3 data mgmt
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Chapter 3
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Data Management: Data, Databases and Warehousing
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Learning Objectives
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Recognize the importance of data, managerial issues, and life cycle
Describe sources of data, collection, and quality
Describe DMS Describe Data Warehousing and
Analytical Processing Describe DBMS (benefits and issues)
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Learning Objectives (Continued)
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Understand conceptual, logical, and
physical data
Understand ERD
The importance of Marketing
The Internet and Data Management
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Introduction
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Corporate data are key strategic assets.
Managing data quality is vital to the organizations.
Dirty data results in:Poor business decisionsPoor customer serviceInadequate product design
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Goal of data management
Chapter 35
The goal of DM is provide the infrastructure to transform raw data into corporate information of the highest quality.
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Building Blocks of DM
Chapter 36
Data profiling:Understanding the data
Data quality management:Improving the quality of data
Data integration:Combining similar data from multiple
sourcesData augmentation:
Improving the value of the data
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Data Problems and Difficulties
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Exponential increase in the data volume with time.
Scattered data across organization collected and stored through various methods and devices.
Consideration of external data for decision making
Data security, quality and integrity.
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-cont…
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Selection of data management tools.
Validity of the data.Maintenance of data to eradicate
redundancy and obsolete.
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Solution to Managing Data
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Organizing data in a hierarchical format in one location.
Supports secured and efficient high-volume processing.
RDBMS add to facilitate end-user computing and decision support.
Data-warehousing.
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Data Life Cycle Process
Chapter 310
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Transactional vs. Analytical Data Processing
Chapter 311
Transactional processing takes place in operational systems (TPS) that provide the organization with the capability to perform business transactions and produce transaction reports.
The data are organized mainly in a hierarchical structure and are centrally processed. This is done primarily for fast and efficient processing of routine, repetitive data.
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-cont…
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Supplementary activity to transaction processing is called analytical processing, which involves the analysis of accumulated data.
Analytical processing, sometimes referred to as business intelligence, includes data mining, decision support systems (DSS), querying, and other analysis activities.
These analyses place strategic information in the hands of decision makers to enhance productivity and make better decisions, leading to greater competitive advantage.
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Data Sources
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Organizational Data: Organizational internal data about people, products, services, processes, equipment, machinery etc.
End User Data: Data created by the IS users or other corporate employees. They may include facts, concepts, thoughts and opinions.
External Data: Commercial databases, sensors, satellites, government reports, secondary storage devices, internet servers, etc..
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Methods for Collecting Raw Data
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Manually Surveys, observations, contributions from
experts..Electronically
H/W and S/W for data storage, communication, transmission and presentation.
Online surveys, online polls, data warehousing, website profiling, data that is scanned/transmitted. CLICKSTREAM DATA: Data that can be collected
automatically using special software from the company’s web site.
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Data QualityData quality determines the data’s
usefulness as well as the quality of the decisions based on the data.
Data quality dimensions:AccuracyAccessibilityRelevanceTimelinessCompleteness
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Categories of Data QualityStandardization (for consistency)Matching (of data if stored in different places)
Verification (against the source)Enhancement (adding of data to increase its usefulness)
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3-Step Method for DMAnalyzing the actual organizational
processesMoving on to analyzing the entities
that these elements compriseFinish by analyzing the relationship
between the data in the business processes that the data must support.
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??? To Understand Business FlowWhat information is input to the
process?What information is changed or
created during the process?What happens to the information
once the process is complete?What value-added information
does the process produce?
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Data Privacy, Cost and EthicsCollecting data raises the concern
about privacy protection.Data collected is about:
EmployeesCustomersOther people
Accessible to authorized people only.Reasonable costs for collection,
storage and use
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Document ManagementDM is the automated control of
electronic documents,page images, spreadsheets, voice word processing documents, and other complex documents through
their entire life cycle within an organization.
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Benefits of DMAllows organization to exert greater
control over production, storage and distribution of
documents,yielding greater efficiency in the reuse of
information ,the control of a documents through a
workflow process and the reduction of product cycle times.
Deals with knowledge,data and information.
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Major Tools for DMWorkflow softwareAuthoring toolsScannersDatabases
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DMSsDocument Management Systems:
provide decision makers with information in an electronic format and usually include computerized imaging systems that can result in substantial savings.
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Hierarchy of Data
Chapter 324
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Hierarchy of Data (cont’d)
Chapter 325
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The Data Warehouse & Data Management
Chapter 326
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Marketing Databases in ActionIntroduction:Data warehouses and data marts
serve end users in all functional areas.
Dramatic applications of DW and DM are seen in Marketing Databases.
Marketing today requires:New databases oriented towards
targeting personalizing marketing messages in real time.
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Marketing Transaction DatabasesMD provides effective means of capturing
information on customer preferences and needs.
Enterprises, use this knowledge to create new and/or personalized products and services.
Combines many of the characteristics of current databases and marketing data sources into a new database that allows marketers to engage in real-time personalization and target every interaction with customers.
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Web-based Data Management Systems – content and information
Chapter 329
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Managerial Issues
Chapter 330
Cost-benefit issues and justification
Where to store data physically
Legal issues
Internal or external?
Data Delivery
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Managerial Issues (Continued)
Chapter 331
Disaster recovery
Data security and ethics
Ethics: Paying for use of data
Privacy
Legacy Data