Data Analytics Project And Industry Experience

Categories: Data Analytics
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About Course

A Tableau Desktop Data Analyst plays a vital role in transforming raw data into actionable insights that drive business decisions. In this role, analysts combine technical expertise in Tableau with strong analytical thinking and communication skills.

Here are the typical responsibilities of a Tableau Desktop Data Analyst in the industry:

Core Responsibilities

  • Data Analysis – Use Tableau Desktop to explore datasets, uncover trends, and identify patterns or correlations.

  • Data Visualization – Create clear, interactive, and engaging dashboards to communicate complex insights simply.

  • Dashboard Development – Build and maintain user-friendly dashboards that empower decision-making across teams.

  • Data Integration – Connect Tableau to various sources (databases, spreadsheets, cloud services) for unified analysis.

  • Data Preparation – Clean, transform, and aggregate data in Tableau to ensure accuracy and consistency.

  • Performance Optimization – Tune workbooks and dashboards for speed and responsiveness.

  • Data Modeling – Create calculated fields, sets, groups, and parameters to support deeper analysis.

  • Collaboration – Work closely with data engineers, scientists, and business stakeholders to meet analytical needs.

  • Documentation – Maintain clear records of workflows, data sources, and calculations for team knowledge sharing.

  • Training & Support – Help business users understand Tableau best practices and empower them for self-service analytics.

  • Staying Updated – Keep pace with Tableau’s latest features and adopt them in day-to-day work.

  • Quality Assurance – Validate dashboards and analyses to ensure reliable and consistent insights.

  • Problem Solving – Troubleshoot issues related to data quality, visualization design, or performance.

  • Ad Hoc Analysis – Respond quickly to urgent reporting or one-off analysis needs.

  • Data Governance – Follow organizational standards for security and compliance when working with sensitive data.

Building Skills for This Role

To step into a Tableau Desktop Data Analyst position, it’s important to progress from basic visualization skills to intermediate and advanced analytics techniques. Our structured pathway prepares you for the role:

  1. Tableau Desktop Basics – Learn visualization fundamentals and Tableau’s interface.

  2. Intermediate Tableau Desktop Skills – Build interactive dashboards, parameters, and advanced calculations.

  3. Advanced Tableau Desktop – Master optimization, data blending, advanced visuals, and integration with R/Python.

  4. Tableau Desktop Data Analyst – Prepare for real-world analyst responsibilities with end-to-end projects and role-based skills.

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What Will You Learn?

  • Data Analysis: Utilize Tableau Desktop to perform in-depth analysis of data sets, identifying trends, patterns, and correlations.
  • Data Visualization: Design and develop visually appealing and interactive dashboards using Tableau Desktop to communicate complex data insights in a clear and concise manner.
  • Dashboard Development: Create and maintain Tableau dashboards that provide actionable insights to stakeholders, ensuring they are user-friendly and intuitive.
  • Data Integration: Integrate data from various sources into Tableau Desktop for analysis, including databases, spreadsheets, and other data repositories.
  • Data Cleansing and Preparation: Cleanse and prepare data for analysis within Tableau Desktop, including data transformation, aggregation, and cleansing to ensure accuracy and consistency.
  • Performance Optimization: Optimize Tableau Desktop dashboards and workbooks for performance, ensuring fast load times and responsiveness.
  • Data Modeling: Develop data models within Tableau Desktop to support complex analyses and calculations, including creating calculated fields, sets, and parameters.
  • Collaboration: Collaborate with other team members, including data engineers, data scientists, and business stakeholders, to understand data requirements and deliver actionable insights.
  • Documentation: Document Tableau Desktop workflows, data sources, and calculations for future reference and knowledge sharing within the team.
  • Training and Support: Provide training and support to users on Tableau Desktop best practices, tips, and tricks to empower them to explore and analyze data effectively.
  • Stay Updated: Stay updated with the latest Tableau Desktop features and enhancements, incorporating them into workflows to improve efficiency and effectiveness.
  • Quality Assurance: Conduct quality assurance checks on Tableau Desktop dashboards and analyses to ensure accuracy, reliability, and consistency of results.
  • Problem Solving: Troubleshoot and resolve issues related to data analysis, visualization, and performance within Tableau Desktop.
  • Ad Hoc Analysis: Perform ad hoc analysis and reporting requests using Tableau Desktop to address immediate business needs and inquiries.
  • Data Governance: Adhere to data governance policies and standards when working with sensitive or confidential data within Tableau Desktop.

Course Content

Choosing the right type of chart for analysis

  • Comparison of Values
    00:00
  • Correlation between measures
    00:00
  • Comparing exact values
    00:00
  • Comparing two measures
    00:00
  • Visualizations for Distributions
    00:00

Design aspects of a dashboard

Visual best practices

Industry Project (Example 1: Data Pipelines dashboard)

Industry Project ( Sales Dashboard)

Multi-Fact Relationship Data Model for Support Case Analytics

Governance

Assessment

Webinars and Live Sessions

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