Mentor Based
Tableau for Business Intelligence
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Course Overview
Program Syllabus
Module 1
About This Course
The Program offered by NanoSchool is designed to equip participants with advanced skills in data visualization and analysis using Tableau. The program covers essential topics such as creating interactive dashboards, integrating data from multiple sources, and utilizing Tableau for business intelligence to drive data-informed decisions. It is led by Dr. Chitra Dhawale, who brings extensive expertise in the field. The course offers a blend of theoretical knowledge and practical application, ensuring that participants can effectively use Tableau in real-world scenarios.
Module 2
Aim
The aim of this program is to empower participants with the skills and knowledge to leverage Tableau for effective data visualization and business intelligence. The course focuses on transforming raw data into insightful, interactive dashboards and reports that aid in strategic decision-making. By the end of the program, participants will be proficient in using Tableau to analyze and visualize data, facilitating better business insights and enhancing their ability to communicate data-driven findings.
Module 3
Program Objectives
- Introducing participants to the Tableau platform
- Developing skills in data visualization
- Building advanced skills in Tableau
- Enhancing data analysis skills
- Collaborating with others on Tableau projects
Lead Instructor
Dr. Sarah Chen
PhD in Computational Mechanics from MIT with 15+ years of experience in Industrial AI. Former Lead Data Scientist at Tesla and current advisor to Fortune 500 manufacturing firms.
Limited SeatsClosing Soon
Tableau for Business Intelligence
Professional Certification Program
๐ฅ
FormatLive + Recorded
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Duration8 Weeks
๐
CertificationVerified
Module 4
Module 1: Introduction to Tableau and Data Visualization Basics
- Getting Started with Tableau: Installing and navigating the Tableau interface, understanding Tableauโs capabilities.
- Introduction to Data Visualization: Principles of effective data visualization, types of charts and when to use them.
- Connecting to Data Sources: Importing data from various sources like Excel, CSV, and databases.
Module 5
Module 2: Data Preparation and Cleaning in Tableau
- Data Connection and Preparation: Handling data sources, joining, blending, and pivoting data.
- Data Cleansing Techniques: Filtering, renaming, and working with metadata for clean, usable data.
- Basic Calculations and Data Aggregation: Applying simple calculations and aggregations, understanding calculated fields.
Module 6
Module 3: Building Basic Visualizations
- Core Chart Types in Tableau: Creating bar charts, line charts, scatter plots, and heat maps.
- Tables, Cross Tabs, and Text Visuals: Displaying data in tables, using crosstabs for analysis.
- Enhancing Visuals with Labels and Tooltips: Adding contextual information to visualizations for clarity.
Module 7
Module 4: Advanced Visualizations and Customization
- Advanced Chart Types: Funnel charts, Pareto charts, bullet graphs, and waterfall charts.
- Geographic Mapping: Creating maps, customizing geographic data, and using maps in BI contexts.
- Using Parameters and Control Elements: Dynamic filtering, input controls, and parameter-driven visualizations.
Module 8
Module 5: Interactive Dashboards and Storytelling
- Dashboard Design and Layout: Principles of dashboard layout, adding interactive elements.
- Dashboard Actions: Using filters, highlight actions, and URL actions for interactivity.
- Storytelling with Data: Creating a story with Tableau, navigating through steps and enhancing narrative flow.
Module 9
Module 6: Data Analysis and Calculations in Tableau
- Advanced Calculations: Using calculated fields, date functions, and logic statements.
- Table Calculations and Level of Detail (LOD) Expressions: Applying table calculations, creating LOD expressions for deeper analysis.
- Trend Lines, Forecasting, and Statistical Analysis: Adding trend lines, forecasting future values, and interpreting statistical summaries.
Module 10
Module 7: Performance Optimization and Best Practices
- Data Optimization Techniques: Managing large datasets, using extracts, and optimizing data connections.
- Dashboard Performance Optimization: Improving load times and performance with best practices.
- Publishing and Sharing: Publishing dashboards to Tableau Public and Tableau Server, best practices for sharing.
Module 11
Module 8: Case Studies and Capstone Project
- Industry Case Studies: Exploring real-world applications of Tableau in business.
- Capstone Project: Students develop and present a BI solution using Tableau, applying skills learned throughout the course.
Module 12
Who Should Enrol?
The course is suitable for data analysts, business intelligence professionals, managers, and anyone interested in leveraging data for decision-making. Basic familiarity with data handling and business processes is recommended but not mandatory.
Module 13
Program Outcomes
- Improved understanding of Tableau
- Ability to create data visualizations
- Improved data analysis skills
- Increased confidence in using Tableau
Module 15
What You’ll Gain
- Full access to e-LMS
- Real-world dry lab projects
- 1:1 project guidance
- Publication opportunity
- Self-assessment & final exam
- e-Certificate & e-Marksheet
Module 16
Join Our Hall of Fame!
Take your research to the next level with NanoSchool.
Module 17
Publication Opportunity
Get published in a prestigious open-access journal.
Module 18
Centre of Excellence
Become part of an elite research community.
Module 19
Networking & Learning
Connect with global researchers and mentors.
Module 20
Global Recognition
Worth โน20,000 / $1,000 in academic value.
Module 21
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