Technology in Action - MCCCokikeq/documents/Chapter9... · object-oriented, and multidimensional. • Relational databases operate by organizing data into various tables based on

Technology in Action

Alan Evans • Kendall Martin

Mary Anne Poatsy

Eleventh Edition

Copyright © 2015 Pearson Education, Inc.

Technology in Action

Chapter 9 Behind the Scenes:

Databases and Information Systems


Chapter Topics

• Database Basics – Database Building Blocks – Database Types – Database Functions

• How Businesses Use Databases – Database Warehousing and Storage – Business Intelligence Systems – Data Mining

Copyright © 2015 Pearson Education, Inc. 2

Database Basics

• Database Building Blocks • Database Types • Database Functions


Database Building Blocks

• A database is a collection of related data, which can be – Stored – Sorted – Organized – Queried

• Databases make data more meaningful and useful

• Databases turn data into information Copyright © 2015 Pearson Education, Inc. 4

Database Building Blocks Databases Versus Lists

• Databases are not needed for managing all types of data – Lists are adequate for simple tasks – Other applications have tools to create lists

• Word • Excel



• When a list is not sufficient for organizing data – Complex information – When multiple people need to access

information



• Lists can lead to inconsistencies – Repetition of data – Errors from inconsistently entered or updated

data

• Data redundancy - unnecessary extra copies of data

• Lists have other problems




Database Building Blocks Advantages of Using Databases

• Databases make our lives easier • Databases can manage large amounts of

data efficiently • Databases make information sharing

possible • Databases promote data integrity


Database Building Blocks Advantages of Using Databases


Database Building Blocks Disadvantages of Using Databases

• Disadvantages of databases – Can be more time consuming and expensive

to set up and administer – Care is needed to insure they function as

intended – Administrator is responsible for designing,

constructing, and maintaining databases


Database Building Blocks Database Management Systems

• How databases are created – Database management system (DBMS) is

designed to capture and analyze data – Four main operations of a DBMS

• Creating databases and entering data • Viewing (or browsing) and sorting data • Querying (extracting) data • Outputting data


Database Building Blocks Database Terminology

• How data is stored in a database


The city column represents one field in this database

All the records representing student information is a table in this database

Julio’s contact data is one record

Database Building Blocks Planning and Creating the Database • How to create a database with a DBMS

– Describe the data to be captured – Data dictionary & Metadata


Database Building Blocks Planning and Creating the Database

• How data tables are created – Step 1: Input unique field names – Step 2: Define the data type – Step 3: Set a maximum field size – Step 4: Set a default value if necessary – Repeat for each field in the table



• How to know what fields are needed – Careful planning is required – Field should describe a unique piece of data

• Do not combine two pieces of data • Allows for better filtering and sorting

• Fields can be added or deleted



• Rules for establishing field names – Must be unique within a table – Do not use spaces

• Use underscores or CamelCase can be used • Use caption field to display spaces

– Creating a data dictionary will help you plan


Database Building Blocks Planning and Creating the Database • Determining what type of data can be

entered in a field – Data type indicates what type of data can

be stored in the fields – Prevents wrong type of data from being

entered





• Amount of data which can be entered into a field – Field size determines maximum number of

characters – Tailor field size to match maximum length of

data – Truncated data can result from field size set

too small


Database Building Blocks Using Primary Keys

• Having the same values in the same table – It is possible for fields to have the same

values – Each record must have a unique value, the

primary key – Primary keys make it impossible to duplicate

records


Database Building Blocks Using Primary Keys

• A good primary key – Must be unique – Doesn’t have to represent something – AutoNumber data type (Microsoft Access) is

often used


Database Types

• Three major types of databases are in use – Relational – Object-oriented – Multidimensional

• Relational databases have the largest market share

• Multidimensional databases are growing


Database Types Relational Databases

• Relational database – Organizes data in table format – Logically groups similar data into a relation

(a table that contains related data) – Links data between tables through

relationships on common keys



Common field in one table (primary key) linked to common field (foreign key) in second table Need to keep data in related tables synchronized



• Relational database – Referential integrity: Each value in the

foreign table has a corresponding value in the primary table – Prevents orphan records



• Different types of relationships in relational databases – One-to-many – One-to-one – Many-to-many


Database Types Object-Oriented Databases

• Store data in objects rather than tables • Contain methods for processing or

manipulating data • Can store more types of data than

relational databases • Can access data faster


Database Types Object-Oriented Databases

• Unstructured data include audio clips, video clips, pictures, and extremely large documents – Binary large object (BLOB) is unstructured data

encoded in binary form – Becoming more popular because of variety of

data – Costly to convert data but can provide many

advantages


Database Types Multidimensional Databases

• Stored data can be analyzed from different perspectives (dimensions)

• Relational database has only two dimensions (fields and records)

• Multidimensional databases organize in cube format



• Data cube – Measure attribute:

Main type of data that cube is tracking

– Feature attributes: Describe measure attribute in meaningful ways



• Advantages of multidimensional databases – Customized to provide information to variety

of users – Process data faster

• Critical for larger databases • Especially when accessed via the Internet


Database Functions

• Functions – Populate the database by creating records – Allow users to extract subsets of data from

the database – Output the data in a meaningful and

presentable format


Database Functions

Inputting Data • How to get data into the database

– Can be directly keyed into the database – Can import from other files

• Saves time • Reduces data error • Must match the format of the database exactly • Filters are often applied • Nonconforming data is flagged


Database Functions Inputting Data

• How to make manual entry into a database more efficient – Input forms used to control data input – Each field has a label – Data is inputted into the blank boxes – Existing data can be changed through forms – Ensures that correct record is changed


Database Functions Inputting Data


Database Functions Data Validation

• Ensuring that only valid data is entered – Process of ensuring that data meets

specified guidelines – Rule is defined in data dictionary – Specified in field properties for each field – Violations result in error message with

suggested action – Common validation rules






Data entered that falls outside the range of acceptable values

No value entered in a required field

Database Functions Viewing and Sorting Data

• Viewing the data in a database – Displaying all data at one time is an option – Many times data is viewed one record at a

time – Forms display individual records

• From only one table • From related tables



• Reordering records in a database – Easy to sort data in ascending or descending

order • Highlight a column • Click Ascending or Descending on the Ribbon



View records by browsing


Sort records by field name

Database Functions Extracting or Querying Data

• Displaying a subset of data – Use a filter or create a query – Query language – Structured Query Language (SQL) is the

most popular – Modern systems provide wizards for creating

queries


Database Functions Extracting or Querying Data


Database Functions Outputting Data

• Retrieving data from of a database – Most common output is viewable or printable

report – Can generate reports from data in tables or

from queries – Adjustments can be made to the report


Database Functions Outputting Data

• Transferring data from a database to another software application – Exporting: Putting data into format that

another application can understand – Data can be imported and exported as well

as converted to and from other formats


Check Your Understanding

1. What is a database, and why is using one beneficial?

47 Copyright © 2015 Pearson Education, Inc.

• A database is a collection of related data that can be stored, sorted, organized, and queried. Many actions we do every day (use an ATM, shop online, make an airplane reservation) generate data that needs to be stored, managed, and used by others.

• By creating an organized structure for data, databases make data more meaningful and therefore more useful. Databases effectively turn data into information.


2. What do database management systems do?


• Databases are created and managed using a database management system (DBMS). A DBMS is specially designed application software (such as Oracle Database or Microsoft Access) that interacts with the user, other applications, and the database to capture and analyze data.

• The four main operations of a DBMS are as follows: 1. Creating databases and entering data 2. Viewing (or browsing) and sorting data 3. Querying (extracting) data 4. Outputting data


3. What components make up a database?


• Understanding how databases store information requires knowing the unique terminology developed to describe databases. Databases have three main components:

1. Fields: A database stores each category of information in a field. Fields are displayed in columns. Each field is identified by a field name, which is a way of describing the information in the field.

2. Records: A group of related fields is called a record. 3. Tables (Files): A group of related records is called a table (or file). Tables are usually organized by a common subject.


4. What types of databases are there?


• The three major types of databases currently in use are relational, object-oriented, and multidimensional.

• Relational databases operate by organizing data into various tables based on logical groupings. In relational databases, a link between tables that defines how the data is related is referred to as a relationship.

• An object-oriented database stores data in objects rather than in tables. Objects contain not only data but also methods for processing or manipulating that data.

• A multidimensional database stores data that can be analyzed from different perspectives, called dimensions. This distinguishes it from a relational database, which stores data in tables that have only two dimensions (fields and records).

Check Your Understanding 5. What are the functions of a relational database?

How do relational databases organize and manipulate data?


Input (populate) data directly by keying in, or by importing from other sources. Input forms control how new data is entered. Data validation rules help prevent improper data from being entered. Data is viewed/displayed through forms showing individual records, or through tables displaying all related records Queries display a subset of data that match certain criteria. Reports used to output data. Data can be aggregated and sorted. Data can be outputted to other applications to be further manipulated.

How Businesses Use Databases

• Database Warehousing and Storage • Business Intelligence Systems • Data Mining


Data Warehousing and Storage

• Problems arise when – Organization gets much larger – Data is stored in separate databases

• Benefits of accessing data from all databases are being recognized

• Data warehouses and data marts are large storage repositories


Data Warehousing and Storage Data Warehouses

• Large-scale collection of data

• Contains and organizes data in one place

• Data comes from multiple databases

• Consolidate information from various systems

• Present enterprise-wide view of operations



• Data is organized as in a normal database – Data is organized by subject – Focus is on one specific aspect of an

operation – Can contain information from multiple

databases



• Does not capture data from only one time period

• Populated with data – Internal sources – External sources – Clickstream data


Data Warehousing and Storage Data Staging

• Fitting source data into the warehouse – Data must be “staged” before being entered

into a data warehouse – Many programs and procedures might be

needed to extract and reformat data – Nature and complexity of data determines

complexity of process



Data Warehousing and Storage Data Staging

Data Warehousing and Storage Data Marts

• How to handle smaller amounts of data – Data mart: Small slices of data warehouse – Analyze related group of data separated

from the main body – Pertains to single component of business – Vital because different data can be extracted

and reformatted – Can be stored in specialized data marts


Business Intelligence Systems

• Software-based solution to gather and analyze information – Delivers up-to-the-minute data

• Integral because they store the functional information – All perform similar functions


Business Intelligence Systems


Business Intelligence Systems Office Support Systems

• What an office support system accomplishes – Office support system (OSS) is designed to

improve communications and assist employees in accomplishing tasks


Business Intelligence Systems Transaction-Processing Systems

• Keeps track of everyday business activities

• Early computers hosted TPSs



• Batch processing – Data is accumulated then several

transactions are processed at once – Appropriate for activities that are not time

sensitive – Often more efficient



• When TPS transactions are processed – Most transactions are processed in real-time – Real-time processing is when the database

is updated while the transaction is taking place

– Online transaction processing (OLTP) ensures that data in the TPS is current


Business Intelligence Systems Management Information Systems

• Management information system (MIS) – Provides timely and accurate information – Enables managers to make critical decisions – Directs outgrowth of TPSs – Powerful if organized and outputted in useful

form – Often included as a feature of TPSs

• Can generate various reports


Business Intelligence Systems Decision Support Systems

• Decision Support System (DSS) – Another type of business intelligence system – Designed to help managers develop

solutions for specific problems – Uses information from databases and data

warehouses – Users can add own insights and experiences

to solution



• How DSSs get data



• What function a model management system performs – Assists in building management models – Analysis tool provides view of a particular

business situation – Aids in decision making – Used to analyze data to create additional

models



• How a knowledge-based system helps in the decision-making process – Fuzzy logic enables the interjection of

experiential learning into the equation by considering probabilities • Enables a system to be more flexible • Consider a wider range of possibilities


Business Intelligence Systems Enterprise Resource Planning Systems

• What an Enterprise Resource Planning (ERP) system does – Accumulates relevant information – Makes information available – Uses a common database


Data Mining

• Data mining – Process by which great amounts of data are

analyzed and investigated – Objective is to spot significant patterns and

trends that would not be obvious


Data Mining

• Why businesses mine their data – Understand customers better – Effective marketing by concentrating efforts – Data is classified, then cluster analysis

allows managers to determine trends

• How businesses mine their data – Classification, Estimation, Affinity grouping,

Clustering, Description and Visualization


Data Mining


Check Your Understanding 6. What are data warehouses and data

marts, and how are they used?


• A data warehouse is a large-scale collection of data that contains and organizes in one place all the data from an organization’s multiple databases.

• Small slices of the data warehouse, each called a data mart, are often created so that companies can analyze a related set of data that are grouped together and separated out from the main body of data in the data warehouse.

Check Your Understanding 7. What is a business intelligence system,

and what types of business intelligence systems are used by decision makers?


• An information system is a software-based solution used to gather and analyze information. Databases, data warehouses, and data marts are integral parts of information systems because they store the information that makes information systems functional.

• All information systems perform similar functions, including acquiring data, processing that data into information, storing the data, and providing the user with a number of output options with which to make the information meaningful and useful.

• Office Support System, Transaction Processing Systems, Management Information Systems, Decision Support Systems, and Enterprise Resource Planning Systems are types of business intelligence systems.

Check Your Understanding 8. What is data mining, and how does it work?


Data mining is the process by which great amounts of data are analyzed and investigated. Data mining enables managers to sift through data in several ways. Each technique produces different information on which managers can then base their decisions. • Classification: Before mining, managers define data classes they think

will be helpful in spotting trends. • Estimation: Estimation enables managers to assign a value to data based

on some criterion. • Affinity grouping (or association rules): When mining data, managers can

determine which data goes together. • Clustering: Clustering involves organizing data into similar subgroups, or

clusters. It’s different from classification in that there are no predefined classes.

• Description and visualization: Often, the purpose of data mining is to describe data so that managers can interpret it in new and different ways.

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Technology in Action - MCCCokikeq/documents/Chapter9... · object-oriented, and multidimensional. • Relational databases operate by organizing data into various tables based on