• Introduction to Tableau Desktop:
• Overview of Tableau Desktop and its features.
• Understanding the Tableau interface and terminology.

• Connecting to Data:
• Importing data into Tableau from various sources (Excel, CSV, databases, etc.).
• Understanding data source connection options and considerations.

• Basic Visualization:
• Creating basic visualizations such as bar charts, line charts, scatter plots, and maps.
• Applying formatting and customization to visualizations.

• Working with Data:
• Data organization and structuring.
• Filtering and sorting data.
• Grouping and aggregating data.

• Advanced Visualization Techniques:
• Creating more complex visualizations such as dual-axis charts, treemaps, and heatmaps.
• Implementing reference lines, bands, and distributions.

• Calculations and Expressions:
• Introduction to Tableau Calculated Fields.
• Writing basic calculations (e.g., arithmetic calculations, string calculations, date calculations).

• Dashboard Creation:
• Building dashboards to combine multiple visualizations into a single view.
• Implementing interactivity with dashboard actions and filters.

• Data Blending and Joins:
• Working with multiple data sources and blending data.
• Understanding different types of joins and their implications.

• Advanced Data Analysis:
• Implementing advanced calculations using Tableau Calculated Fields and Parameters.
• Utilizing Level of Detail (LOD) expressions for complex analysis.

• Geospatial Analysis:
• Mapping geographic data in Tableau.
• Creating custom geocoding and using spatial files for analysis.

• Performance Optimization:
• Optimizing workbook performance for large datasets.
• Understanding Tableau data extracts and incremental refreshes.

• Advanced Dashboard Techniques:
• Designing interactive and responsive dashboards.
• Incorporating storytelling and guided analytics into dashboards.

• Data Connection and Basic Visualizations:
• Import a dataset (e.g., CSV, Excel) into Tableau Desktop.
• Create a bar chart to visualize sales by product category.
• Create a line chart to show trends in monthly sales.
• Add filters to interactively explore the data.

• Geographic Visualization:
• Use a geographic dataset (e.g., countries, states) to create a map visualization.
• Color code the map based on a measure such as sales or population.
• Drill down from country-level to state-level data using hierarchical filters.

• Advanced Visualizations:
• Create a dual-axis chart to compare two measures on the same axis.
• Build a treemap to visualize hierarchical data such as sales by product category and subcategory.
• Design a dashboard to display multiple visualizations together.

• Calculations and Expressions:
• Create a calculated field to calculate profit margin (profit divided by sales).
• Use a LOD (Level of Detail) expression to calculate the total sales regardless of filters applied.
• Implement a parameter to dynamically change the view (e.g., switch between different metrics).

• Advanced Analytics:
• Implement forecasting to predict future sales trends.
• Use clustering algorithms to segment customers based on their purchasing behavior.
• Apply trend lines and statistical models to analyze data patterns.

• Dashboard Design and Interactivity:
• Design a dynamic dashboard with interactivity (e.g., use of parameters, dashboard actions).
• Incorporate user input controls like dropdowns and sliders to filter data dynamically.
• Implement URL actions to link Tableau visualizations to external web pages or documents.

• Sales Performance Analysis:
• Analyze sales performance by region, product, and time period.
• Identify top-performing products and regions.
• Visualize sales trends and seasonality.

• Customer Segmentation:
• Segment customers based on demographics, purchasing behavior, or lifetime value.
• Identify key characteristics of each segment and tailor marketing strategies accordingly.

• Profitability Analysis:
• Analyze profitability by product line, customer segment, or sales channel.
• Identify low-margin products or unprofitable customer segments and recommend actions to improve profitability.

• Introduction to Tableau Server:
• Overview of Tableau Server
• Introduction to Tableau Server architecture and components.
• Understanding the role of Tableau Server in the Tableau ecosystem.

• Installation and Configuration:
• Installation prerequisites and best practices.
• Step-by-step installation and configuration of Tableau Server.

• User Management:
• User authentication options (local authentication, Active Directory, SAML).
• Managing users, groups, and permissions.

• Content Management:
• Publishing workbooks and data sources to Tableau Server.
• Managing projects and content permissions.
• Versioning and revision history.

• Tableau Server Administration:
• Server Administration Tasks:
• Monitoring server status and performance.
• Configuring server settings and resource management.
• Backup and restore procedures.

• Data Source Management:
• Connecting to data sources and configuring data connections.
• Managing data source permissions and connections.

• Security and Governance:
• Implementing security best practices.
• Enforcing data governance policies.
• Auditing and logging user activities.

• High Availability and Scalability:
• Configuring high availability and load balancing.
• Scaling Tableau Server for increased capacity.

• Advanced Topics:
• Customization and Integration:
• Customizing Tableau Server interface and branding.
• Integrating Tableau Server with other applications and services.

• Automation and Scripting:
• Automating server tasks using Tableau Server REST API.
• Scripting common administrative tasks for efficiency.

• Disaster Recovery and Failover:
• Planning and implementing disaster recovery strategies.
• Configuring failover and redundancy options.

• Setting Up Tableau Server:
• Installation and Configuration:
• Install Tableau Server on a virtual machine or server environment.
• Configure server settings, including authentication method (local, Active Directory, SAML).

• Adding Users and Groups:
• Add users to Tableau Server and assign them to appropriate groups.
• Configure permissions to control access to projects, workbooks, and data sources.
• Publishing Content to Tableau Server

• Publishing Workbooks:
• Publish a workbook from Tableau Desktop to Tableau Server.
• Set permissions for the published workbook to control who can view and interact with it.

• Publishing Data Sources:
• Publish a data source to Tableau Server.
• Configure data source permissions and refresh schedules.

• Managing Content on Tableau Server:
• Managing Projects:
• Create new projects on Tableau Server to organize content.
• Move workbooks and data sources between projects.

• Content Permissions:
• Modify permissions for existing content on Tableau Server.
• Assign permissions to specific users or groups for projects, workbooks, and data sources.
• Collaboration and Interactivity:
• Creating and Managing Comments:
• Add comments to workbooks and views on Tableau Server.
• Reply to comments and manage comment threads.
• Subscriptions and Alerts:
• Set up email subscriptions to receive scheduled updates of workbook views.
• Configure alerts to be notified when certain data thresholds are met.
• Monitoring and Administration:
• Server Status and Performance Monitoring:
• Monitor server status, including CPU usage, memory usage, and disk space.
• Identify performance bottlenecks and optimize server resources.
• Backup and Restore:
• Perform a backup of Tableau Server data and configuration.
• Practice restoring Tableau Server from a backup in a test environment.
• Security and Governance:
• Security Best Practices:
• Review and implement security best practices for Tableau Server.
• Ensure compliance with data governance policies and regulations.
• Auditing and Logging:
• Review audit logs to track user activity on Tableau Server.
• Analyze logs to identify security incidents or compliance issues.
• Scaling and High Availability:
• Scaling Tableau Server:
• Add additional nodes to scale Tableau Server for increased capacity.
• Configure load balancing to distribute traffic across multiple nodes.
• High Availability Configuration:
• Configure Tableau Server for high availability to ensure uptime and reliability.
• Test failover and disaster recovery procedures to ensure continuity of service.
• 
  

• Introduction
• Roles
• Snowflake Pricing
• Resource Monitor – Track Compute Consumption
• Micro-Partitioning in Snowflake
• Clustering in Snowflake
• Query History & Caching
• Load Data from AWS – CSV / JASON / PARQUET & Stages
• Snow pipe – Continuous Data Ingestion Service
• Different Type of Tables
• Time Travel – Work with History of Objects & Fail Safe
• Task in Snowflake – Scheduling Service

• Snowflake Stream – Change Data Capture (CDC)
• Zero-Copy Cloning
• Snowflake SQL – DDL
• Snowflake SQL – DML & DQL
• Snowflake SQL – Sub Queries & Case Statement
• Snowflake SQL – SET Operators
• Snowflake SQL – Working with ROW NUMBER
• Snowflake SQL – Functions & Transactions
• Procedures
• User defined function
• Types of Views

• Intro to Qlik View
• Installation of Qlik view
• Data Modelling in Qlik View
• Circular reference
• Link Tables to your model
• Joins in Qlik view
• ETL in Qlik View
• Handling Null Values
• Visualizations in Qlik View
• Pivot Table in Qlik View
• KPI Development in Qlik View

• Set Analysis in Qlik View
• Date functions
• What If analysis
• Calculated Dimensions
• Conditional Objects
• Securing your document and document tuning
• Cross tables
• Bookmarks
• Chart-level and script-level functions
• Security measures and access points in QlikView
• Integrating visualizations with dashboards

Tableau case studies illustrate the diverse applications and benefits of using Tableau for data visualization and analytics across various industries. Here are a few notable examples:

• Healthcare: A major healthcare provider used Tableau to analyze patient data from electronic health records (EHR). By visualizing patient outcomes, treatment effectiveness, and resource utilization, healthcare professionals could identify trends and insights that improved patient care quality and operational efficiency. Tableau dashboards allowed for real-time monitoring of key metrics, enabling timely interventions and informed decision-making.

• Retail and E-commerce: A leading e-commerce platform utilized Tableau to analyze customer purchasing behavior and enhance marketing strategies. By integrating data from website traffic, sales transactions, and customer demographics, analysts created interactive dashboards to track sales performance, identify popular products, and optimize promotional campaigns. Visualizations helped stakeholders understand customer preferences and market trends, leading to increased sales and customer satisfaction.

• Finance: A financial institution used Tableau to analyze financial data, monitor market trends, and manage risk effectively. Tableau dashboards provided insights into investment portfolios, asset performance, and market volatility, enabling portfolio managers and analysts to make data-driven decisions swiftly. Visualizing complex financial data allowed stakeholders to mitigate risks, optimize investment strategies, and comply with regulatory requirements.

• Education: A university leveraged Tableau to analyze student enrollment data, academic performance, and retention rates. By visualizing student demographics, course enrollment patterns, and graduation rates, administrators identified factors influencing student success and implemented targeted interventions. Tableau dashboards facilitated data-driven decisions to improve educational outcomes, allocate resources effectively, and enhance student support services.

• Manufacturing and Operations: A manufacturing company used Tableau to monitor production metrics, supply chain performance, and quality control processes. Visualizing real-time data on production yields, equipment downtime, and inventory levels helped managers optimize production schedules, identify bottlenecks, and reduce operational costs. Tableau dashboards enabled proactive management of manufacturing operations, improving efficiency and maximizing productivity.

These case studies highlight Tableau’s versatility in transforming raw data into actionable insights across different sectors. By visualizing data effectively, organizations can improve decision-making, enhance operational efficiency, and drive innovation in their respective industries. Tableau’s intuitive interface and powerful analytics capabilities empower users to explore data, uncover trends, and communicate findings that lead to tangible business outcomes.