Combining-Predictive-Techniques
Projects Submitted for Udacity's Predictive Analytics for Business Nanodegree using Alteryx and Tableau.
Capstone Project Overview The capstone project has three main tasks, each of which requires you to use skills you developed during the Nanodegree program. Once you complete all three tasks, please submit the project as a PDF. Task 1: Store Format for Existing Stores Your company currently has 85 grocery stores and is planning to open 10 new stores at the beginning of the year. Currently, all stores use the same store format for selling their products. Up until now, the company has treated all stores similarly, shipping the same amount of product to each store. This is beginning to cause problems as stores are suffering from product surpluses in some product categories and shortages in others. You've been asked to provide analytical support to make decisions about store formats and inventory planning.
Task 2: Determine the Store Format for New Stores You’ve been asked to:
Develop a model that predicts which segment a store falls into based on the demographic and socioeconomic characteristics of the population that resides in the area around each new store. Use a 20% validation sample with Random Seed = 3 when creating samples with which to compare the accuracy of the models. Make sure to compare a decision tree, forest, and boosted model. Use the model to predict the best store format for each of the 10 new stores. Use the StoreDemographicData.csv file, which contains the information for the area around each store. Note: In a real world scenario, you could use PCA to reduce the number of predictor variables. However, there is no need to do so in this project. You can leave all predictor variables in the model.
Task 3: Forecasting Produce Sales You’ve been asked to prepare a monthly forecast for produce sales for the full year of 2016 for both existing and new stores. To do so, follow the steps below.
Data Used
StoreSalesData.csv - This file contains sales by product category for all existing stores for 2012, 2013, and 2014.
StoreInformation.csv - This file contains location data for each of the stores.
StoreDemographicData.csv - This file contains demographic data for the areas surrounding each of the existing stores and locations for new stores.