
Build a clean, normalized e-commerce data model by creating dim customer and dim product tables and a central fact table, importing CSVs into MySQL via DBeaver, then connecting to Tableau.
Connect Tableau to MySQL, prepare a lightweight data model from five normalized tables, and create calculated fields like profit margin, return status, and discount status to drive dashboards and visualizations.
Create donut charts in Tableau to visualize profit by customer tier and sales by plan type, then build a month line chart for trends with clean formatting.
Create a monthly sales line chart in Tableau, compare top two categories with color-coded lines, filter by category, and adjust axes for clearer insights.
Create dashboard visualizations, including a map of sales and profit, a customer profit bar chart, an area chart by month with media type, and a discount line chart with filters.
Build the final sharpness dashboard by arranging KPI cards in a floating container, adjusting padding, and adding two donut charts, a highlight table, and a line chart across interlinked pages.
Extract actionable insights from the dashboard, such as platinum customers driving the most profit and premium plans delivering the most sales, with seasonal and country trends guiding discounts and advertising.
Begin building a real-world hr analytics dashboard with snowflake and tableau, transforming raw csv data into a four-dashboard, kpi-driven portfolio that reveals regional performance, profit, and satisfaction insights.
Import tables into the Snowflake analytics schema, load data from files, verify row counts, and create views joining dim and fact tables for HR analytics.
Create a Snowflake view from the hr analytics database and analytics schema, naming bw_hr_transactions, joining the fact and dim tables, and limit top ten rows for preview before tableau integration.
Connect Tableau to Snowflake, create customer events and HR transactions views in the HR analytics database, then build an executive summary dashboard visualizing profit, transaction count, revenue, and customers.
Create a dual axis bar and line chart to show hiring trends, adjust axes and labels, and then build a donut chart of job roles versus employees with clear labeling.
Learn to build highlight tables, bar charts, donut charts, and dual-axis charts in Tableau, counting employees by department and visualizing monthly revenue.
Learn to build Tableau dashboards with top 15 by profit bar chart, HR trend, dual axis department and transactions chart, and donut chart for profit by job role.
Create area charts and maps, differentiate event types by color, and build heat maps of regions versus department with profit; also design treemaps and dual-axis visuals comparing counts and revenue.
Build a Tableau dashboard with revenue, profit, and transaction KPIs, and visualize hiring trends, regional performance, and customer satisfaction through varied charts.
Create a main executive summary dashboard in Tableau using horizontal and vertical containers, a left-side work tab with navigation, KPI sections, and visuals such as hiring trends and revenue.
Explore a revenue analysis dashboard in Tableau with six visualizations—map, donut, scatter, stacked bar, histogram, and butterfly chart—to guide inventory and pricing decisions.
Develop data preparation and visualization skills in tableau by building a real-world dashboard that analyzes revenue by state, month, age, region, category, and gender from a CSV dataset.
Create and explore a Tableau dashboard of Seattle Airbnb data from Kaggle (2016), analyzing bedroom counts, prices, and seasonal revenue with zip code and map visualizations.
Build an Airbnb dashboard in Tableau by importing Excel data, linking listings and calendar, and visualizing average price by zip code with color-coded maps and labels.
Create a weekly time-series visualization of Airbnb revenue across the year, filter end dates, and compare bedrooms versus revenue to reveal which bedroom count yields higher average revenue, in dollars.
Create KPI cards for total casualties and fatal, serious, and slight casualties with current year and previous year comparisons and year-on-year calculations in a Tableau data analyst dashboard.
build sparklines for monthly accidents and casualties, compare current and previous year with synchronized axes, convert one to an area chart, adjust tooltips, and assemble a dashboard layout.
Explore data grouping techniques in Tableau by categorizing vehicle types into groups, creating weather and road-type pie charts, stacked bars, and location maps, with dashboard formatting and year filters.
Explore a final map dashboard in tableau that plots districts from latitude and longitude, refines tooltips with casualties and vehicles, and includes current-year filters.
Build a final Tableau dashboard using a heat map and density map of state and zip-code data to reveal top issues, daily complaints, with interactive filters and a trend line.
Explore interactive Tableau dashboards built from the Amazon Prime Video US statistics dataset, highlighting radial bar, donut, area, and stacked charts to analyze genres, release year, and country trends.
Learn to build and design a Tableau dashboard featuring top ratings radial bar, top ten genres, total shows by country and release year insights, while refining titles, colors, and layout.
Create and format donut, bar, and line charts while building a density map dashboard with tooltips to analyze incidents by location, severity, weather, and fatalities.
Import a video game sales dataset into Tableau, define dimensions and measures, and build a dual-axis sales by year and genre visualization using a zone parameter.
Create top ten sales visualizations in Tableau using filters, end date parameter, and study period to compare 2014 data, with bar charts and a tree map using zonal sales.
Create a total sales by genre dashboard in tableau by configuring filters, parameters, colors, and labels, then add text sheets for total names, platforms, and publishers.
Refine a tableau dashboard combining top ten names and platforms by sales with genre insights, and apply layout, colors, and interactive filters like zone and date range for exploration.
Data visualization and analytics are at the heart of every data-driven business decision today. This course is designed to help you gain practical, job-ready skills in Tableau by working on 12 real-world data analytics and dashboard projects across diverse industries.
Instead of focusing only on theory, you will learn by building professional dashboards step by step. Each project is based on real datasets from domains like e-commerce, HR analytics, revenue trends, rental markets, social media, safety analysis, customer feedback, streaming platforms, gaming, retail sales, and marketing strategy. These projects give you the opportunity to practice turning raw data into clear, interactive dashboards that provide actionable insights.
Along the way, you will also get hands-on practice with supporting tools like MySQL, Snowflake, and Excel to manage and prepare data before visualization. You will explore techniques like KPI design, advanced charts, parameters, filters, interactivity, and storytelling with dashboards, helping you go beyond the basics and build compelling visual analytics.
By the end of this course, you will have completed a portfolio of 12 dashboards, each demonstrating your ability to analyze data, identify trends, and communicate insights effectively. This portfolio will be a valuable asset when applying for roles in business intelligence, data analysis, and data visualization.
Whether you are looking to transition into data analytics, strengthen your Tableau expertise, or gain project experience to advance your career, this course provides everything you need to become a confident Tableau data analyst.