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Data Visualization on Oracle Analytics Cloud LVC Course Overview

Data Visualization on Oracle Analytics Cloud LVC Course Overview

Data Visualization on Oracle Analytics Cloud LVC Course Overview

Discover the power of data visualization with our Data Visualization on Oracle Analytics Cloud LVC course. This comprehensive training, offered by Koenig Solutions, equips you with the skills needed to harness Oracle Analytics Cloud for impactful data presentations. You’ll explore key topics such as advanced analytics, machine learning, and augmented analytics. Learn to create interactive dashboards, perform data preparation, and uncover actionable insights. By the end of this course, you will be able to visualize complex data sets, enhance decision-making capabilities, and drive data-driven strategies in your organization. Join us to transform your data analytics skills today!

This is a Rare Course and it can be take up to 3 weeks to arrange the training.

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  • Live Online Training (Duration : 16 Hours)
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  • Live Online Training (Duration : 16 Hours)
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Course Prerequisites

Prerequisites for Data Visualization on Oracle Analytics Cloud Course

To ensure you have the foundational knowledge necessary to succeed in the Data Visualization on Oracle Analytics Cloud LVC course, we recommend you possess the following prerequisites:


  • Basic Understanding of Data Types and Structures: Familiarity with fundamental data concepts such as tables, columns, and data types is essential.
  • General Knowledge of SQL: Basic knowledge of SQL queries will help you understand how data can be queried and manipulated.
  • Introduction to Cloud Computing: A basic understanding of cloud concepts can be beneficial, as the course will cover various aspects of Oracle Analytics Cloud.
  • Basic Computer Skills: Proficiency with standard computer operations, such as navigating the operating system and using software applications, is necessary.
  • Familiarity with Business Intelligence (BI) Concepts: A general idea about BI tools and their applications can provide a helpful context for this course.

These prerequisites are designed to ensure you have the foundational knowledge needed to get the most out of the Data Visualization on Oracle Analytics Cloud course. If you meet these requirements, you'll be well-prepared to dive into the course content!


Target Audience for Data Visualization on Oracle Analytics Cloud LVC

  1. Introduction: The "Data Visualization on Oracle Analytics Cloud" course is designed for professionals seeking to leverage Oracle's powerful analytics platform for creating intuitive and impactful data visualizations.


  2. Target Audience and Job Roles:


  • Data Analysts
  • Business Intelligence Developers
  • Data Scientists
  • IT Professionals
  • Business Analysts
  • Data Engineers
  • Database Administrators
  • Analytics Consultants
  • Data Architects
  • IT Managers
  • Project Managers
  • Reporting Analysts
  • Financial Analysts
  • Marketing Analysts
  • Operations Analysts
  • Product Managers
  • Research Analysts
  • Decision Makers and Executives seeking data-driven insights
  • Anyone involved in data navigation and interpretation within Oracle ecosystems


Learning Objectives - What you will Learn in this Data Visualization on Oracle Analytics Cloud LVC?

Introduction

The Data Visualization on Oracle Analytics Cloud LVC course by Oracle University equips students with the skills necessary to create impactful data visualizations, analyze data using advanced analytics, and leverage machine learning capabilities within Oracle Analytics Cloud.

Learning Objectives and Outcomes

  • Understand the Oracle Analytics Cloud (OAC) overview and architecture.
  • Master data visualization techniques and best practices in OAC.
  • Implement and leverage advanced analytics and machine learning features in data projects.
  • Utilize augmented and mobile analytics to gain insights on the go.
  • Manage administration and security within Oracle Analytics Cloud.
  • Create and optimize data sets for cross-table analysis.
  • Harness the power of augmented analytics for smarter data preparation and enrichment.
  • Integrate and configure map layers and backgrounds for enhanced geospatial visualizations.
  • Apply natural language queries and narratives to communicate findings effectively.
  • Develop and train machine learning models for predictive analytics.