Mis 4 Data Resource Management

8/6/2019 Mis 4 Data Resource Management

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Data Resource Management


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Data Resource Management

A managerial activity

Applies information systems technology to

managing data resources


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Database a collection of related data organized in

a way to facilitate data processing (ie searches)

DBMS Database Management Systems

Use a DBMS software to create, store, organize, andretrieve data from a single database or several databases

Example: Microsoft Access

What is a DataBase?


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Foundation Data Concepts

Levels of data

Character

Single alphabetical, numeric, or other symbol

Field Groupings of characters

Represents an attribute of some entity

Records

Related fields of data

Collection of attributes that describe an entity

Fixed-length or variable-length


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Foundation Data Concepts (continued)

Files (table)

A group of related records

Classified by

Primary use Type of data

permanence


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Data Elements


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Database (wrap up)

Integrated collection of logically related data elements

Consolidates records into a common pool of data

elements Data is independent of the application program using

them and type of storage device


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NetworkServer

ExternalDatabases on

the Internet &Online

Services

ClientPC or

NC

OperationalDatabases ofthe Organization

DataMart

End UserDatabases

Data

Warehouse

DistributedDatabases on

Intranets &Other Networks

Major Types of Databases


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Types of Databases

Operational

Supports business processes and operations

Also called subject-area databases, transaction

databases, and production databases.

These also include databases of Internet and

electronic commerce activity, such as click

stream data or data describing online behaviorof visitors at a companys website.


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Types of Databases (continued)

Distributed

Replicated and distributed copies or parts of

databases on network servers at a variety of sites. Done to improve database performance and security

These are the databases of local workgroups and

departments at regional offices, branch offices, and other

work sites needed to complete the task at hand.


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Data Warehouse Databases. These store data

from current and previous years that has been

extracted from the various operational and

management databases of the organization. Asa standardized and integrated central source of

data, warehouses can be used by managers for

pattern processing, where key factors and trends

about operations can be identified from thehistorical record.


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Data Marts. Are subsets of the data included ina Data Warehouse which focus on specificaspects of a company, e.g. department,

business process, etc. End UserDatabases. These consist of a variety

of data files developed by end users at theirworkstations. For example, an end user in sales

might combine information on a customersorder history with her own notes andimpressions from face-to-face meetings toimprove follow-up.


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External Databases. Many organizations make

use of privately generated and owned online

databases or data banks that specialize in a

particular area of interest. Access is usuallythrough a subscription for continuing links or a

one-time fee for a specific piece of information

(like the results of a single search). Other

sources like those found on the Web are free.


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Data Warehouse and Data Mining

ClientPC or

NCAnalytical

Data Store

Enterprise

Warehouse

Data MartDataAcquisition

Subsystem

Warehouse

Design

Subsystem

Data

Management

Subsystem

Data Access

and Delivery

Subsystem

Web

Information

System

Operational

Databases

Metadata

Directory

Metadata

Repository

Metadata

ManagementSubsystem


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Data Warehouses and Data Mining

Data warehouse

Stores data extracted from operational, external,

or other databases of an organization

Central source of structured data

May be subdivided into data marts


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How Organizations Get the Most

from Their Data Data Mining

A method for better understanding data

Information on customers, products, markets, etc. Drill down: from summary to more detailed data

Sort and extract information

Trends, correlations, forecasting, statistics


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How Organizations Get the

Most from Th

eir Data

Data Mining Online Transaction Processing (OLTP)

Immediate automated responses to user requests

Multiple concurrent transactions

A big part of interactive Internet e-commerce


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How Organizations Get the

Most from Their Data

Data Mining Online Analytical Processing (OLAP)

Graphical software tools that provide complex analysis

of data stored in a database

Drills down to deeper levels of consolidation

Time series and trend analysis

What if and why questions


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Applications

Banking: loan/credit card approval predict good customers based on old customers

Customer relationship management:

identify those who are likely to leave for a competitor. Targeted marketing:

identify likely responders to promotions

Fraud detection: telecommunications, financialtransactions from an online stream of event identify fraudulent events

Manufacturing and production: automatically adjust knobs when process parameter changes


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Applications (continued)

Medicine: disease outcome, effectiveness of

treatments

analyze patient disease history: find relationship between

diseases Molecular/Pharmaceutical: identify new drugs

Scientific data analysis:

identify new galaxies by searching for sub clusters

Web site/store design and promotion: find affinity of visitor to pages and modify layout


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Data Mining in Use

Basketball teams use it to track game strategy

Cross Selling

Target Marketing

Holding on to Good Customers

Weeding out Bad Customers

Mis 4 Data Resource Management

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