• Post category:StudyBullet-4
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RA: Supply chain applications series : Retail. Deploy a comprehensive analytics app with R & Shiny.

What you will learn

Build a retail dashboard from scratch!

learn how to use R to do retail analysis ad metrics calculation in real time.

work on a project like case study for mango incorportation.

deploy and scale the application using cloud service.

Description

Welcome to our latest course in the supply chain applications series, we are excited to share with RA: Supply chain applications with Shiny: Retail Analytics Which is the second course that dives deep into how to apply supply chain applications using R & Shiny. we already set the bar high after our previous course that discusses  deploying inventory applications  became a Bestseller . we aim at this course to meet the same standards.

we are proud to have more than 40,000 students across the globe taking our data science supply chain courses and that our courses were the first to discuss these topics thus our courses tend to be creative and unique in nature.

in this course, you will Deploy an end to end retail solution to mango incorporation, an apparel  retailer that have  four stores, each store has its own characteristics , assortment and popularity. in the solution that you will build for mango incorporation, it has to contain :

1-  An overall business overview dashboard.

2-  to brands dashboard.

3- top suppliers dashboard.

4- size curve and color curve dashboard.

5- historical sales dashboard.

6- Contributions dashboard.

7- Retail metrics dashboard.

8- Market Basket data.

9-Margins dashboard.

in addition, the  retail solution that you will provide to mango incorporation has to be :

1- Accessible from anywhere.


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2- Deployed on the cloud.

3- Process information real-time.

Sounds like a real project, right ? actually yes, it’s very much real project made by rescale analytics converted to a course.

Feedback from Clients and Training:

“In Q4 2018, I was fortunate to find an opportunity to learn R in Dubai, after hearing about it from indirect references in UK.

I attended a Supply Chain Forecasting & Demand Planning Masterclass conducted by Haitham Omar and the possibilities seemed endless. So, we requested Haitham to conduct a 5-day workshop in our office to train 8 staff members, which opened us up as a team to deeper data analysis. Today, we have gone a step further and retained Haitham, as a consultant, to take our data analysis to the next level and to help us implement inventory guidelines for our business. The above progression of our actions is a clear indication of the capabilities of Haitham as a specialist in R and in data analytics, demand planning, and inventory management.”

Shailesh Mendonca

Commercial lead-in Adventure AHQ- Sharaf Group

“ Haytham mentored me in my Role of Head of Supply Chain efficiency. He is extremely knowledgebase about the supply concepts, latest trends, and benchmarks in the supply chain world. Haytham’s analytics-driven approach was very helpful for me to recommend and implement significant changes to our supply chain at Aster group”

Saify Naqvi

Head of Supply Chain Efficiency

“I participated to the training session called “Supply Chain Forecasting & Management” on December 22nd 2018. This training helped me a lot in my daily work since I am working in Purchase Dpt. Haytham have the pedagogy to explain us very difficult calculations and formula in simple way. I highly recommend this training.”

Djamel BOUREMIZ

Purchasing Manager at Mineral Circles Bearings

English
language

Content

Introduction

Welcome
About RA
Introduction
What should be in a retail dashboard?
Why R ?
Shiny
Recommendations
Application Dynamics
Supply chain applications
Summary

Welcome To R

Introduction
What is R statistical language?
How to install R ?
How to install Rstudio ?
A walkthrough tutorial
Setup your project
Install Packages!
Summary

R programming fundmentals.

Introduction
Different data structures and types in R
Do arithmetic calculations in R and write functions
Creating a list
Importing data in R and basic explorations
Selecting data in a dataframe
Ifelse function
Conditions
conditions with functions
For loops
Applying a function inside a forloop
Forloop on a dataframe
Applying a function on dataframe
Basics of R assignment
Assignment explanation 1
Assignment explanation 2
Summary

Manipulating data in R

Intro
Intro to dplyr
Investigate with Dplyr
Unique invoices
average invoice per country
average number of items in an invoice
Joining
Changing date time to date
spreading the data /pivoting
Compressing the data
Separate and paste
putting it all together
Newyork airlines
Assignment 1
Assignment 2
Assignment 3
Assignment 4
Summary

Shiny Basics

Introduction
installing Packages
First shiny application
Our first UI
Input and output
Reactive app
Fibonacci assignment
Fibonacci sequence assignment
Declarative Vs imperative Programming
Getting unique identifiers
overview
User interface
App structre
Date reactivity
Country and SKU reactivity
Line plots
Application running
Datatables
Summary

Retail Metrics

what should be in a retail app ?
Operational retail metrics
Practice in excel
Margins vs Markups
Top and Bottom lines
Conversions rate
30 cents on the dollar
Margins Vs Markups
Supplier Dynamics with the retailer
summary

Market Basket

Intro
Intro to market basket analysis
Top 10 Products
Reading transactions
Summary transactions
Apriori
Top 10 rules
Subsetting
Assignment
summary

Retail Dashboard User interface

Libraries for the Application
Defining variables
Defining variables part 2
app layout
Sidebar panel
Mango overview Page
Summary-Suppliers-Brands-Items
Overview summary
Page 5 and 6
Price Distributions Page
Finalizing UI

Application- Main Page server

User Reactivity
All user reactivity
Summary reactive function
Summary reactive function for section
Our First interactive plots
Plots preview
Top function for ranking
arranging
Top_overall
overall plot
Plot ranking overview
plot overall
Downloading Data

Application( Page 2 to 8)

Supplier and Brand plots
input brush
Item summary
Line plots
Timeseries calibration
Price Curves
Size and color curve
Size and color preview
Contributions

Metrics , Margins and Basket analysis

Metrics
UPT,ATV and conversion
Margins main panel
Margins
Margin Plots
Basket function part1
Basket function part2
Basket function final
Workflow
Downloading mysql server
Installation
Initializing database
Sending data
App with database connection

VM for App

Azure free account
Deploying a Virtual Machine
Setting up server
Rstudio server
Essential libraries
Shiny server
Remote database connection
Is Everything working ?
Sudo R package installation
Uploading the retail app
making sure shiny is working

VM2 : mysql database

Introduction
setting up s new virtual machine
Connecting to a new virtual machine
Installing libraries
Mysql Configuration
Sending data to database
Connecting both virtual machines
Success
Final message