Chapter 4: Organizing and Manipulating the Data in Databases Introduction Creating Database Tables in Microsoft Access Entering Data In Database Tables Extracting Data From Databases: Data Manipulation Languages Recent Database Advances and Data Warehouses

Creating Database Tables in Microsoft Access Database Management Systems An Introduction to Microsoft Access Creating Database Tables Creating Relationships

Database Management Systems (DBMS) Overview Not a database Separate software system Functions Enables users to utilize database information more efficiently Examples Access, SQL Server, mySQL, Oracle, DB2

Introduction to Microsoft Access A popular relational DBMS Used by many businesses and individuals Used for small database applications

Microsoft Access – Opening Screen

Creating Database Tables – Defining Record Format Field Name Names assigned to the data fields Data Type Specified for each data field Identifies how to store the data – field properties Description Optional field Defines record structures

Creating Database Tables – Opening Screen

Creating Database Tables – Record Format

Creating Relationships Purpose Link tables together Enable users to create multi-table reports Steps in Creating Relationships Select tables Link the tables

Creating Database Relationships – Linking Tables

Creating Relationships – Multitable Relationships

Creating Records Utilize datasheet view to input data

Ensuring Valid and Accurate Data Entry Data Definition Language (DDL) Enables users to define record structure Define individual fields of each record

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

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

Drop-Down List Example

Validation Rule Example

Creating Referential Integrity

Study Break #1 All of the following are examples of DBMSs except: Access Oracle DB2 SQL

Study Break #1 - Answer All of the following are examples of DBMSs except: Access Oracle DB2 SQL

Study Break #2 An example of a validation rule is: An input value must be an integer An input value must also have a default value An input value must be between 0 and 40 You cannot delete parent records that have child records associated with them

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

Tips for Creating Database Tables and Records Design first Create tables and records last Name tables systematically Use conventional tbl prefixes Use mnemonic names for data fields Assign correct data types to data fields

Tips for Creating Database Tables and Records Data fields that link tables must be the same data type Limit the size of text data fields to reasonable lengths Use input masks

Extracting Data From Databases Schema All information in a database All relationships of the tables Map of entire database Subschema Subset of the schema

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

Query Example

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

Select Query Example

Multi-Table Select Query Example

Multi-Table Select Query Example

Creating Action Queries Delete queries Append queries Sum a column Update queries Make-table queries

Query Wizard Queries Simple query Wizard Crosstab queries Find-Duplicates queries Find-unmatched queries

Query Wizard Screen

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

Extracting Data From Databases Structured Query Language (SQL) Example of SQL Instructions

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

Cloud Computing Form of Internet-based Computing Software provided through the Internet Processing occurs on a Web of computers Expands IT capabilities Database-As-A-Service (DAAS) Outsourcing of databases Backup Services

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