Tableau Assignment Help

Tableau Assignment Help

Get Professional Tableau Assignment Help Online for Data Analytics

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Tableau assists in simplifying the raw data in a very understandable format. It is a powerful and fastest-growing visualization tool used in the business intelligence industry. Tableau is utilized by many government organizations, businesses, academic researchers, and visual data analysis. It gives a desktop, server, and hosted software. Tableau permits users to connect, explore, and visualize their data.

Tableau is the most straightforward application to examine, visualize and operate data. It is one of the most capable software used for hold or manipulating big data. Tableau augments learning and teaching using a quick and easy to use visual analytics platform.

Significance of Tableau: -

  • Tableau permits students to increase their analytical skills.
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  • Tableau offers the component of connecting to the information source. Ex: - MS Excel

Products of Tableau Used for Tableau Assignment Help for Data Visualization

  1. Tableau online: -Tableau Online is a cloud established product utilized for content sharing. It is also used for content sharing. Tableau online assists in offering business intelligence in the cloud.
  2. Tableau Server: -Tableau server is used for association purposes in various organizations. Through this, you can track the usage.
  3. Tableau Desktop: -Tableau desktop allows data-driven decisions to conduct calculations, decode complex statistics, and identify trends. It is mostly for personal use.
  4. Tableau Public: -It is liberally available that enables the general public, such as journalists and bloggers, to post interactive articles online.
  5. Tableau Reader: -Tableau reader is a product that lets the user read saved files on the desktop computer. It is obtainable free of cost, and the information saved is secure and confidential.

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Sample of Tableau Assingment Help Solved by Our Tableau Assignment Experts

What to upload? As your lab work for this week, upload your R script for the first exercises (Question 1) only. 

1.	You are the Western Power manager responsible for sourcing coal for the Muja power station.  The Muja power 
station has a capacity of 850MW and is the largest power station in Western Australia.  The Muja power station 
is a critical part of the State’s electricity infrastructure.  There are two coal mines in Collie that are 
approximately equidistant to the power station.  These coal mines are the Griffin Coal mine, owned by Lanco; 
and the Premier coal mine, owned by Yancoal.  You have been tasked with deciding if a single contract should 
be given to one mine or if each mine should be given a supply contract.  The delivered price of coal will be 
the prevailing market price, so the key difference between the coal from the two mines is the ash content.  

If there is no difference in the ash content of the coal from each mine you will give each mine a contract as 
diversity in supply is preferred.  However, if there is a difference in the ash content, you will give the contract
 to the supplier with the coal that has the lowest ash content.  The Premier v Griffin data file contains 
 measurements, expressed in percentage terms, on the ash content of the coal from random samples at each mine. 
 Conduct a structured test to determine if the ash content for the two samples are the same or not.    

a.	Calculate the mean and sample standard deviation for each set of ash content measurements.  

b.	Create an appropriate plot for the data.  Rather than rely on the default column headings as the group names 
in your plot use “Premier coal” and “Griffin coal” as the group names.  That means you will need to use the names 
argument to rename the groups in your plot.

c.	Conduct a formal test to compare the ash content of the coal from the two mines, and make a decision about 
whether you should issue one supply contract or two supply contracts.  If you decide you should issue only one 
supply contract, specify which coal mine will get the contract.

Upload required for exercise above:
Upload the complete R script you used for the exercises above (a, b, and c) along with the accompanying commentary
or documentation. (You do not need to upload the plot generated by the script – only the script is to be uploaded). 
The upload should include :
(i)	Data exploration and what the exploration suggests (This is parts (a) and (b) above)
(ii)	The null and alternative hypotheses for the tests you did
(iii)	The significance level (or alpha value) for the tests
(iv)	The implementation the tests 
(v)	The interpretation of the results (Is the null rejected/accepted? And why)