Modern Data Visualization with Augmented Analytics
Duration : 1 Day (8 Hours)
Modern Data Visualization with Augmented Analytics Course Overview:
The Modern Data Visualization with Augmented Analytics certification showcases expertise in using advanced tools to interpret complex data sets. It focuses on augmented analytics, which leverages artificial intelligence (AI) and machine learning (ML) to automate data preparation, insight discovery, and sharing. Industries utilize this certification for predictive and prescriptive data analysis, leading to streamlined decision-making, increased efficiency, and a competitive advantage.
Certified professionals can effectively translate raw data into comprehensible visuals and interactive dashboards, making data-driven insights more accessible for strategic planning and policy-making. This certification enhances the ability to navigate advanced data systems and optimize business intelligence, contributing to better-informed decisions and improved overall performance.
- Data analysts and scientists
- Business intelligence professionals
- IT and data management professionals
- Data-driven decision makers in businesses
- Management and strategy consultants
- Professionals interested in data visualization
- Business managers focusing on predictive analytics and decision making
- Researchers and data-focused academics.
Learning Objectives of Modern Data Visualization with Augmented Analytics:
1. Understand the fundamental principles and techniques of modern data visualization and augmented analytics.
2. Learn how to interpret and present complex data in a visually appealing and easy-to-understand format.
3. Gain knowledge on various data visualization tools and software and their practical applications.
4. Acquire skills to explore and analyze large datasets using augmented analytics.
5. Understand the role of machine learning and AI in augmenting data analytics.
6. Learn to create interactive dashboards and reports for effective business decision-making.
7. Understand the ethical considerations and best practices in data visualization and augmented analytics.
8. Develop abilities to communicate effectively about data-driven insights to both technical and non-technical stakeholders.
Module 1: Augmented Analytics
- Oracle Analytics: Home Page
- Bring in Your Data: Data Import
- Data Visualization: Glance at Project Features
- Avoid Blank Canvas Syndrome
- Interact with Data: Project and Filters
- Practice 1-1: Create a Project with Any Data Set
- Practice 1-2: Use Explain
Module 2: Augmented Enrichment
- Project Overview: Sales Analysis
- Data Preparation Basics with Oracle Analytics
- Preparation Script: Edit, Create, Delete Steps
- Practice 2-1: Augmented Data Preparation
- Practice 2-2: Analyze enriched Data
Module 3: Story Telling and Collaborating Your Discovery Project
- Business Use Case: Soccer Half-Time Analysis
- Self Service Analysis: Auto Generate Insights
- Missing Metrics: Build Calculated Metrics
- Paint Canvases: Create Multiple Canvases
- Use OOTB Statistical Tools: Advanced Analysis in Visual
- Share Your Story: Narrate and Share Your Discovery
- Practice 3-1: Create Insights from Data
Modern Data Visualization with Augmented Analytics Course Prerequisites:
- Basic understanding of data analysis and business intelligence concepts.
- Familiarity with any programming language, preferably Python or R.
- Knowledge of SQL and database management.
- Familiarity with any data visualization tool, like Tableau or PowerBI.
- Basic understanding of statistical analysis is beneficial.
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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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