Exploratory Analysis and Classification – Data Analytics Assignment Help

Assignment Task

Part 1: Visualization
The following assignment is regarding an analysis of employee salaries. The original dataset is posted on Data.gov, but we have modified the dataset to suit the assignment.
In this assignment, you will need to download the “Employee_Salaries.xlsx” file, build a Tableau public dashboard and make a video of your insights. The Tableau dashboard should include:
1-    A map of the gross pay by zip code
2-    A bar chart of gross pay by gender
3-    A bar chart of gross pay by number of years being hired (hint: create a table calculation and find the difference in dates between todays date and first hired date)
4-    A tree map of overtime pay and department name
What to submit:
1.    Tableau public dashboard
2.    Video recording of your visualisation

Part 2: Exploratory Analysis and Classification

Problem Context
This dataset (diabetes.csv) is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective of the dataset is to diagnostically predict whether a patient has diabetes, based on certain diagnostic measurements included in the dataset. Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage.
Dataset Content
The datasets consist of several medical predictor variables and one target variable, Outcome. Predictor variables includes the number of pregnancies the patient has had, their BMI, insulin level, age, and so on.

Tasks:
1.    Using KNIME platform Examine Summary Statistics
2.    Build a Decision Tree Workflow in KNIME
3.    Create validation set: Split your dataset into two parts of train and test
4.    Train and build a Decision Tree Classification model on your dataset
5.    Evaluate the Performance of your Decision Tree Model by Generate a Confusion Matrix and Determine Accuracy Rate