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Tableau is one of the premier data visualization tools used for data analysis and business intelligence. In the field of data science, business intelligence, and data analytics, proficiency in Tableau is a fundamental requirement. It holds a key role for students aiming to excel academically. As students delve into this subject, understanding Tableau's core concepts is challenging, appearing as a formidable task. To succeed in this domain, understanding data exploration, calculations, and data security is key for revealing meaningful insights from datasets. At TutorBin, we recognize the significance of these concepts and are dedicated to providing tailored Tableau homework help to support your academic journey.

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Challenges Where Students Need Tableau Assignment Help

1. Data Visualization Proficiency:

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2. Complex Tool Interface:

Tableau's powerful interface can be overwhelming. Understanding and guiding through its multiple features and options can be challenging for students, making it difficult to create compelling visualizations.

3. Data Connection and Cleaning:

Integrating and cleaning data from various sources is a fundamental aspect of Tableau. Students face difficulties in connecting to databases, preparing data, and handling messy datasets, which are essential for creating accurate visualizations.

4. Formula and Calculations:

Crafting custom calculations and formulas in Tableau poses a challenge. Students will struggle with formulating these calculations correctly, impacting the accuracy of their analyses and visualizations.

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Proficiency in data aggregation is crucial. Students must comprehend how to summarize and group data effectively. Misunderstanding aggregation can lead to inaccurate results in assignments.

6. Interactivity and Dashboard Design:

Creating interactive and user-friendly dashboards can be daunting. Students need to grasp how to design dashboards that clearly convey insights and allow end-users to explore data effortlessly.

7. Limited Data Access:

Students encounter difficulties in acquiring relevant datasets for their Tableau assignments. Availability of data, especially for specific topics, can be limited, forcing students to work with incomplete or irrelevant information.

8. Software Updates and Versions:

Tableau regularly updates its software, which can lead to compatibility issues with older versions. Students might face difficulties when their assignments require specific software versions or features that are no longer supported.

Tableau Topics & Concepts Covered

TOPICS CONCEPTS
Data Connection Data Sources, Preparation, Blending
Data Visualization Charts, Graphs, Maps
Data Exploration Sorting & Filtering
Dashboard Design Interactivity and User Experience
Data Preparation Data Transformations & ETL
Calculations Level of Detail (LOD) Expressions
Server & Sharing Publishing & Sharing Workbooks
Advanced Analytics Clustering & Segmentation

Tableau Homework Help

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Recently Asked Tableau Questions

Expert help when you need it
  • Q1:Analyze our team: How many salespeople are meeting their goal? Who are the top 4 performers? After we identify them, we can assign them as mentors to the rest of our salesforce. We have 28 total salespeople, so each mentor will get 7 people. List our top 10 most profitable stores? What are they selling? What is the income level in that area? That can help us predict what will sell in other areas. Where do most of our orders come from? (Look at our sales channels) Analyze our products: What are our top 5 bestsellers, in terms of profit? What are our top 5 bestsellers in terms of popularity? Analyze our market: Who are our top 5 customers, in terms of profit? What are these customers buying? Rank our regions in terms of profitability. What items are most popular in each region. Rank our states in terms of profitability. What items are most popular in each state? For each region: What products are bringing in the most money? What items are most popular? We want to keep these regions stocked with those products. For each state: What products are bringing in the most money? What items are most popular? We want to keep these regions stocked with those products. What about seasonal trends? Are some products more popular at certain times of the year than others?See Answer
  • Q2:Deliverables: 1) Go through the dataset (excel file). 2) Go through the "question instruction file" 3) Create visualisation in Tableau. 4) Write a story identifying injury pattern of two age groups (young and old) and suggest how to avoid such injuries for these groups. 5) Write 1 page for each group. EACH STORY MUST CONTAIN THE USE OF MULTIPLE PRODUCTS AND BODY PARTS.See Answer
  • Q3:Part 1: Creating a Simple Dashboard with Bokeh Layouts For the US Census Income dataset, create a dashboard that shows: • Age Distribution Marital status Distribution Working Class Distribution • Education Distribution Your Dashboard Should: 1. Use Bokeh Library with Layouts. 2. Select proper color, opacity and width for the bar charts. 3. Space the four figures evenly on the html page. 4. Maximize Data-Ink Ratio for each plot./nPART 2 - Need to use Tableau for below In this set of activities, we will see how calculated fields can be used to perform simple data processing, mainly for data slicing & dicing for visualization purposes. All activities are done on the US Census Income DatasetLinks to an external site.. Activity 1: Visualizing Income by Age Group We want to create a visualization to show the income within different age groups. The age groups are defined as follows: ● People younger than 20 years People in their 20's People in their 30's People in their 40's People in their 50's People older than 60 years. To create these age groups in tableau, we will create a calculated field. The final visualization should look like this:/nActivity 2: Summarizing Marital Statuses The US Census dataset contains a categorical attribute: marital status that can take one of these values: • Married-civ-spouse, Divorced, Never-married, Separated, Widowed, Married-spouse-absent, • Married-AF-spouse. There are three different types of married statuses. We would like to create one married category for the three types. Essentially, we want to summarize the marital status attribute into these categories: • Never Married • Married Divorced Widowed/nPart 3: Creating Interactive Dashboards using Parameters & Calculated Fields Part 3: Guidelines: For each problem below, submit the following: A brief explanation of what you did. Screenshots of any parameters and/or calculated fields that you have created, showing the actual code for the calculated fields. • The final dashboard with maximized data ink ratio: o Text/values on top of marks o No unnecessary axes o No repeated axis labels o No repeated axis values Problem 1: Using a Parameter to Create a Top-N Filter Suppose that you have a bar chart that contains many bars. You would like to allow the user to have the option of showing the top-n bars only, for some value n that the user specifies. This will make the dashboard interactive, meaning that the user can change what is displayed. In this activity we will show how parameters can be used to create a top-N filter and add interactivity to a dashboard. Create a Top-N Filter for a bar chart For the U.S. Census Income datasetLinks to an external site., create a visualization for the different countries of origin, excluding the U.S.. Then create a top-n filter that allows the user to select the number of countries they want to show, starting with the country/nActivity 4: Using a Parameter to Filter Multiple Views The World Population dataset file shows the population of different countries and regions of the world over multiple years. In this lab, you will create a dashboard that compares the populations of the different regions for the years 2011 vs 2020. You will create a dashboard that contains two visualizations, one for each year. The dashboard should contain a control that allows the user to filter the views to show the numbers for a certain country. The dashboard should also allow the user to show the complete data for all countries. Follow these steps: 1. Download the dataset file. 2. Open the dataset file in tableau. 3. Create a new sheet. Name it "2011". Create a bar chart that shows the populations for the different countries in 2011. 4. Create a new sheet. Name it "2020". Create a bar chart that shows the populations for the different countries in 2020. 5. Create a parameter "Country" as a string and load it with the country values from the data source. 6. Make sure to show the parameter control by right clicking on the parameter and selecting that option. 7. For the "2011" sheet, create a filter that filters the view based on the "Country" parameters. 8. Repeat the same and create a filter for the "2020" sheet. 9. Create a new dashboard. 10. Drag both sheets into the dashboard.See Answer
  • Q4:Case Questions Here is a list of questions that you will be answering for this case. Complete instructions for how to construct the interactive Tableau dashboard are in the tutorial video that accompanies this project. Please read this student case handout in its entirety before starting the case. Use the data dictionary provided on page 1 of these instructions and the interactive Tableau dashboard file to answer the following questions: 1. What were total sales revenues for the 1st quarter of 2020? 2. What were the total sales revenues for the Medical category in the 3rd quarter of 2021? 3. Which product line had the highest sales in 2020 under the materials processing category? 4. What is the top product line for the Germany division in 2019? 5. In 2021, which quarter had the highest sales in the Telecom category, under the UK Division? What was the dollar amount? 6. Who is KAT Manufacturing's top customer in the 4th quarter of 2019? 7. Who is the top customer for the Germany division in 2021? 8. If you were on the top management team of KAT Manufacturing, what overall strategy questions could this dashboard help you address? Answer this in your video assignment!See Answer
  • Q5:Question 6 (This relies on the file iris.csv that can be found in LumiNUS. Use that file to avoid problems associated with different versions.) p-norms are used to measure the distance between multi-dimensional data points and the origin. For a n-dimensional data point x = (X₁, X2, ..... Xn), the p-norm is given by: 11/p n ΣX₂² k=1 See: https://en.wikipedia.org/wiki/Lp_space#The_p-norm_in_finite_dimensions Here we will, for each type of flower (setosa, versicolor, and virginica), measure the distance between each data point in the 1-norm, 2-norm, and 3-norm from the mean of each of the factors: Sepal Length, Sepal Width, Petal Length, and Petal Width. So each data point is in 4-dimensions, and the distance from each data point from the mean from is in 4-dimensions The number of data points where the (component-wise) difference of the data point from the mean for its flower type has a p-norm less than or equal to 1.5 is: Type of Flower \p setosa FLAG QUESTION versicolor virginica 2 FYI: Depending on which items were selected for this assignment in this semester, there may or may not be another question that tells you do do the exact same thing for with a different threshold. So create your visual accordingly. Note: The 1-norm is the Manhattan distance, which is quite relevant in transportation operations in cities. The 2-norm is the usual straight line distance. In analytics work, it is common to generalise well known metrics.See Answer
  • Q6:Question 7 (This relies on the file iris.csv that can be found in LumiNUS. Use that file to avoid problems associated with different versions.) p-norms are used to measure the distance between multi-dimensional data points and the origin. For n-dimensional data point x = (X1, X2, ..., Xn), the p-norm is given by: setosa 11/p See: https://en.wikipedia.org/wiki/Lp_space#The_p-norm_in_finite_dimensions Here we will, for each type of flower (setosa, versicolor, and virginica), measure the distance between each data point in the 1-norm, 2-norm, and 3-norm from the mean of each of the factors: Sepal Length, Sepal Width, Petal Length, and Petal Width. So each data point is in 4-dimensions, and the distance from each data point from the mean from is in 4-dimensions The number of data points where the (component-wise) difference of the data point from the mean for its flower type has a p-norm less than or equal to 1.7 is: Type of Flower \p FLAG QUESTION versicolor virginica 1 1 2 2 3 FYI: Depending on which items were selected for this assignment in this semester, there may or may not be another question that tells you do do the exact same thing for with a different threshold. So create your visual accordingly. Note: The 1-norm is the Manhattan distance, which is quite relevant in transportation operations in cities. The 2-norm is the usual straight line distance. In analytics work, it is common to generalise well known metrics.See Answer
  • Q7:(This relies on the file Sample - Superstore.xlsx and postal-code-delivery-data.xlsx that can be found in LumiNUS. Use those files to avoid problems associated with different versions.) (This question might be viewed as the first of two independent parts of the Delivery from the Customer Perspective question. As the ordering of questions may not be sequential, you may want to check if the other independent part was included in the assessment this semester.) You are managing fulfilment at a nationwide retailer in the USA. You are interested in the customer experience but have limited data on fulfilment due to late adoption of supply chain management methodologies and technology. If an order ships the same day, we take the gap between ordering and shipping to be 0.25; if an order ships the day after it was ordered, we take the gap between ordering and shipping to be 1.25; if an order ships two days after it was ordered, we take the gap between ordering and shipping to be 2.25; and so on. There is data on average timings between orders being shipped and arrival at the customer's address in postal-code-delivery-data.xlsx. If there is missing data on the Average Delivery Lead Time (Days) (time from shipment to arrival at a customer's address) for a given Postal Code, you will fill in the missing value with 3.5, a conservative value for the entire country. Calculate the average End to End lead time between orders being placed and deliveries arriving at the customer address (in days) for the following states: Alabama: (1) • Arkansas: (2) • California: • Colorado: • Mississippi: Give your answers to 2 decimal places. Note: In this question, Ship Mode does not matter. SX int: Postal Codes can be tricky to work with. There is at least some postal code data for New Jersey and New Hampshire. Hint: Be careful to avoid double counting since there might be multiple rows from the same order.See Answer
  • Q8:SX Question 9 FLAG QUESTION (This relies on the file Sample - Superstore.xlsx and postal-code-delivery-data.xlsx that can be found in LumiNUS. Use those files to avoid problems associated with different versions.) (This question might be viewed as the second of two independent parts of the Delivery from the Customer Perspective question. As the ordering of questions may not be sequential, you may want to check if the other independent part was included in the assessment this semester.) You are managing fulfilment at a nationwide retailer in the USA. You are interested in the customer experience but have limited data on fulfilment due to late adoption of supply chain management methodologies and technology. If an order ships the same day, we take the gap between ordering and shipping to be 0.25; if an order ships the day after it was ordered, we take the gap between ordering and shipping to be 1.25; if an order ships two days after it was ordered, we take the gap between ordering and shipping to be 2.25; and so on. There is data on average timings between orders being shipped and arrival at the customer's address in postal-code-delivery-data.xlsx. If there is missing data on the Average Delivery Lead Time (Days) (time from shipment to arrival at a customer's address) for a given Postal Code, you will fill in the missing value with the current average across all orders in the state for which there is data (this has to be weighted against the number of orders). If there is no data for the entire state, then use 3.5, a conservative value for the entire country. Calculate the average End to End lead time between orders being placed and deliveries arriving at the customer address (in days) for the following states: • Alabama: • Arkansas: (2) • California: • Colorado: • Mississippi: 5 Give your answers to 2 decimal places. Note: In this question, Ship Mode does not matter. Hint: Postal Codes can be tricky to work with. There is at least some postal code data for New Jersey and New Hampshire. Hint: Be careful to avoid double counting since there might be multiple rows from the same order.See Answer
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