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8/6/2019 Mis 4 Data Resource Management
1/21
Data Resource Management
8/6/2019 Mis 4 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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Foundation Data Concepts (continued)
Data Elements
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Foundation Data Concepts (continued)
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