Enhanced Visual Analysis with Data Visualization
Duration : 1 Day (8 Hours)
Enhanced Visual Analysis with Data Visualization Course Overview:
The Enhanced Visual Analysis with Data Visualization certification focuses on the art of converting raw data into compelling visual narratives to leverage the power of data effectively. This certification equips professionals with techniques to represent and interpret complex datasets in an easily understandable format. By using data visualization, organizations can make well-informed decisions, identify patterns, and forecast trends. Professionals with this certification possess the ability to visualize relationships between multidimensional datasets, interpret statistical models visually, and present visualized data effectively. As a result, it enhances strategic planning, decision-making processes, and overall operations across various industries, including healthcare, marketing, finance, and logistics.
- Data analysts
- Business intelligence professionals
- Data scientists
- Machine learning engineers
- Data-driven marketers
- Market research analysts
- IT professionals working with data
- Graduate students in data-related fields
- Corporate decision-makers relying on data analysis.
Learning Objectives of Enhanced Visual Analysis with Data Visualization:
The Enhanced Visual Analysis with Data Visualization course has the following learning objectives:
- Develop an understanding of representing data effectively through visual formats for clear communication of complex information.
- Learn the principles and techniques for creating impactful and understandable data visualizations.
- Gain hands-on experience with data visualization tools.
- Learn how to interpret and draw meaningful conclusions from data visualizations.
- Understand the ethical considerations in data visualization, including the potential for misrepresentation or bias.
By the end of the course, students will be equipped to critically assess data visualizations, create their own, and enhance data-driven decision-making processes.
Module 1: Data Visualization on Oracle Analytics Cloud: Overview
- Introduction to Oracle Analytics Cloud
- Key Features of Oracle Analytics Cloud
- Benefits of Oracle Analytics Cloud
Module 2: Uploading Data from External Sources
- Characteristics of External Sources
- Adding a Spreadsheet as a Data Source
- Creating Data Sources from Databases
- Creating a Project with an Oracle Application Connection
Module 3: Blending and Managing Data
- Blending Data from Multiple Sources
- Controlling Sharing of Data between Users
- Managing Data Sources in Projects
Module 4: Data Wrangling and Data Flow
- Using Data Wrangling Functions
- Curating Data Sources with Data Flow
Module 5: Adding Data Elements and Visualizing Content
- Adding Data Elements to a Blank Canvas
- Enhancing Visualizations with Advanced Analytics Functions
- Adjusting Visualization Properties
Module 6: Exploring Data by Using Filters, Drilling, Sorting, and Selecting
- Overview of Filters
- Automatically Applied Filters
- Creating Custom Filters for Data Exploration
Module 7: Creating Calculated Data Elements and Building Expressions
- Creating Calculated Data Elements with Formulas
- Composing Expressions for Advanced Data Manipulation
Module 8: Visualization Interaction and Exploring Data on Mobile Devices
- Overview of Visualization Interaction and Synchronization
- Synchronizing Visualizations across Devices
Module 9: Importing, Exporting, and Converting Projects
- Importing Applications or Projects into Oracle Analytics Cloud
- Exporting Projects as Applications for Sharing
- Exporting Visualizations, Canvases, or Stories
Module 10: Accessing and Organizing Content
- Finding and Exploring Your Content within Projects
- Assigning Ownership of Items
- Embedding Content in Other Applications
Module 11: Managing Users, Backup, and Restore
- Getting Started with Application Roles
- Assigning Application Roles to Multiple Users through Roles
- Project Indexing, Monitoring Users, and Activity Logs
Module 12: Troubleshooting Issues in Projects
- Troubleshooting Data Issues in Oracle Analytics Cloud Projects
Enhanced Visual Analysis with Data Visualization Course Prerequisites:
• Basic knowledge of data analysis techniques and concepts
• Basic understanding of statistics
• Familiarity with relevant programming languages like Python, R, or Java
• Experience with data visualization tools such as Tableau or PowerBI
• Strong problem-solving abilities and analytical thinking skills.
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This course comes with following benefits:
- Practice Labs.
- Get Trained by Certified Trainers.
- Access to the recordings of your class sessions for 90 days.
- Digital courseware
- Experience 24*7 learner support.
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