ACC 3202 ch13

Foreign 13 45 relational databases normalization

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Unformatted text preview: 13-46 The Need for Normalized Data The Need for Normalized Data The process of converting data into tables that meet the definition of a relational database is called data normalization. ► Seven rules of data normalization, additive. ► Most relational databases are in third normal form. ► First three rules of data normalization are: 1. Eliminate repeating groups 2. Eliminate redundant data 3. Eliminate columns not dependent on primary key. Chapter 13-47 SO 5 The need for normalization of data in a relational database The Need for Normalized Data The Need for Normalized Data Relational databases consist of several small tables. Small tables can be joined in ways that represent relationships among the data. Exhibit 13-6 Relational Database in Microsoft Access Bolded field is the primary key. Chapter 13-48 SO 5 The need for normalization of data in a relational database The Need for Normalized Data The Need for Normalized Data Relational database has flexibility in retrieving data. Structured query language (SQL) has become the industry standard. SELECT Customers.CustomerID, Customers.CompanyName, Orders.OrderID, Orders.ShippedDate FROM Customers INNER JOIN Orders ON Customers.CustomerID Orders.CustomerID; Chapter 13-49 Exhibit 13-7 Relational Database in Microsoft Access SO 5 The Need for Normalized Data The Need for Normalized Data Trade-offs in Database Storage Relational database ►Not most efficient way to store data that will be used in other ways. ►Most organizations are willing to accept less transaction processing efficiency for better query opportunities. Chapter 13-50 SO 5 The need for normalization of data in a relational database Use of a Data Warehouse to Analyze Data Use of a Data Warehouse to Analyze Data Management often needs data from several fiscal periods from across the whole organization. Exhibit 13-8 The Data Warehouse and Operational Databases Chapter 13-51 SO 6 Data warehouse and the use of a data warehouse to analyze data Use of a Data Warehouse to Analyze Data Use of a Data Warehouse to Analyze Data Management often needs data from several fiscal periods from across the whole organization. ► ► Identify the data ► Standardize the data ► Cleanse, or scrub, the data ► Chapter 13-52 Build the data warehouse Upload the data SO 6 Data warehouse and the use of a data warehouse to analyze data Data Analysis Tools Data Analysis Tools Data mining is the process of searching for identifiable patterns in data that can be used to predict future behavior. Online Analytical Processing (OLAP) is a set of software tools that allow online analysis of the data within a data warehouse. Analytical methods in OLAP usually include: 1. Drill down 2. Consolidation 5. Exception reports 3. Pivoting Chapter 13-53 4. Time series analysis 6. What-if simulations SO 7 The use of OLAP and data mining as analysis tools Distributed Data Processing Distributed Data Processing Early days Centralized processing Centralized databases Today’s IT Environment Distributed data processing (DDP) Distributed databases (DD...
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This note was uploaded on 03/30/2014 for the course ACC 3202 taught by Professor Baron during the Spring '12 term at CUNY Baruch.

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