Houston E-Retailers Presented BY: Bala AnuDeep Guduri (LEAD)
Kavya Hegde Divya Gangwani Suhas Malavalli Background HOUSTON E-RETAILERS, INC is a startup E-Retail store based in Houston,Texas and carries various products from different famous franchisees for anumber of internationally recognized brands likeDr. Pepper under Beverages,Proctor and Gamble for Toys and Cosmetics and many more. The company is mainly an E-Retail business which is looking on to expand itscustomer base and also grow their business and compete amongst theircompetitors in the E-Retail market. Business Need To build a long-term relationship with the customer.
To run a profitable operation which typically means increasing revenue whilelimiting the expense. To analyze the transactional data and finally drive the company towards thesuccess by making effective strategic decisions. Use effective tools or techniques which help in analyzing the data and producereports to know the trending for past and the upcoming years. Why Data Warehousing ? Houston e-retailers being a startup company needed an appropriate technique ortool to drive the company towards success. Hence a well designed data warehousing that would feed our business with theright information at the right time in order to make strategic decisions in e-retailenvironment is needed. This technique is useful for generating reports and analyzing the collected dataover years. How Would Houston E-Retailers Benefit from Data Warehouse?
This would make us aware of the past and future trends with regards to customerpurchase, the product sales and many more by analyzing the data collected overthe years. Knowing the sale of a particular product under a particular category at a giventime that would facilitate in increasing the revenue for the future years. Finally, an important benefit being that its facilitates or company to provide theright product to the customer when they want. Reports Overall yearly sales report based on Product Category
Sales Report based on Gender Sales Report based on Gender and Customer Age group Quarterly Sales Report based on Customer Age group and Gender Sales Report based on Product category, Customer Age group and Gender Dimensional Model Star SCHEMA Customer Product ProductCategory
Fact_Sales Vendor Date Dimensional MODEL Dimension Tables Customer Dimension: (In SQL Server and Access DB) Dimension Tables Vendor Dimension:(In SQL Server and Access DB) Dimension Tables Date Dimension: (In SQL Server and Access DB) Dimension Tables Product Dimension: (In SQL Server and Access DB) Dimension Tables Product Category Dimension: (In SQL Server and Access DB) Dimension Tables Fact_Sales Dimension: (In SQL Server and Access DB) Workflow EXCEL Access DB SQL Server & BI
E-Retail data collected from an online site Files where in Excel format Created few of our own tables like Product Category, Fact Sales Access DB Imported the Excel files into Access DB Created their Relationship in form of a star schema SQL Server & BI Access DB files imported into MS SQL Sever (SBUS-DB) as Ecommerce-Retailers. Using Visual Studio BI, created a Cube for our Ecommerce-Retailers database. Generated reports appropriately as required. Date Dimension Created hierarchies in order to navigate easily between various level attributeswithin the date dimension. Further an attribute relationship was created within the hierarchy. Product Dimension Created hierarchies in order to navigate easily between various level attributeswithin the date dimension. Further an attribute relationship was created within the hierarchy. Customer Dimension Named Calculation:
Created an Age column in the Customer dimension Reports Following reports have been generated using the cube:
Sales Report Gender and Age Based Sales Report Product Sales Report Report 1 Yearly Sales Report based on Product Category Conclusion:
From the report we can inferthat cosmetics sales are high ina fiscal year which is 7, with is 21 % of over all sales ofHouston E-Retailers Report 2 Sales Report based on Gender Conclusion:
From the report we caninfer that female customersare making more purchasesthan male customers and thepurchasing trend for thisfemale group is increasing. Report 3 Sales Report based on Gender and Customer age group
Conclusion: From the report we can inferthat Female customers underthe age group generatemore sales than the othergroup. Report 4 Quarterly Sales Report based on Customer Age group and Gender
Conclusion: From this we can infer that thecustomers under the age group for both the gendershave to be looked up upon toretain them in the future years. Report 5 Sales Report based on Product Category and Customer Age group Conclusion We have build a data warehouse specifically for our company, the Houston E- Retailer from the data that we collected. We have successfully developed a cube which gives an organized andsummarized data which is current or collected over the years. We have also learnt generating different reports according to our requirement andanalyzing the measures for a given criteria. On an overall note, the project was really a learning and interesting experiencefrom the start to finish. Thank You Comments or Queries?