Chapter 3

1

Data Management: Data, Databases and Warehousing

Learning Objectives

2

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)

Learning Objectives (Continued)

3

Understand conceptual, logical, and

physical data

Understand ERD

The importance of Marketing

The Internet and Data Management

Introduction

4

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

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.

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

Data Problems and Difficulties

7

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.

-cont…

8

Selection of data management tools.

Validity of the data.Maintenance of data to eradicate

redundancy and obsolete.

Solution to Managing Data

9

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.

Data Life Cycle Process

Chapter 310

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.

-cont…

12

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.

Data Sources

13

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..

Methods for Collecting Raw Data

14

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.

Data QualityData quality determines the data’s

usefulness as well as the quality of the decisions based on the data.

Data quality dimensions:AccuracyAccessibilityRelevanceTimelinessCompleteness

15

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)

16

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.

17

??? 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?

18

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

19

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.

20

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.

21

Major Tools for DMWorkflow softwareAuthoring toolsScannersDatabases

22

DMSsDocument Management Systems:

provide decision makers with information in an electronic format and usually include computerized imaging systems that can result in substantial savings.

23

Hierarchy of Data

Chapter 324

Hierarchy of Data (cont’d)

Chapter 325

The Data Warehouse & Data Management

Chapter 326

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.

27

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.

28

Web-based Data Management Systems – content and information

Chapter 329

Managerial Issues

Chapter 330

Cost-benefit issues and justification

Where to store data physically

Legal issues

Internal or external?

Data Delivery

Managerial Issues (Continued)

Chapter 331

Disaster recovery

Data security and ethics

Ethics: Paying for use of data

Privacy

Legacy Data