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DATABASE FUNDAMENTALS

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UNDERSTANDING INFORMATION

• Data is a valuable organizational resource & should be managed

• Its usefulness depends to a large extent on how it is stored, organized, and accessed/retrieved

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UNDERSTANDING INFORMATION

• Information is everywhere in an organization

• Employees must be able to obtain and analyze the many different levels, formats, and granularities of organizational information to make decisions

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UNDERSTANDING INFORMATION

• Information granularity – refers to the extent of detail within the information (fine and detailed or coarse and abstract)

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Information Quality

• Business decisions are only as good as the quality of the information used to make the decisions

• Characteristics of high quality information include:– Accuracy– Completeness– Consistency– Uniqueness– Timeliness

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Information Quality

• Low quality information example

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Understanding the Costs of Poor Information

• The four primary sources of low quality information include:

1. Online customers intentionally enter inaccurate information to protect their privacy

2. Information from different systems have different entry standards and formats

3. Call center operators enter abbreviated or erroneous information by accident or to save time

4. Third party and external information contains inconsistencies, inaccuracies, and errors

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Understanding the Costs of Poor Information

• Potential business effects resulting from low quality information include:– Inability to accurately track customers– Difficulty identifying valuable customers– Inability to identify selling opportunities– Marketing to nonexistent customers– Difficulty tracking revenue due to inaccurate

invoices– Inability to build strong customer relationships

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Understanding the Benefits of Good Information

• High quality information can significantly improve the chances of making a good decision

• Good decisions can directly impact an organization's bottom line

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DATABASE FUNDAMENTALS

• Information is stored in databases– Database – maintains information about

various types of objects (inventory), events (transactions), people (employees), and places (warehouses)

– Database Management System (DBMS) - SW through which users and application programs interact with a database

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DATABASE FUNDAMENTALS

• Database models include:– Hierarchical database model – information is

organized into a tree-like structure (using parent/child relationships) in such a way that it cannot have too many relationships

– Network database model – a flexible way of representing objects and their relationships

– Relational database model – stores information in the form of logically related two-dimensional tables

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DATABASE ADVANTAGES

• Database advantages from a business perspective include– Increased flexibility– Increased scalability and performance– Reduced information redundancy– Increased information integrity (quality)– Increased information security

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Database• A database is comprised

of one or more tables. Each database also contains a unique name.

• Microsoft Access is an example of a database program that allows you to store, retrieve, and

manipulate data.

DATABASE FUNDAMENTALS

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Database

• Table– Field– Record

• Query

• Form

• Report

DATABASE FUNDAMENTALS

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Field• A field is the smallest piece of a database; that is, one

specific piece of information like a number, a word, a date, a picture, or a reference for some other piece of data. Each column you see in the diagram would all be the same data type; that is one column of data would all be numbers.

Record• A record is a collection of one or more fields together in

a row. (In a real database, you would not count the word ‘Record’ like in the diagram – this is just to help visualize the concept.)

DATABASE FUNDAMENTALS

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Table• A table is comprised of one or more records. Each table

also has a unique name.

Query• A query is just like a question you ask the database.

There are two types of queries: select and action. A select query will extract and display data based on criteria you provide. An action query will find all data relevant to your query and perform some action on it. A query can be performed on one or more tables in a database.

DATABASE FUNDAMENTALS

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Form• A form is a tool that is used to easily and accurately

enter data into a table. A form presents one record of a database at a time to a user, or allows a user to enter data into the database one record at a time.

Report• A report presents the data found by a query. A report

can be formatted to show summaries, calculations, charts, and more based on the data returned by a query. Access takes the report one step further by letting you organize and format a report into a sleek, professional document.

DATABASE FUNDAMENTALS

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• Entity – a person, place, thing, transaction, or event about which information is stored– The rows in each table contain the entities– In Figure 6.5 CUSTOMER includes Dave’s Sub Shop

and Pizza Palace entities

• Entity class (table) – a collection of similar entities– In Figure 6.5 CUSTOMER, ORDER, ORDER LINE,

DISTRIBUTOR, and PRODUCT entity classes

RELATIONAL DATABASE FUNDAMENTALS

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• Attributes (fields, columns) – characteristics or properties of an entity class– The columns in each table contain the attributes– In Figure 6.5 attributes for CUSTOMER include:

• Customer ID• Customer Name• Contact Name• Phone

RELATIONAL DATABASE FUNDAMENTALS

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• Primary keys and foreign keys identify the various entity classes (tables) in the database– Primary key – a field (or group of fields) that

uniquely identifies a given entity (record) in a table

– Foreign key – a primary key of one table that appears as an attribute in another table and acts to provide a logical relationship (link) between the two tables

RELATIONAL DATABASE FUNDAMENTALS

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Potential relational database for Coca-Cola

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DATABASE MANAGEMENT SYSTEMS

• Four components of a DBMS

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Data Definition Component

• Data definition component – creates and maintains the data dictionary and the structure of the database

• The data definition component includes the data dictionary– Data dictionary – a file that stores definitions of

information types, identifies the primary and foreign keys, and maintains the relationships among the tables

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Data Manipulation Component

• Data manipulation component – allows users to create, read, update, and delete information in a database

• A DBMS contains several data manipulation tools:– View – allows users to see, change, sort, and query the

database content– Report generator – users can define report formats – Query-by-example (QBE) – users can graphically

design the answers to specific questions– Structured query language (SQL) – query language

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Application Generation and Data Administration Components

• Application generation component – includes tools for creating visually appealing and easy-to-use applications

• Data administration component – provides tools for managing the overall database environment by providing faculties for backup, recovery, security, and performance

• IT specialists primarily use these components

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HISTORY OF DATA WAREHOUSING

• Data warehouses extend the transformation of data into information

• In the 1990’s executives became less concerned with the day-to-day business operations and more concerned with overall business functions

• The data warehouse provided the ability to support decision making without disrupting the day-to-day operations

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DATA WAREHOUSE FUNDAMENTALS

• Data warehouse – a logical collection of information – gathered from many different operational databases – that supports business analysis activities and decision-making tasks– Stores 3 – 10 year’s of historical data – Supports managerial decision making (analysis)– Is regularly updated, cleansed or scrubbed, and

purged of old data– Requires heavy-duty processing power and storage

capacity– Uses queries to analyze past data in order to spot

trends, patterns

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DATA WAREHOUSE FUNDAMENTALS

• Data mart – contains a subset of data warehouse information, usually for a single aspect of a company’s business– Finance, inventory, personnel, sales, etc.

• Is limited in scope & customized to support decision making for a particular end-user group

• Useful for smaller groups – Small and medium-sized businesses– Departments within a business

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DATA WAREHOUSE FUNDAMENTALS

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Multidimensional Analysis

• Databases contain information in a series of two-dimensional tables

• In a data warehouse and data mart, information is multidimensional, it contains layers of columns and rows– Dimension – a particular attribute of

information

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Information Cleansing or Scrubbing

• An organization must maintain high-quality data in the data warehouse

• Information cleansing or scrubbing – a process that weeds out and fixes or discards inconsistent, incorrect, or incomplete information

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BUSINESS INTELLIGENCE

• Business intelligence – information that people use to support their decision-making efforts

• Principle BI enablers include:– Technology– People– Culture

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Data Mining

• Data Mining – the process of analyzing data to extract information not offered by the raw data alone

• Data-mining systems sift instantly through information to uncover patterns and relationships

• Data-mining systems include many forms of AI such as neural networks and expert systems

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Multidimensional Analysis

To perform data mining users need data-mining tools– Data-mining tools – use a variety of

techniques to find patterns and relationships in large volumes of information, and infer rules that predict future behavior and guide decision making

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DATA MINING

• Common forms of data-mining analysis capabilities include:

– Cluster analysis– Association detection– Statistical analysis

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Cluster Analysis

• Cluster analysis – a technique used to divide an information set into mutually exclusive groups such that the members of each group are as close together as possible to one another and the different groups are as far apart as possible

• Example: CRM systems depend on cluster analysis to segment customer information and identify behavioral traits

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Association Detection

• Association detection – reveals the degree to which variables are related and the nature and frequency of these relationships in the information

– Market basket analysis – analyzes such items as Web sites and checkout scanner information to detect customers’ buying behavior and predict future behavior by identifying affinities among customers’ choices of products and services

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Statistical Analysis

• Statistical analysis – performs such functions as information correlations, distributions, calculations, and variance analysis

– Forecast – predictions made on the basis of time-series information

– Time-series information – time-stamped information collected at a particular frequency

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• Establishing an information policy

• Firm’s rules, procedures, roles for sharing, managing, standardizing data

• E.g., What employees are responsible for updating sensitive employee information

• Data administration: Firm function responsible for specific policies and procedures to manage data

• Data governance: Policies and processes for managing availability, usability, integrity, and security of enterprise data, especially as it relates to government regulations

• Database administration : Defining, organizing, implementing, maintaining database; performed by database design and management group

Managing Data Resources

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• Ensuring data quality• More than 25% of critical data in Fortune 1000 company databases

are inaccurate or incomplete

• Most data quality problems stem from faulty input

• Before new database in place, need to:

• Identify and correct faulty data

• Establish better routines for editing data once database in operation

Managing Data Resources

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• Data quality audit:• Structured survey of the accuracy and level of completeness of the data in

an information system

• Survey samples from data files, or

• Survey end users for perceptions of quality

• Data cleansing• Software to detect and correct data that are incorrect, incomplete,

improperly formatted, or redundant

• Enforces consistency among different sets of data from separate information systems

Managing Data Resources

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DATABASE FUNDAMENTALS