This assessment will test your ability to build an application using data and statistical modeling in R or Python with Shiny.

For this assessment, we have included a file titled Data.xslx which is a dataset that contains time series data with product sales information.

The goal of this exercise is to take a dataset that contains time series data and generate a 24-month sales forecasting application using Shiny.

Your requirements for this assessments are:

1. Create a plot of the dataset in Shiny and deploy it to a test server.

2. Overlay a Holt-Winters Seasonal forecasting model with the data and extrapolate it for 24-months.

3. Calculate and display performance metrics of the model so the user knows how accurate the model is. You can decide what metrics to show.

4. Create a function to allow the user to upload a new dataset to replace the current one and update the forecast.

5. Bonus: Add additional forecasting models and allow the user to select a different model to see if it's more effective.

You will need to deploy the application to the web (https://www.shinyapps.io/) and provide us with the link to review.

In addition, post your code to a private Github repository and provide the user hd-assessments-review with read-only access to the code.

Do not commit the dataset in the repository, and ensure that your repository is private.

You will need to present the application and explain its functionality to a Hire Digital Technical Recruiter.