Reference no: EM133857868
Assessment Details for Assessment Item: Report - Design business intelligence system and data warehouse
Introduction
In this independent assessment, you will leverage the case study presented in Assessment Item 1 as a foundation for your tasks.
Develop the architecture for a business intelligence system and formulate a data warehouse framework.
Employ visual analytics to convey your discoveries. Your work will be presented in the format of a report.
The assignment relies on the dataset found in the file Assignment1_RetailStore_Dataset.xlsx, which can be downloaded from LMS. Case Study: Retail Store Data Set:
The proliferation of supermarkets in densely populated urban regions has intensified market rivalry. This dataset contains historical sales information from a supermarket enterprise, encompassing records from three distinct branches during a three-month timeframe. Employing predictive data analytics methods with this dataset is easily accessible and uncomplicated.
Data Description:
The "Data Description" sheet describes all the variables used in the "Retail Store Dataset" and is copied below for your convenience. Invoice id: Computer generated sales slip invoice identification number
Branch: Branch of supercenter (3 branches are available identified by X, Y and Z). City: Location of supercenters
Customer type: Type of customers, recorded by Members for customers using member card and Normal for without member card. Gender: Gender type of customer
Product line: General item categorization groups - Electronic accessories, Fashion accessories, Food and beverages, Health and beauty, Home and lifestyle, Sports and travel
Tasks:
Let's break down the key components of this assessment:
you have access to a dataset that contains information related to a retail store. This dataset likely includes data on sales, customer information, inventory, and other relevant aspects of the retail business.
Designing Business Intelligence (BI) System and Data Warehouse Framework:
Your first task is to design the architecture of a Business Intelligence (BI) system and a data warehouse framework.
Business Intelligence System: A BI system is a set of tools and technologies that help in gathering, processing, storing, and analyzing data to provide valuable insights to support business decision-making. Your role in this assessment is to plan and design the structure and components of this system. You'll need to decide how data will be collected, processed, and presented to the end-users.
Data Warehouse Framework: A data warehouse is a central repository of data that is specifically designed for querying and reporting. You'll need to define how data from the retail store dataset will be stored in the data warehouse. This involves decisions regarding data modeling, ETL (Extract, Transform, Load) processes, data storage technologies, and overall architecture.
B. Utilizing Visual Analytics: Visual analytics is a process of analyzing data through interactive and visual methods such as charts, graphs, and dashboards. In this assessment, you are expected to use visual analytics techniques to analyze the retail store dataset. This means you'll be creating visual representations of data to uncover insights, trends, and patterns. Your findings should help us to understand the retail business better.
Your design of the BI system and data warehouse framework, explaining the rationale behind your choices.
Visualizations and insights obtained from the retail store dataset using visual analytics techniques.
Any recommendations or conclusions drawn from your analysis.
The report should be well-structured, clearly written, and include visual aids like charts or graphs to support your findings.
Following the successful completion of these tasks using the appropriate tools, produce an analytical report that leverages visual analytics to convey the insights uncovered to the Retail Store Directors.
The report should span roughly 2000 words (excluding references), adhere to 1.5 line spacing, and employ a 12-point Times New Roman font. Make use of both numerical and graphical statistical summaries, as certain insights may become apparent through one form of representation that might not be evident in the other.