Data-Science-With-Tableau

Welcome to my Data Science with Tableau Portfolio.
This repository documents part of my Data Science Journey.
You can find me on Tableau Public.
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Project start date: January 2022
Project updated: March 2022
Portfolio: Tableau Public Gallery
Data Sources: Data

Comparing Multiple Measures in Views

Challenge: I'm preparing a report for management. They want to see how the sales forecast compares to actual sales. In this hands-on-activity, I have built a combined axis chart to answer the question:

How does Budget Sales compare to actual Sales over the last few years?

The Dashboard and story can be found here:

Using Scatter Plots To Show Relationships Between Measures

Challenge: I have been asked to create a view for my company that compares average sales with average marketing expenses, broken down by product type, state, and area code, to see if there is a relationship. I have built a scatter plot to answer this question:

What is the relationship between average marketing expenses and average sales?

The Dashboard and story can be found here:

Creating Spreadsheet-like Views Using Text Tables

Challenge: I have been asked to create a text table that shows the average sales for each product within my company’s three departments across four sales regions. This will help users determine:

Which region has the highest average sales for each product within each category and sub-category?

The Dashboard and story can be found here:

Showing Breakdowns of the Whole Using Pie Charts

Challenge: I have sales data that I want to present using two pie charts, one showing sales by customer segment and one showing sales by region.

I used two different methods to create my charts.

The Dashboard and story can be found here:

Showing Breakdowns of the Whole Using Tree Maps

Challenge: I'm looking at my organization’s sales data, and I want to see the relative contribution of each product category and region to your total sales. T

To determine this, I built a tree map.

The Dashboard and story can be found here:

Using Bar-in-Bar Charts and Bullet Graphs to Compare Measures

Challenge 1: I have sales data for office products. To compare 2018 and 2019 sales for product category and sub-category

I have built a bar-in-bar chart that shows 2018 sales as a small bar on top of 2019 sales as a larger bar.

Challenge 2: Using data about coffee and product sales, I wanted to compare the actual sales to projected sales, and I wanted to see sales as a bar over distribution areas marking 50%, 75% and 100% points.

I added a line to mark the quota (projected sales), and used color to show whether a product met quota.

The Dashboard and story can be found here:

Creating Symbol and Filled Maps

Challenge:I'm working with passenger data for European airports, and I’d like to determine which airports were the busiest during a span of time.

Using the three-character IATA airport industry codes, I created a symbol map of the airport data, using size and color to compare the number of passengers for each airport in 2021. I limited map clutter by leveraging tooltips and removing unnecessary map layers. I added a filter to the view to help show which airports were the busiest.

The Dashboard and story can be found here:

Creating a Density Map

Challenge:I'm working with a data set of hail storm damage reported in Minneapolis, Minnesota, and I’d like to identify the neighborhoods with the most reported storm damage.

I created a density map of the street address locations of the reported hail storm damage, adjusted the combination of Color, Intensity, and Size to make the trends more apparent.

The Dashboard and story can be found here:

Working with String and Type Conversion Functions

Challenge: I have data that contains information about students. You would like to create a field, Student Name and ID that contains:

• The student’s last name in all capitals
• The student’s first initial
• The student’s ID
• A comma and space after the last name, a period and space after the first initial, and the fixed string "ID:" and a space before the ID number. For example, for the student Glen Adams, ID# 596, you would like the data to display as follows:
  

ADAMS, G. ID: 596

The Dashboard and story can be found here:

Using Histograms and Box & Whisker Plots to Show Distribution

Challenge 1: I have data on student test scores, and I want to see the distribution of scores to understand how many students earned each score.

I built a histogram with a bin size of 10. Then, to see more detail, I edited the bin size to 5. Finally, I edited the tick marks to match the bin size.

Challenge 2: I wanted to compare the distribution of SAT scores in each state, broken down by year and subject.

To accomplish this, I created a box & whisker plot that shows the year and subject of the test results, and used the Analytics pane to show the distribution of state values.

The Dashboard and story can be found here:

Creating Relationships between Tables

Challenge: I am trying to find which of my customers has the most purchases (transactions) for a new store I opened called Wholesale Carbonated Beverages. I also want to know the quantity sold for each of my products. I have two Excel spreadsheets as my data sources. One contains sheets or tables for Products and Customers, and the other contains Transactions.
I need to connect to these two data sources, create relationships between the various tables, and build two visualizations to answer these questions:

Which customer had the most purchases?

What was the best-selling product?

The Dashboard and story can be found here:

Building a Dashboard

Challenge: I have created some views to show sales by segment, region, and profit. I wanted to be able to monitor and share all three views at once, and answer the following questions.

Which category of the product has the lowest profit in different regions?

Which countries and segments are generating negative profit?

The Dashboard and story can be found here:
I also wanted to share this dashboard with my manager and colleagues so that they can explore the data in the dashboard and find their own insights. To improve its usability and exploratory capabilities, I added interactivity to the dashboard by:

• Using the pie chart as a filter to drill down on data
• Making the Market filter global so that the filtering applies to all views
• Using the Segment color legend to highlight important data
  

Creating Interactive Dashboards Using Actions

Challenge: I need to create an interactive dashboard that allows users to get the following information about the 2014 Olympics:

• Which country earned the most medals?
• Which sport earned Canada the most medals, and which sport earned the most gold medals?
• Which sport earned the USA most medals? I created two filter actions, one that allows me to see the total medals by sport for each country and another that shows the medal winners for individual sports. I also added a Go to Sheet action to see additional details about each athlete who won medals in various sports.

Telling Stories with Data

Challenge: Profit in the Furniture department of my company is very low, although sales are high compared to other departments. After analyzing the data, I have found that Table sales in the Eastern region have been deeply discounted. I created a data story to present your findings.

Using Context Filters to Limit Scope

Challenge: I am creating a view that showcases the top 10 products sold in each category. I built a view that filters the products to the top 10, and then creates a context filter to show the top 10 products in each category.

Using Calculated Fields

Challenge: I have two sets of data: One has club membership data and the other shows total sales by member. I need to create a bar chart that shows how long the member with the greatest sales has been with the club. To do this, I use a cross-database join and then a join calculation to add sales information on the members.

Blending Data Using Custom Relationships

Challenge: I have separate data sources for sales and quota data. I need a view that shows sales for each sub-region in the US as bars. The I use the quota from the other data source to create reference lines. Finally, I create a calculation to show whether sales have met quota, and use it to color the bars.

Replacing Data Sources for Views

Challenge: I created the Sales and Profit by Customer view. It uses the Superstore 2016 2019 data source. An updated data source is available, Superstore 2018 2021, and I want to update the view to use this new data source.

After I download the starter workbook and new data source, I add the data source to the workbook. Modify the new data source to avoid potential impacts to the view. Then replace the data source, and resolve remaining impacts to the view.

Aggregating Dimensions in Advanced Calculations

Challenge: I am trying to create a strategy to increase profitability for a franchise of coffee shops. I would like to create a view that clearly organizes the profitable and unprofitable product categories. To do this, I will need to use a calculated field that contains an aggregated dimension.

Writing Table Calculations in the Calculated Field Editor

Challenge: My marketing team launches an annual campaign at the end of Q1 each year.

I want to show the growth of orders compared to Q1 of that year compared to the total number of customers. I use a LOOKUP function and a helper function when creating that calculated field. .

Using Level of Detail Expressions

Challenge: I want to show the average profit of each product sold, compared to average sales in each market and category. I use a FIXED calculation to show the average profit by product, and create a dual axis chart that compares these values to average sales.

Using Fixed LOD Expressions for Cohort Analysis

Challenge: I know that sales have been improving every year, but I want to know which group of customers contributed the most to overall sales, and how well I am retaining customers. I create a FIXED LOD expression to calculate a customer’s first order date, and use this field to see how each cohort purchases across each market and year.

Making Projections with Trend Lines and Forecasts

Challenge: I am the sales manager for a U.S. territory. I would like to see trend lines for Sales versus Profit in each of your company’s product categories. I would also like to segment the data to compare these trends across each region of the U.S. To do this, I create a scatter plot to compare Sales versus Profit. Then, I create panes using the Category and Region dimensions. This creates a group of charts that share the same axes and scales, referred to as small multiples. The small multiples enable me to compare trends across dimensions, Category and Region in this example, in a single view. What trends across categories and regions can you determine for sales and profit?

Using Parameters to Swap Measures

Challenge: My audience would like to analyze multiple measures related to Superstore's products. They want to see totals for profit and sales, respectively, over time. To enable my audience to see each measure separately in the view, I'll provide dynamic selection by creating a parameter so they can switch between the measures they’d like to see in this view.

Challenge: I have created a second parameter to give people even more control and flexibility by allowing them to change the aggregation type on the measure they select.

Add Location Data

Challenge: I want to add the location of the distribution center for each of the four regions on the map. I'll need to duplicate a field, and edit the location to create the view. Then I can create a map that shows the amount of traffic seen in each distribution center.

Customizing Geocodes for Addresses

Challenge: I own an Events Planning business and I would like to create an interactive map that displays event sites and the number of events at each location. My data is recorded in two separate data sources so I will need to blend the data.

Plot Data on an Image

Challenge: I have data about workplace injuries, and you want to show which injuries are most common. To do this, I'll use a custom background image for my map and plot the injury locations data on top of the image.

Navigating Between Dashboards

Challenge: I have dashboards for two divisions of my organization that use two different data sources. I want to create a filter that applies to both dashboards, so that when I filter by Region on one dashboard, a link is created to the other dashboard that filters it by the selected regions. I also want to create a navigation button back to the original dashboard.

Data Preparation

"Data preparation is the process of manipulating data into a form for further analysis. This manipulation includes cleaning, shaping, or combining it with other data sources. Regardless of its source, most data needs cleaning and shaping to optimize it for analysis." - Tableau

Clean data and produce an output file

Types of Data

Flat Files:

• PDFs
• Microsoft Excel workbooks, such as XLSX files.
• Text files, such as Comma Separated Values (CSV) files
• Statistical files, such as RDATA and SAS files

Tableau Data Extracts:

• .tde
• .hyper

Tableau Published Data Sources:

• Tableau Server
• Tableau Online

Databsases:

• Microsoft SQL Server
• Oracle
• PostgresSQL
• Google BigQuery