Week 2 - Business Intelligence Architecture and Data Warehouse Design

Week 2 - Business Intelligence Architecture and Data Warehouse Design

Info iconThis preview shows pages 1–2. Sign up to view the full content.

View Full Document Right Arrow Icon
Data Warehouse Design: Understanding Star Schema Defining Schema: A Review | Operational Database Schema | Star Schema | Comparing Operational and Data Warehouse Database Design | Snowflake Schema | Summary Defining Schema: A Review The term schema probably is not new to you. In BIS-245: Database Essentials for Business (or BIS-240: Database Decision-Making for Business) you learned how to design database schema (or database designs, to use a simpler term) that modeled business situations requiring data storage. These designs used tables that were joined to other tables creating a network of tables that were related to each other in various ways, such as one-to-one, one-to-many, many-to-one and many-to-many relationships. Each table had a primary key, which is simply a column that uniquely identifies each row in the table. Usually, this is an internally generated number that ensures each row has a unique identifier. Tables that were related to each other also used foreign keys -- a primary key value from another table that was stored in a related table. These foreign keys allowed you to create queries and reports that would pull together information from related tables. Below is an example of a database schema that shows multiple tables joined by primary and foreign key relationships: Operational Database Schema The databases you have worked with so far have been considered operational databases. Operational databases hold data that companies use in their day-to-day operations as they interact with customers and suppliers, employees, and other stakeholders in the business. As such, they undergo a significant amount of alteration using action queries like the kind you created in Week 1's iLab -- Insert, Update, and Delete queries. As a result, they are designed to optimize update, insert and delete queries through normalization. Normalization is the process of removing redundancy from a database design, ensuring that data is stored in one place only. This prevents errors, and speeds up action queries -- an important feature when a customer is updating their information online, or when an employee needs to update company data quickly. Operational Databases and Data Anomalies
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Image of page 2
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 01/18/2010 for the course BIS 445 taught by Professor Ward during the Fall '09 term at DeVry Cincinnati.

Page1 / 3

Week 2 - Business Intelligence Architecture and Data Warehouse Design

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online