Managing Data to Improve Business Performance · PDF file3.2 File Management Systems • Bit: Smallest unit of data; binary digit (0,1) • Byte: Group of bits that represents a single

Chapter 3

Managing Data to Improve Business Performance

Information Technology for Management Improving Performance in the Digital Economy

7th edition

John Wiley & Sons, Inc.

Slides contributed by Dr. Sandra Reid Chair, Graduate School of Business & Professor, Technology

Dallas Baptist University

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3-1 Copyright 2010 John Wiley & Sons, Inc.

[email protected]

Chapter Outline

3.1 Data, Master Data, and Data Management

3.2 File Management Systems

3.3 Database Management Systems

3.4 Data Warehouses, Data Marts, and Data Centers

3.5 Enterprise Content Management

3.6 Managerial Issues

3-2 Copyright 2010 John Wiley & Sons, Inc.

Figure IT 7eU The Business Performance Management Cycle and IT Model

Copyright 2010 John Wiley & Sons, Inc. 3-3

Applebee’s International Learns & Earns


Problem: Huge quantities of data in many Databases.

Solution: Enterprise data warehouse implemented.

Results: Improved profitability.

http://applebees.com/History.aspx

http://www.teradata.com/enterprise-data-warehouse

Figure 3.1 Applebee’s enterprise data warehouse and feedback loop.



3.1 Data, Master Data, and Document Management

Chapter 10 7

Data Management Concerns

• Data profiling – understanding the data.

• Data Quality Management – improving the quality of data.

• Data Integration – combining similar data from multiple sources.

• Data augmentation – improving the value of the data.

Building Blocks of Data Management:

Chapter 10 8

Data Management

• The amount of data increases exponentially with time.

• Data are scattered throughout organizations.

• Data are collected by many individuals using several methods.

• External data needs to be considered in making organizational decisions.

• Data security, quality, and integrity are critical.

• Selecting data management tools can be a major problem.

IT applications cannot be done without using some kind of data Which are at the core of management and marketing operations. However, managing data is difficult for various reasons.

Data are an asset, when converted to information and knowledge, give the firm competitive advantages.


• Importance

• Uncertainty: A Constant on Managers

• Data Management

Data Life Cycle 9


• Data Life Cycle – principles for IT Investment Decisions:

– Principle of diminishing data value

– Principle of 90/90 data use – 90% data is seldom used after 90 days.

– Principle of data in context

• Data Visualization - presentation

10

Figure 3.3


Dow Jones industrial average (DJIA) for a single day in tabular display and graphical display.

Data Visualization


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• Data management: problems and challenges

• Master Data Management (MDM)

• Transforming data into knowledge

13

Figure 3.4. Model of an enterprise data warehouse.


(Source: From Syncsort, synchsort.com. Used with permission.)

Data – Information – Knowledge -

Wisdom

Data - Factual information, especially information organized for analysis or used to reason or make decisions.

Information - Knowledge derived from study, experience, or instruction; Knowledge of a specific event or situation; intelligence


Wisdom

Knowledge - The state or fact of knowing. 2. Familiarity, awareness, or understanding gained through experience or study. 3. The sum or range of what has been perceived, discovered, or learned

Wisdom - Understanding of what is true, right, or lasting; insight; Common sense; good judgment


Wisdom

Data - Factual information,

Information - Knowledge of a specific event or situation;

Knowledge – something which has been discovered or learned

Wisdom - insight


• Data quality and Integrity

• Data privacy and ethical use

• Document Management

18

19

Data Quality and Integrity

• Intrinsic DQ: Accuracy, objectivity, believability, and reputation.

• Accessibility DQ: Accessibility and access security.

• Contextual DQ: Relevancy, value added, timeliness, completeness, amount of data.

• Representation DQ: Interpretability, ease of understanding, concise representation, consistent representation.

Data quality (DQ) is an extremely important issue since quality determines the data’s usefulness as well as the quality of the decisions based on the data. Data integrity means that data must be accurate, accessible, and up-to-date.

Data quality is the cornerstone of effective business intelligence.

Chapter 10 20

Document Management

• Maintaining paper documents, requires that:

• Everyone have the current version

• An update schedule be determined

• Security be provided for the document

• The documents be distributed to the appropriate individuals in a timely manner

Document management is the automated control of electronic documents, page images, spreadsheets, word processing documents, and other complex documents through their entire life cycle within an organization, from initial creation to final archiving.

Table 3.2





• Bit: Smallest unit of data; binary digit (0,1)

• Byte: Group of bits that represents a single character

• Field: Group of words or a complete number

• Record: Group of related fields

• File: Group of records of same type

• Database: Group of related files

• Data warehouse: Group of related databases

23

Figure 3.5 Example of primary and foreign keys.


Figure 3.6 Hierarchy of data for a computer-based file.


Figure 3.6 Hierarchy of data for a computer-based file.


Figure 3.7 Indexed sequential access method.


Figure 3.8


Computer-based files of this type cause problems such as redundancy, inconsistency, and data isolation.


• Accessing records from computer file: – Sequential

– Direct – random

– Indexed

29


• Limitations of data file environment: – Redundancy

– Inconsistency

– Isolation

– Security

– Lack of integrity

– Concurrency

30


3.3 Databases and Database Management Systems


• Centralized

• Distributed

32


Figure 3.9 (a) Centralized database. (b) Distributed database with complete or partial copies of the central database in more than one location.

Figure 3.10


Database management system provides access to all data in the database.


• Functions of Data Base Management Systems:

– Data filtering and profiling

– Data quality

– Data synchronization

– Data enrichment

– Data maintenance

35

Table 3.3

3-36




• Data base and data warehouse • Trends towards more real time support from

a data warehouse • Need for data warehousing • Benefits:

– Marketing and sales – Pricing and contracts – Forecasting – Sales performance – Financial

38

Figure 3.11 Data warehouse framework and views.



• Characteristics of data warehousing are: – Organization. Data are organized by subject

– Consistency. In the warehouse data will be coded in a consistent manner.

– Time variant. The data are kept for many years so they can be used for trends, forecasting, and comparisons over time.

– Nonvolatile. Once entered into the warehouse, data are not updated.

– Relational. Typically the data warehouse uses a relational structure.

– Client/server. The data warehouse uses the client/server architecture mainly to provide the end user an easy access to its data.

– Web-based. Data warehouses are designed to provide an efficient computing environment for Web-based applications

– Integration

– Real time

40

Figure 3.12 Teradata Corp.’s enterprise data warehouse.


(Source: Teradata Corporation [teradata.com], with permission.)


• Building a data warehouse: – Architecture and tools

– Putting it on intranet

– Suitability

• Data mart

• Consolidating data marts into enterprise data warehouse

• Data centre

42

Table 3.4

3-43

Selling

• Cross Selling - that of selling an additional product or service to an existing customer

• Up-selling - is a sales technique whereby a salesperson induces the customer to purchase more expensive items, upgrades, or other add-ons in an attempt to make a more profitable sale

Copyright 2010 John Wiley & Sons, Inc. 44

Table 3.5

3-45




• Four driving forces: – Growth

– Integration

– Support

– Governance

• Electronic record and document management

47

Figure 3.13


Electronic records management from creation to retention or destruction.


3.6 Managerial Issues

Managerial Issues

• Reducing uncertainty. • Cost-benefit issues & justification. • Where to store data physically. • Legal issues. • Internal or external collection, storage, maintenance, &

purging of databases of information. • Disaster recovery. • Data security & ethics. • Privacy. • Legacy systems. • Data delivery.


Documents

Managing Data to Improve Business Performance · PDF file3.2 File Management Systems • Bit: Smallest unit of data; binary digit (0,1) • Byte: Group of bits that represents a single