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Succeeding with Technology
Database Systems
Basic Data Management Concepts Organizing Data in a Database Database Management Systems Using Database Systems in Organizations Database Trends Managing Databases
Please discontinue use of cell phone and turn off ringer
Chapter 7
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The Value of Databases
Databases and Database Management Systems (DBMS) transform large quantities of data into specific and valuable information for accomplishing some goal.
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Database Management System (DBMS)
A DBMS consists of a group of programs that manipulate the database and provide an interface between the database and the user or the database and application programs.
Front End
DATABASE
Back End
DBMS
SecureAccess
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File or Table
Database
A collection of data organized to meet user’s needs.
Records (Entities)
Field(Attribute)
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Keys and Primary Key
Key: A field in a record that is used to identify the record
Primary key: A field that uniquely identifies a recordA primary key field prevents duplicate
records from occurring in a table.
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Primary Keys
Which field would act as the best primary key?Which field would act as the best primary key?
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7.2
Organizing Data in a Database
• Relational Model• Data Analysis
Key Terms
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The Relational Model
In a relational database, tables are linked (related) through common fields.
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Relation Types One-to-many
Most typical Makes use of primary key
One-to-one Many-to-many
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Data Analysis
Data analysis is a process that involves evaluating data to identify problems with the content of a database.Consider what would happen if
CardNumber were not a primary key, and two or more customers had the same CardNumber.
Data Integrity refers to the accuracy of the data in a database.
GIGO, or Garbage In Garbage Out, refers to the fact that inaccurate data entered in a database will result in inaccurate information produced from the database.
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7.3
Database Management Systems
• Data Integrity• GIGO• Schema• Data Dictionary• SQL
Key Terms
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Creating a Database
A schema is an outline of the logical and physical structure of the data and relationships among the data in the database.
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Creating a Database
A data dictionary provides a detailed description of all data used in the database.
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Database Strengths
Data can be sifted, sorted and queried through the use of data manipulation languages.
The power of a database and DBMS lies in the user’s ability to manipulate the data to turn up useful information.
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Data Manipulation Language
A Data Manipulation Language (DML) is a specific language provided with the DBMS that allows people and other database users to access, modify, and make queries about data contained in the database, and to generate reports.
Structured Query Language (SQL): The most popular DML. SELECT * FROM EMPLOYEE WHERE JOB_CLASSIFICATION = ‘C2”
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7.4
Using Database Systems in Organizations
• Data Warehouse• Data Mining
Key Terms
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The data deluge… The Machinery Moves on:
Moore’s law: processing “capacity” doubles every 18 months : CPU, cache, memory
It’s more aggressive cousin: Disk storage “capacity” doubles every 9 months
The Demand is exploding:Every business is an eBusinessScientific Instruments and Moore’s lawGovernment
The Internet – the ubiquity of the Web The Talent Shortage
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Data Stores Data Warehouse: A database that holds
important information from a variety of sources.
Data Mart: A small data warehouse, often developed for a specific person or purpose.
Data Mining: the process of extracting information from a data warehouse.“Connecting the dots”
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What Is a Hypercube?
Create multi-dimensional “cubes” of information that summarize transactional data across a variety of dimensions.
OLAP vs. OLTP
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What is Data Mining?
Finding interesting structure in data Structure: refers to statistical patterns, predictive models,
hidden relationships Interesting: ?
Examples of tasks addressed by Data MiningPredictive Modeling (classification, regression)Segmentation (Data Clustering )Affinity (Summarization)
relations between fields, associations, visualization An Example
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Data Mining and Databases
Many interesting analysis queries are difficult to state precisely
Examples:which records represent fraudulent transactions?which households are likely to prefer a Ford over a Toyota?Who’s a good credit risk in my customer DB?
Yet database contains the information good/bad customer, profitabilitydid/did not respond to mailout/survey/...
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Example: market basket Transactions
{Bread, Milk}
{Bread, Diapers, Beer, Eggs}
{Milk, Diapers, Beer, Cola}
{Bread, Milk, Diapers, Beer}
{Bread, Milk, Diapers, Cola}
What pattern can you see?
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A more systematic approach: a “Decision Tree”
All 1615 patients
Split # 1: Age
“terminal node”Systolic BP
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Visualization is Important
Factory food example from this week’s New York Times
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The myths…
Companies have built up some large and impressive data warehouses
Data mining is pervasive nowadaysLarge corporations know how to do itThere are tools and applications that discover
valuable information in enterprise databases
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The truths… Data is a shambles,
most data mining efforts end up not benefiting from existing data infra-structure
Corporations care a lot about data, and are obsessed with customer behavior and understanding it
They talk a lot about it… An extremely small number of businesses are
successfully mining data The successful efforts are “one-of”, “lucky strikes”