February 20
Time:
6:00 pm - 8:00 pm
Website:
https://www.meetup.com/SF-Bay-ACM/events/257921992/

Organizer

SF Bay ACM Chapter
Website:
https://www.meetup.com/SF-Bay-ACM/

Venue

Oracle Building 4 Santa Clara Offices
4040 George Sellon Circle
Santa Clara, ca 95054 US
+ Google Map



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