Develop appropriate plots to characterise data

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Reference no: EM133797549

Data-driven Forecasting

Assessment - A Forecasting Project

Your Task
Apply forecasting techniques to a given dataset and provide a business application of the forecasts.

Assessment Description
You will be provided with a dataset and a detailed assessment brief on the day of the assessment.
The data provided for the assessment are a time series of monthly sales revenue for two stores.
The objective of the assessment is to use Exploratory, Tableau, and Excel software to:
describe the time series
develop Prophet and Holt-Winters demand forecast models for the two stores
compare forecasts from these models.

Assessment Instructions

In class: You will be presented with a dataset in class. As a group, analyse the dataset using Tableau and Exploratory.io.

You will provide an oral presentation of the group work in parts A to D during the third hour of the workshop.

The data set will be posted or emailed to you at the beginning of class in Week 5.
After Class: Individually perform a follow up analysis, based on a different data set, and which will include the use of Excel. Submit your report and Excel file. This component of the assessment is to be submitted via Turnitin, within 48 hours of midnight of the day of your class in Week 5.

As a group:
You will be provided with a dataset and a detailed assessment brief on the day of the assessment. Get solution now!

Load data into a BI tool

Develop appropriate plots to characterise data.

Develop forecasting models and model evaluation metrics.

Prepare a PowerPoint presentation with your answers. Include screenshots showing how you use the software, and of the information provided by the software.

Present your slide deck in class in the final hour.

Submit your slide deck via the Turnitin portal + zip your data files along with the analytics model files and submit them via the File Submission portal at the end of the allocated time. Uploading files to the incorrect place or not uploading the data/model files late/at all will be treated as poor project management practice and penalised accordingly.

As individuals:
You will be provided with a dataset and a detailed assessment brief on the day of the assessment.

Divide your dataset into train and test data.

Plot training series plus HW forecasts for the test year in Tableau.
Plot training series plus Prophet forecasts for test year in Exploratory.
Selecting from statistics given in Tableau and Exploratory, construct a table of RMSE within the training series by method by store.
Make calculations in Excel and construct a table of RMSE in the test series by method by store.
Comment on the statistics observed in the above steps.
Make calculations in Excel and find the MASE.

Note: You must submit your individual report before midnight on the second day after your class in Week 5.

Reference no: EM133797549

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