Group 11 analyzed sales data from Dominick's Finer Foods stores to answer business questions. They extracted data from flat files into staging tables then transformed and loaded it into a data warehouse with dimensions for time, store, and product, and a fact table for store sales. Reports and OLAP cubes were created in SQL Server Analysis Services and SQL Server Reporting Services to analyze the impact of factors like season, holidays, and promotions on sales and profits by product and store. Significant effort was required to cleanse the large raw data, design the data marts, implement the ETL process, and generate reports and analyses.
2. Business Questions
1. What is the difference in sales of products in different
stores? Which customer segments visit these stores and
thereby contribute to their buying?
2. What effect does the time of year have on the sales of each
product category? Determine if seasons impact sales on
product type
3. What are the differences between the average monthly sales
for each product taking into account the different prices at
each store?
4. What impact do holidays have over sales? Which product
categories are impacted the most?
5. What stores have increased revenue margins over the last
five years?
6. What stores have increased revenue margins over the last
five years?
4. ETL Process
BQ: What is the effect of promotions in increasing the overall sales of
a product?
Extraction
◦ Source - Flat Files : Movement , Demographic and WeekDecode
◦ Data Staging – Used SSIS to create temporary tables, clean data,
create temporary Dimensions: DimTime, DimStore, DimProduct
and temporary Fact table : FactStoreSales Tables
Transformation
◦ Derived attributes were added using SSIS- Weekly Sales, Month,
Year, Holiday Period
Loading
◦ Load the Dimensions and Fact tables to Data warehouse area.
6. OLAP Particulars
BQ: What impact do holidays have over Sales? How does the change
in sales affect the profits during holiday period?
SSRS Over SSAS
SSAS – Create data source view, create cube, dimensional hierarchy
and deploy to SQL Server Analysis Services.
SSRS – Create report using SSRS over the SSAS
Deploy to Infodata.tamu.edu/reportserver
7. Effort
Analyze Data and come up with business questions
◦ Most effort expended as data was huge and had dirty data
◦ Used excel graphs to analyze if solutions to questions were feasible with given
data
Revise Business question and design the data marts
◦ Design dimension and facts measures. Group them to create four data marts to
answer all business questions.
Create Staging and Data warehouse database and implement ETL
◦ Involved heavy effort to extract, transform and load huge data.
Create reports and Analyze the business questions
◦ Used SSAS, SSRS, SSAS+SSRS, Report Builder 2.0