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Chapter 5-1. Chapter 5-2 Chapter 5: Organizing and Manipulating the Data in Databases Introduction Normalization Validating the Data in Databases Extracting.

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Presentation on theme: "Chapter 5-1. Chapter 5-2 Chapter 5: Organizing and Manipulating the Data in Databases Introduction Normalization Validating the Data in Databases Extracting."— Presentation transcript:

1 Chapter 5-1

2 Chapter 5-2 Chapter 5: Organizing and Manipulating the Data in Databases Introduction Normalization Validating the Data in Databases Extracting Data From Databases: Data Manipulation Languages (DMLs) Object-Oriented Databases, Multimedia Databases, and Data Warehouses

3 Chapter 5-3 Normalization Most data organized in flat files  No sequence or order  Difficult to find records  Difficult to use data efficiently Normalization  Process of examining and arranging file data  Allows for more efficient use of data  Avoid problems accessing and modifying

4 Chapter 5-4 Unnormalized Data

5 Chapter 5-5 First Normal Form In First Normal Form (1 NF) when:  All data fields are well defined  Data can be stored in a flat file Problems  Data redundancy  Insertion anomaly  Deletion anomaly

6 Chapter 5-6 First Normal Form Example

7 Chapter 5-7 Second Normal Form In Second Normal Form (2 NF) when:  It is in 1 NF  All data items depend on primary record key Benefits  More efficient design  Eliminates data redundancy

8 Chapter 5-8 Second Normal Form Example

9 Chapter 5-9 Third Normal Form In Third Normal Form (3 NF) when:  It is in 2 NF  Does not contain transitive dependencies  Data field A does not determine data field B Ultimate Goal  Create database in 3 NF

10 Chapter 5-10 Third Normal Form Example

11 Chapter 5-11 Database Management Systems Overview  Not a database  Separate software system Functions  Enables users to utilize database information more efficiently Examples  Access, Alpha 5, dQuery, Lotus Approach

12 Chapter 5-12 Data Validation Data Definition Language (DDL)  Enables users to define record structure  Define individual fields of each record Example

13 Chapter 5-13 Tools for Data Validation Proper Data Types for Fields Input Masks  Limit data to specific formats Default Values  Data fields of new records

14 Chapter 5-14 Tools for Data Validation Drop-Down Lists Validation Rules  Create rules than limit range of values that may be entered Referential Integrity  Deleting of information disallowed when it would disrupt references

15 Chapter 5-15 Drop-Down List Example

16 Chapter 5-16 Validation Rule Example

17 Chapter 5-17 Creating Referential Integrity

18 Chapter 5-18 A database is in the third normal form (3 NF) if it is second normal form and: A.All the data attributes in a record are well defined B.All the data attributes in a record depend upon the record key C.The data contain no transitive dependencies D.The data can be stored in two or more separate tables Study Break #1

19 Chapter 5-19 A database is in the third normal form (3 NF) if it is second normal form and: A.All the data attributes in a record are well defined B.All the data attributes in a record depend upon the record key C.The data contain no transitive dependencies D.The data can be stored in two or more separate tables Study Break #1 - Answer

20 Chapter 5-20 An example of a validation rule is: A.An input value must be an integer B.An input value must also have a default value C.An input value must be between 0 and 40 D.You cannot delete parent records that have child records associated with them Study Break #2

21 Chapter 5-21 An example of a validation rule is: A.An input value must be an integer B.An input value must also have a default value C.An input value must be between 0 and 40 D.You cannot delete parent records that have child records associated with them Study Break #2 - Answer

22 Chapter 5-22 Extracting Data From Databases Schema  All information in a database  All relationships of the tables  Map of entire database Subschema  Subset of the schema

23 Chapter 5-23 Creating Select Queries Queries  Create customized subschemas Dynaset  Dynamic subset of a database  Created by queries  Data Manipulation Language (DML)

24 Chapter 5-24 Query Example

25 Chapter 5-25 Creating Select Queries One-Table Select Queries  Creates a dynaset  Based on:  Criteria determining which records to include  Criteria determining which fields to include from those records  Single or Multiple Criteria

26 Chapter 5-26 Select Query Example

27 Chapter 5-27 Multi-Table Select Query Example

28 Chapter 5-28 Multi-Table Select Query Example

29 Chapter 5-29 Creating Action Queries Simple query Wizard Crosstab queries Find-Duplicates queries Find-unmatched queries Delete queries

30 Chapter 5-30 Creating Action Queries Append queries Sum a column Update queries Make-table queries

31 Chapter 5-31 Query Wizard Screen

32 Chapter 5-32 Guidelines for Creating Queries Spell accurately and be case sensitive Specify AND and OR operations correctly Tables must be joined properly Name queries systematically Choose data fields selectively

33 Chapter 5-33 Extracting Data From Databases Structured Query Language (SQL) Hypertext  Hypertext Markup Language (HTML) eXtensible Markup Language (XML)

34 Chapter 5-34 Extracting Data From Databases Online Analytical Processing (OLAP)  Complex, multidimensional data analysis  Pivot tables Data Mining  Utilize a set of data analysis and statistical tools  Identify relationships, patterns, or trends

35 Chapter 5-35 Pivot Table

36 Chapter 5-36 Object-Oriented Database Object-Oriented Database (OODB)  Contains text data  Information about set of actions taken on data field Multimedia Databases  Include graphics, audio information, and animation Multidimensional Databases

37 Chapter 5-37 Data Warehouses Pools of data from separate applications Characteristics  Free of errors  Defined uniformly  Span longer timeframe than transaction systems  Optimized data relationships

38 Chapter 5-38 All of the following are examples of action queries except: A.Update query B.Append query C.Delete query D.Find missing data query Study Break #3

39 Chapter 5-39 All of the following are examples of action queries except: A.Update query B.Append query C.Delete query D.Find missing data query Study Break #3 - Answer

40 Chapter 5-40 SQL is an example of: A.A tool to perform online analytical processing B.A database management system C.A query language D.A multimedia database Study Break #4

41 Chapter 5-41 SQL is an example of: A.A tool to perform online analytical processing B.A database management system C.A query language D.A multimedia database Study Break #4 - Answer

42 Chapter 5-42 Copyright Copyright 2010 John Wiley & Sons, Inc. All rights reserved. Reproduction or translation of this work beyond that permitted in Section 117 of the 1976 United States Copyright Act without the express written permission of the copyright owner is unlawful. Request for further information should be addressed to the Permissions Department, John Wiley & Sons, Inc. The purchaser may make backup copies for his/her own use only and not for distribution or resale. The Publisher assumes no responsibility for errors, omissions, or damages, caused by the use of these programs or from the use of the information contained herein.

43 Chapter 5-43 Chapter 5


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