Oracle Analytics Cloud Corporate Training | Oracle Analytics Data Visualization Corporate Training Agenda

Oracle Analytics data visualization corporate training agenda

Our Data visualization (DV) course is perfect for both professionals with no / basic understanding of OAC, and technical users with a good understanding / experience with OAC. It provides attendees with a full end-to-end understanding of the tool. It is designed for anyone who is new to data visualization or who wants to understand the full capabilities of a modern analytics tool.

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Data visualization (DV) is Oracle's self-service reporting tool for data exploration and visualization, which enables users to access, analyze, and visualize data without the need for extensive technical expertise or assistance from IT.

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Pythian has cultivated a relationship with Oracle built on deep technical excellence and a commitment to customer success, establishing ourselves as a premier partner in the Oracle ecosystem. Our proven history working with the world's most complex Oracle environments, backed by a team of industry-leading Oracle ACEs, guarantees that your Oracle applications and data systems deliver maximum value and performance.

How is our Oracle Analytics data visualization corporate training delivered?

The course will be divided into lessons and labs. During lessons, the instructor will present a series of slides to explain the topic. During labs, delegates will be provided with exercises going over the functionality the instructor has just covered in the lessons. The delegates will be asked to complete the labs in the allocated time. The instructor will be available to answer any questions and provide assistance. Each delegate will be provided with a live Oracle Analytics instance to complete the labs.

Introduction

Where does DV fit in?
Overview of features and key processes

Data acquisition

Connections
Datasets

Data preparation

Data profiles and semantic recommendations
Preparation script

Data exploration and visualization

Prepare
Visualize
Narrate

Data flows

Adding data sources
Transformations
Scheduling data flows

Machine learning

Concepts and principles
Advanced analytics functions
Explain attributes and measures
Machine learning models

Lab session

Creating a dataset from a file
Creating a dataset with multiple tables
Creating a workbook
Blending data in workbooks
Presenting data in workbooks
Creating a data flow
Augmented analytics
Creating a machine learning model

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