INFO100 and CSE100
Fluency with Information Technology
Katherine Deibel
2012-05-23
Katherine Deibel, Fluency in Information Technology
1
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We have so far discussed
 What a database is
 What database operations do
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Today, we will discuss
 Databases as tools
 How queries are used
2012-05-23
Katherine Deibel, Fluency in Information Technology
2
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Keep records of our:
 Clients
 Staff
 Volunteers
Keep a record of activities and interventions
 Keep sales records

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Develop reports
Perform research
 Longitudinal tracking
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2012-05-23
Katherine Deibel, Fluency in Information Technology
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Field
(columns in a table)
Smallest unit of information in a table
Sometime called “attributes”
Record
(rows in a table)
All related fields are collectively called a
record
Table
A collection of records is a data table
Database Management
System (DBMS)
All the related tables, queries, data entry
and edit forms, reports, macros and VBA
modules that constitute a database
Records
(rows)
Fields (columns)
Anderson
Thomas
A 123 Marine Dr
237-1234
Benson
Karen
C 1300 Ohio Ave
237-8912
Casserly
Rick
J
12492 Rt 146
238-9011
Drummond
Lynn
M 1209 15th Ave N
931-4545
Table
2012-05-23
Katherine Deibel, Fluency in Information Technology
4
Field
(columns in a table)
Smallest unit of information in a table
Sometime called “attributes”
Record
(rows in a table)
All related fields are collectively called a
record
Table
A collection of records is a data table
Database Management
System (DBMS)
All the related tables, queries, data entry
and edit forms, reports, macros and VBA
modules that constitute a database
Records
(rows)
Fields (columns)
Anderson
Thomas
A 123 Marine Dr
237-1234
Benson
Karen
C 1300 Ohio Ave
237-8912
Casserly
Rick
J
12492 Rt 146
238-9011
Drummond
Lynn
M 1209 15th Ave N
931-4545
Table
2012-05-23
Katherine Deibel, Fluency in Information Technology
5

Data (according to Information Science)
 Unprocessed, raw information

Information
 Organized, structured data that is communicated
in a coherent and meaningful manner

Knowledge
 Information that has been evaluated and further
organized so that it can be used purposefully

Action
 Applying knowledge towards achieving goals
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We collect data

Information is harvested from the data
 Many companies are good at collecting data
 Fewer are good at harvesting information

Knowledge is elicited from the information
and put into action
 Database Management Systems are tools for
supporting this transformation process
Data
2012-05-23
Information
Knowledge
Katherine Deibel, Fluency in Information Technology
Action
7
The Tools for Data to Information to Knowledge to Action
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DMSs are software data tools to:
 Store (tables)
 Organize (sort)
 Add, modify or delete
 Ask questions (queries)
 Produce forms and reports

Toolbox is a good analogy
2012-05-23
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Microsoft Access
FileMaker Pro
Lotus Notes
Structured Query Language (SQL)
 Microsoft SQL Server
 Oracle
 MySQL
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Three major distinctions
 Purpose of database:
Operational versus Analytical
 Data representation:
Flat-file versus Relational
 Implementation:
Desktop versus Client/Server
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Desktop databases
 Oriented toward single-user applications
 Reside on standard personal computers

Client / Server databases
 Contain mechanisms to ensure the reliability and
consistency of data
 Offers security options on [subsets of] data
 Oriented toward multi-user applications
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Operational databases Analytical databases

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Used to track and assist in
daily “business” activities
Data typically changes
frequently over time

Tend to be more static

Historical data is analyzed
for patterns or trends

Often support the strategic
activities of an organization

Goals may include
Examples
 Human resources
 Mailing lists
 Predicting the future
 Inventory management
 Summarizing historical data
 Accounting systems
 Prove historical assumptions
 Point of sale systems
(cash registers)
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Flat-File Database
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All relevant data in a
single table, or series
of unrelated tables
Work best for small
quantities of data
Typically a person’s
first databases
2012-05-23
Relational Database
Solution to data entry
redundancy problems
 Tables linked together
queried as if one table
 Linked via common
fields (columns) with
exactly the same data
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Weaknesses common to flat-file systems
 Duplicate information is repeated redundantly
 Inconsistencies in how data is entered
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Our quarry is the query
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Users rarely work with the entire database
 Exception are the database managers

Instead, users interact through
 Forms: read and write data
 Reports: read only

All of these are based on the query
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Forms allow interaction with the database
in a more scripted fashion

Data is read
and maybe
even edited
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Reports are summaries generated
from the database
Read-only
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Generate a table from other tables in the
database via sequences of operations
 Select
 Difference
 Project
 Product
 Union
 Join
SQL: Structured Query Language
 Standard database language
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 SQL sequences are usually auto-generated
 Interfaces allow easy construction of SQL
 We can view the generated SQL if we want
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Some records may be editable
 If the data is linked to a primary key
 Generally not true for collapsed data
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Relies on primary keys and the underlying
intelligence of the database
 Further security settings can set edit rights
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Updates can be sent out to all views
 Synchronization is a big issue
 Editing a linked value will chance all instances
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Expanded database from Lab 10
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A good relational database
 Uses IDs to connect records across tables
(i.e. relationships)
 Provides specific views to meet specific users'
needs

Learning these skills is beyond the scope
of this course
 Knowing the essential ideas is part of being
fluent in databases
 We will discuss some basic design on Friday
2012-05-23
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Queries, on the high-level, are the
final outcome of transforming data
into action
Database Management Systems
provide tools for creating and
manipulating queries
2012-05-23
Katherine Deibel, Fluency in Information Technology
29

You will get to explore a database by
playing different roles at an
interstellar travel agency
 Astronomical cartographer
 Trip planner
 Planetary information broker
 End consumer
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