Data Analysis and Visualization with Tableau
Learn how to analyze and visualize data using Tableau like the experts do.
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Kirankrishna M
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ARJUN PP
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Meganath Prabu S
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SRITHARAN N
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Syllabus
This course is full of best-in-class content by leading faculty and industry experts in the form of videos and projects
Course Overview
As organizations rely on data to make informed decisions and drive business forward, data analysis and visualization using software tools such as Tableau have become core skills sought after in the industry. Through data visualization, organizations can draw inferences, compare data, identify errors, recognize patterns, and present all their findings in one place.
In this course, you will learn how to analyze, visualize, and draw inferences from a dataset using Tableau - a platform widely used in the industry to interactively visualize and present data. You will gain an established understanding of key concepts such as data types, sorting, blending, grouping, filtering, and table calculations. By taking this course, you will learn how to build a complete dashboard, while adhering to best practices followed in the industry. This course will progress into advanced calculations and analytics, nested Level of Details (LODs), dynamic designs, and Tooltip visualizations.
Throughout this course, you will work on projects that require extensive use of Tableau to develop dashboards which effectively present data. This will expose you to how datasets are analyzed and visualized in the industry.
Who can enrol in this course?
Students and working professionals with an interest in gaining industry-relevant data analysis and visualization skills.
Course Syllabus
On a daily basis we talk to companies in the likes of Tata Elxsi and Mahindra to fine tune our curriculum.
Week 1 - Introduction to Tableau
Tableau software allows businesses to clearly visualize, analyze, and report large data sets. In the industry, Tableau is a business intelligence tool used to make decisions supported by data. In order to develop effective dashboards and data visuals that can be studied and interpreted, learners must understand the UI and basic features.
This week will cover
- Basics and Installation of Tableau
- Types of Products and Roles
- Interface and Workflow
- Tableau Dashboards vs PPT
- Connecting to Data
- Data Source & its Types
- Live and Extracts Connections
Week 2 - Shelves, Cards, and Analytics Pane
The Tableau workspace has features such as shelves, cards, the Data Pane, Analytics Pane, toolbars, and menus. Each of these features has a specific function that learners must understand how to use when working with Tableau.
This week will cover
- Basics of Data Pane
- Quick Visualisations
- Marks and its Properties
- Pages Shelf
- Menu and Toolbar
- Analytics Pane
Week 3 - Data Types, Sorting, Grouping
As not all types of data are the same, Tableau supports 7 different data types, which can be sorted and grouped according to requirements. In order to present and organize data visually, learners should understand the features of Tableau related to data types and sorting.
This week will cover
- Sheet Interface
- Data Types
- Dimensions and Measures
- Sorting & Custom Sort and Grouping
- Sets & Combines Sets and Hierarchies
- Highlight Data
- Split & Custom Split
Week 4 - Filtering & Table Calculations
There are six different filters available for users on Tableau, each with their own unique function. By using filters, datasets can be condensed to illustrate concise information, thus improving the efficiency of dashboards. Data in a table can also be analyzed through performing table calculations. These features are essential for learners, as they can be used to develop efficient and concise dashboards.
This week will cover
- Filters, Filter Types, and Order Process
- Highlighted Data
- Context Filter and its Uses
- Calculated Fields
- Aggregations and their Uses
- Table Calculations
- Level of Detail Expression (LODs)
- Bins and its Uses
Week 5 - Complete Dashboard Building & Best Practices
Spreadsheets with data can be transformed into visually interactive dashboards that present the information. Dashboards can be combined with spreadsheets to tell a story and narrate performance through measured parameters. By learning the best practices, learners can design and develop effective dashboards and stories for businesses.
This week will cover
- Parameters
- Action Filters
- Dashboard Layout
- Sizing and Object
- Formatting
- Stories
- Best Practices
Week 6 - Distributing & Publishing
Tableau workbooks can be shared, exported, and published as required. As many individuals may work on a dashboard together, it is important for learners to understand how distribution and publishing work.
This week will cover
- Distribution
- Exporting
- Workbook File Types
- Publishing
- Replacing Data Sources
Week 7 - Joins and Blending
Tableau is also used to perform data blending and data joining. Through joining, data in tables and sheets from the same source can be combined. Data blending lets users combine data from different sources. It is important for learners to understand joins and blending as both are often required in the industry.
This week will cover
- Joins
- Inner and Outer Join
- Left and Right Join
- Blending
- Union
Week 8 - Relationships (2020.2 and Later Versions)
When analyzing data on Tableau, Relationships let you combine data from different tables. It is important for learners to understand how to work with multiple sets of data for effective analysis and visualization.
This week will cover
- Relationships
- Data Models
- Relationships vs Joins
- Creating and Optimizing a Relationship
- Types of Relationships
- Smart Aggregations and their Types
Week 9 - Data Preparations, Parameter & Set Actions
Before data is used in business intelligence, it goes through data preparation. This involves collecting, combining, and systematically organizing the dataset before it gets processed. It is important for learners to understand the parameters considered when preparing data.
This week will cover
- Pivot
- Custom Split
- Hide & Unhide Fields
- Sampling the Data
- Interactivity
- Parameter Actions
- Set Actions
Week 10 - Advanced Calculations and Analytics
When working with large sets of data, Tableau lets users perform advanced calculations and analytics to draw accurate inferences. It is important for learners to understand how to perform advanced calculations using Tableau to meet industry standards.
This week will cover
- Advanced Calculations
- Regular Expressions
- Table Calculations
- Use Cases
- Trend Lines
- Clustering and Forecasting
Week 11 - Nested LODs and Mapping Functions
Nested LOD is an advanced topic in Tableau that lets users assess data sets in-depth. Users can also build maps using Tableau, and understand the related data. As certain data sets may require mapping functions, and analysis in-depth, it is important to know about these concepts.
This week will cover
- Nested LOD and Use Cases
- Geo Mapping
- Geospatial Data and Use Cases
- Standard Maps
- Map Hierarchies
- Map Layers
- Background Maps
- Common Issues
Week 12 - Dynamic Designs, Extensions, and Tooltip Visualizations
Through dynamic designs, values in dashboards can automatically change when related data is modified. As it is common for data sets to have changing values, knowing how to work with dynamic designs is an essential skill for learners.
This week will cover
- Dynamic Designs
- Ways to Create
- Interactivity
- Extensions
- Tooltip in Visualizations
- Performance Recording
- Design Principles
Our courses have been designed by industry experts to help students achieve their dream careers
Industry Projects
Our projects are designed by experts in the industry to reflect industry standards. By working through our projects, Learners will gain a practical understanding of what they will take on at a larger-scale in the industry. In total, there are 2 Projects that are available in this program.
Developing a Dashboard on Tableau - Women in STEM Fields
Learners are required to develop a dashboard on Tableau with a given data set. The data set will have data about the women who graduated (year of graduation, number of employed women, those in STEM jobs, educational level, and salary comparisons). At the end of this project, learners are to deliver a dashboard that resembles an article predicting basic issues. It should be titled “Women in STEM Fields” and have pie graphs as well as comparisons regarding the statistics. Learners are also to write insights regarding the gender game in the STEM industry.
Developing a Dashboard on Tableau - Literacy Rate in Tamilnadu
Learners are required to develop a dashboard titled “Literacy Rate in Tamil Nadu” showing the female literacy population when compared to the total. It should depict the status of each city, and the scholarship/beneficiaries each State receives. The overall dashboard should be presented like an article predicting basic issues with titles and floating sheets where needed.
Our courses have been designed by industry experts to help students achieve their dream careers
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INR 40,000
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Instructors profiles
Our courses are designed by leading academicians and experienced industry professionals.
1 industry expert
Our instructors are industry experts along with a passion to teach.
8 years in the experience range
Instructors with 8 years extensive industry experience.
Areas of expertise
- Tableau
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