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Loginworks Softwares

CASE STUDY

 

Objective:

The purpose of this visualization is to visualize the retails data and optimize in one page to large amount of data. Retails has continued to retain the top position on the Fortune 500 list for a consecutive fifth year. The brand has continued to grow based on its everyday low prices strategy and has taken fast advances into the digital market.

The core of retail’s business model is price leadership. The brand has led the US retail market through its lowest prices. Today, it operates more than 11000 physical stores in 28 countries and has eCommerce websites in more than 11 countries. The focus of retails is now on creating a seamless experience for its customers whether they are shopping from their mobiles or in the stores.

Four Important factors driving growth of retails
• Large sales volume made possible by a large customer base and scale of operation.
• A highly efficient supply chain system that maximizes productivity and reduces outlays.
• Low operational and overhead costs
• Use of bargaining power to grab the least prices from the suppliers (a very important strength for a large scale retailer that plays the most important role in its price advantage).

 

Overview:

We have scraped a data of retails store and created the representation in the graphical format for the easy result sets. We can filter out all the columns in visualization that show the relation of two or more columns.

 

Stages in completion of this project:

We have gone through various stages for the completion of this project. Each and every team member is involved in this project and has done a great job to fulfill their responsibilities.

Initial Stage:

We scraped Walmart store for zip 27513. We have 30 columns in this file and row depending on all product of particular location.
Columns are: id, site, zip, date, image link, price, Price_Mult, Eprice, Indicator, alt price, AltpriceMult, Ealtprice, Alt Indicator, pack, unit, uom, size, product_id, upc, asin, category, description, note, rating, valid, page image, aisle, orig_upc, job_number, sale_enddate

Some columns should not be blanks like id,site,zip,date,description,page image,UPC ,job number but remaining column should be blanks . If require details are not on the website then they should be blanks.

Data is show on below screenshot:

 

 

 

Planning Stage:

All columns of data sets are related to each other, Now we have to create the visualization graph that will show the result sets in easy based on particular selected value of the column.

Implementation and Execution Stage:

All columns are interrelated to each other. We have created the relation between the given columns in following steps:

1. We can show the category count in below graph if we click on one category it will show the count of that particular category.

This graph represents sub_category of main_category.

 

 

2. This graph represents the count of price of particular indicator. If we select any indicator then it show the count of price.

 

Team Meeting:

We also conducted daily stand up meeting to discuss the progress of the project, also we have discussed all the issues in this project and came up with the solution for those issues. The team members also involved in discussion with each other to make sure that the quality of the project can be maintained.
Also, the project manager has assigned the daily tasks to all the team and collect the reports on a daily basis for the status of those tasks.

Before delivering the set of features to the client we have conducted a review session, to review all the visualization steps to check the quality of reports and also the test execution report.

 

Ongoing stage:

This visualization graph represents the summary of data in one page. This is Dashboard of Walmart data for many locations. All graph in this dashboard are interrelated to each other. In this dashboard we can select any location or any product. This dashboard is showing the result set of particular selected variable like category,indicator v/s price, UPC details,description and price.

 

Summary:

This was the visualization steps of Walmart data that is representing the relation of two or more columns.

 

How Can We Help You?

Write to us at sales@loginworks.com to find how we can assist you as well with our data services to resolve the complexities of your project.

 

 

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