Complete Power BI Book
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Tableau Free Book
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How to choose a graph

Complete step-by-step syllabus of #Tableau for Data Analytics Preparation:-

Introduction to Tableau

Overview of Tableau's capabilities
Differences between Tableau Desktop, Tableau Server, and Tableau Public
Navigating the Tableau interface

Getting Started with Data in Tableau

Importing data from various sources (Excel, SQL, cloud platforms, etc.)
Live vs. Extract data connections
Data types and roles in Tableau
Organizing and managing data sources

Working with Data

Data transformation tools: split, pivot, group, create calculated fields, etc.
Handling missing data
Data blending and joining Level of Detail (LOD) expressions

Visualization Techniques

Basic charts: bar, line, scatter, pie, etc.
Advanced charts: waterfall, Pareto, treemap, histogram, etc.
Time series analysis
Geospatial analysis with maps
Interactivity with dashboard actions, filters, and parameters

Dashboard and Story Design

Organizing and designing dashboards for user experience
Best practices for visualization
Storytelling with data
Mobile dashboard design

Advanced Tableau Features

Sets and combined sets
Forecasting and trend lines
Clustering and data modeling
Reference lines and bands
Publishing and Sharing
Publishing to Tableau Public, Server, and Online
Managing users and permissions
Interacting with content on Tableau Server and Mobile Performance Optimization
Best practices for a speedy dashboard
Aggregating data and optimizing extracts
Efficient workbook design

Tips and Tricks Keyboard shortcuts

Utilizing Tableau's community and resources
Customizing Tableau's look and feel with style and formatting options

Real-world Projects and Case Studies

Practice datasets and project scenarios
Portfolio development

MUST ADD these 5 POWER Bl projects to your resume to get hired

Here are 5 mini projects that not only help you to gain experience but also it will help you to build your resume stronger

📌Customer Churn Analysis
🔗 https://www.kaggle.com/code/fabiendaniel/customer-segmentation/input

📌Credit Card Fraud
🔗 https://github.com/sahidul-shaikh/credit-card-fraud-

📌Movie Sales Analysis
🔗https://www.kaggle.com/datasets/PromptCloudHQ/imdb-data

📌Airline Sector
🔗https://www.kaggle.com/datasets/yuanyuwendymu/airline-

📌Financial Data Analysis
🔗https://www.kaggle.com/datasets/qks1%7Cver/financial-data-

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Simple guide

1. Data Utilization:
- Initiate the process by using the provided datasets for a comprehensive analysis.

2. Domain Research:
- Conduct thorough research within the domain to identify crucial metrics and KPIs for analysis.

3. Dashboard Blueprint:
- Outline the structure and aesthetics of your dashboard, drawing inspiration from existing online dashboards for enhanced design and functionality.

4. Data Handling:
- Import data meticulously, ensuring accuracy. Proceed with cleaning, modeling, and the creation of essential measures and calculations.

5. Question Formulation:
- Brainstorm a list of insightful questions your dashboard aims to answer, covering trends, comparisons, aggregations, and correlations within the data.

6. Platform Integration:
- Utilize Novypro.com as the hosting platform for your dashboard, ensuring seamless integration and accessibility.

7. LinkedIn Visibility:
- Share your dashboard on LinkedIn with a concise post providing context. Include a link to your Novypro-hosted dashboard to foster engagement and professional connections.

Hope this helps you