IT for Management: On-Demand Strategies for
Performance, Growth, and Sustainability
Twelfth Edition
Turban, Pollard, Wood
Chapter 3
Data Management, Data Warehouses, and
Data Governance
Learning Objectives (1 of 5)
Data
Management
Electronic
Document,
Record, and
Content
Management
Information
Management
Data
Warehouses
and Data
Marts
Data
Governance
and Master
Data
Management
(MDM)
Copyright ©2021 John Wiley & Sons, Inc.
2
Data Management (1 of 2)
• Oversees the end-to-end lifecycle of data from creation
and initial storage to the time when it becomes
obsolete and is deleted.
• The goals of effective data management include:
1.
2.
3.
4.
5.
6.
Mitigating the risks and costs of complying with regulations.
Ensuring legal requirements are met.
Safeguarding data security.
Maintaining accuracy of data and availability.
Certifying consistency in data that come from or go to
multiple locations.
Ensuring that data conform to organizational best practices
for access, storage, backup, and disposal.
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Data Management (2 of 2)
• Benefits of data management include:
1.
2.
3.
4.
5.
6.
greater compliance
higher security
less legal liability
improved sales and marketing strategies
better product classification
improved data governance to reduce risk.
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4
Data Management: Database
Technologies
• Database: A collection of data sets or records stored in
a systematic way
• Database management system: (DBMS) Software that
integrates with data collection systems to store data in an
organized way and provide facilities for accessing and managing
data.
• Data warehouse: Large data set that integrates data from
multiple databases and data silos across the organization, and
organizes them for complex analysis, knowledge discovery, and
to support decision-making.
• Data mart: A small-scale data warehouse that supports a single
function or one department.
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Data Management: Databases
• Transaction: a single logical unit of work that accesses
and possibly modifies the contents of a database.
• Centralized database: stores all data as a unified body
in a single central computer such as a mainframe or
server in one physical location.
• Distributed database: stores portions of the database
on multiple computers controlled by a database
management system (DBMS) within a network in a
client-server configuration.
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Data Management: Centralized
database
Benefits
1. Better control of data
quality
2. Ease of use
3. Better IT security
4. Better data integrity
Disadvantages
1. Transmission delay
2. Security
3. Reliability
4. Scalability
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Data Management: Distributed
databases
Advantages
1. Security
2. Reliability
3. Speed
4. Scalability
Disadvantages
1. Availability
2. Expense
3. Security
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Database Management System (DBMS)
• Online transaction processing (OLTP): a database
design that breaks down complex information into
simpler data tables to strike a balance between
transaction processing efficiency and query efficiency.
• Online analytics processing (OLAP): the analysis of
complex data from a data warehouse.
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Database Management: Elements of a DBMS
• Four important elements:
1. data structure
2. data modeling language
3. data query language, and
4. transaction mechanisms.
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Elements of a DBMS: Data
structure
• A specialized format for organizing and storing
data. General data structures include, file,
record, table, tree, and so on.
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Elements of a
DBMS: Data
modeling language
•Approaches to the modeling
language of the DBMS include
hierarchical, network,
relational, and object-oriented.
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Data modeling
language: Network
A data model that allows
multiple records to be
linked to the same
parent.
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Data modeling
language:
Relational
•An approach to managing
data using a structure and
language that involves the
use of data tables to collect
groups of elements into
relations.
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Data modeling
language:
Object-Oriented
(OO)
•A data model that supports
the modelling and creation
of data entities as objects
that contain both data and
the relationships of those
data.
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Data modeling
language:
Blockchain
•A distributed ledger
represented by a sequential
chain of data blocks that
records transactions,
establishes identity of the
user, and establishes
contracts.
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Data modeling language: Blockchain
•
Blockchains are also designed to be secure and build trust.
•
The blocks in a blockchain are chained together using
cryptographically created keys (hash).
Hash: a function that takes an input value and outputs a unique
fixed-size hexadecimal number that is the cryptographically
created key for the data.
Proof-of-work and peer-to-peer network are two other
mechanisms that are used to boost the security of the
blockchain.
•
•
•
In all industry sectors, the level of trust and security that
currently only blockchain can offer is critical to a secure supply
chain.
Copyright ©2021 John Wiley & Sons, Inc.
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Elements of a DBMS:
Data Query Language
•Query is an ad hoc (unplanned)
user request for specific data.
• Structure Query Language (SQL) is the most widely-used mainstream
declarative language that works with any database to simplify data access by
requiring that users only declare what data they want rather than tell the
DBMS how to get it.
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• NoSQL is a non-relational database
query language.
Data
Query
Language:
Not Only
SQL
(NoSQL)
• The advantages of NoSQL include:
• higher performance
• easy distribution of data on different
nodes, which enables scalability and
fault tolerance
• greater flexibility
• simpler administration
• NewSQL is the latest type of
scalable database that supports a
SQL interface. It combines the
reliability of SQL and the speed and
performance of NoSQL to provide
better functionality and services
and provide database
administrators with ACID
performance guarantees.
Copyright ©2021 John Wiley & Sons, Inc.
22
DBMS Vendor Rankings
•
The top five enterprise database management
systems of 2019 are:
1. Oracle’s Database 18c,
2. Microsoft SQL Server 2019,
3. IBM DB2,
4. SAP Sybase ASE, and
5. PostgreSQL
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Data Management : Questions
1.
2.
3.
4.
Describe the purpose and benefits of data management.
Define a database and a database management system (DBMS).
What are the four elements of a DBMS?
Explain what an online transaction-processing (OLAP) system
does, and which database technology is most appropriate for its
use.
5. Describe the functions of a DBMS.
6. What is a relational database management system?
7. What are the main elements of a block in a blockchain?
8. What are the three mechanisms that help keep a blockchain
secure?
Copyright ©2021 John Wiley & Sons, Inc.
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Learning Objectives (2 of 5)
Data
Management
Electronic
Document,
Record, and
Content
Management
Information
Management
Data
Warehouses
and Data
Marts
Data
Governance
and Master
Data
Management
(MDM)
Copyright ©2021 John Wiley & Sons, Inc.
25
Data Warehouses and Data Marts
• Data warehouse is a central depository of integrated
data from one or more disparate sources.
• Data mart is a small-scale data warehouse that
supports a single function or one department.
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Moving Data from a Database to a Data
Warehouse or a Data Mart
• Data are moved in three main steps:
1. Extracted from designated databases.
2. Transformed by standardizing formats, cleaning the
data, and integrating them.
3. Loaded into a data warehouse.
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Building and Using a Data Warehouse
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Real-Time Support from an Active Data
Warehouse
•
Active data warehouse (ADW): the technical ability
to capture transactions when they change and
integrate them into the warehouse along with
maintaining bath or scheduled cycle refreshes.
• Companies with an ADW are able to:
• Interact with a customer to provide superior
customer service.
• Respond to business events in near real time.
• Share up-to-date status data among merchants,
vendors, customers, and associates.
Copyright ©2021 John Wiley & Sons, Inc.
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Data Warehousing Supports Action as
Well as Decisions
•
•
Data warehouses are infrastructure investments that
companies in a variety of industries make to support
ongoing and future operations, including: Marketing,
Pricing and contracts, Forecasting, Sales, and Financial
Enterprise data warehouses (EDWs) are data
warehouses that integrate data from many different
databases across an entire enterprise.
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Data Lakes
•A single store of structured,
semi-structured, and
unstructured enterprise data
stored in its natural format.
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Data Warehouses and Data Marts:
Questions
1. What are the differences between databases and data
warehouses?
2. What are the differences between data warehouses and data
marts?
3. Explain ETL.
4. Explain CDC.
5. What is an advantage of an enterprise data warehouse (EDW)?
6. Why might a company invest in a data mart instead of a data
warehouse?
7. What levels of an organization benefit most from a data
warehouse?
8. How is a data lake different from a data warehouse?
Copyright ©2021 John Wiley & Sons, Inc.
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Learning Objectives (3 of 5)
Data
Management
Electronic
Document,
Record, and
Content
Management
Information
Management
Data
Warehouses
and Data
Marts
Data
Governance
and Master
Data
Management
(MDM)
Copyright ©2021 John Wiley & Sons, Inc.
34
Data Governance and Master Data
Management (MDM)
• Data governance is the overall management of the
availability, usability, integrity, and security of data
used in an enterprise.
• Three industries that rely heavily on data governance:
• Food industry
• Financial services industry
• Health-care industry
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Master Data and Master Data
Management (MDM)
• Master data: the term used to describe businesscritical information on customers, products and
services, vendors, locations, employees, and other
things needed for operations and business transactions
• Master data management (MDM) integrates data from
various sources or enterprise applications to create a
more complete (unified) view of a customer, product,
or other entity.
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Master Reference File and Data Entities
• Data entity is anything real or abstract about which a
company wants to collect and store data.
• Master file is a collection of records describing one of
the main entities in a database, such as customers,
products, employees, and vendor. It is usually
periodically updated.
• Customer-centric is an approach to doing business that
focuses on providing a positive customer experience at
and after the point of sale to drive profit and gain
competitive advantage.
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Benefits of Data Governance and
Master Data Management
1. Improved regulatory compliance
2. More efficient decision-making
3. Improved data understanding
4. Increased revenue
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Data Governance and Master Data
Management (MDM): Questions
1. Explain why it is important to develop an effective data
governance program?
2. Explain the purposes of master data management.
3. Why has interest in data governance and MDM increased?
4. What are two ways that data is used in business?
5. What are three benefits of data governance.
Copyright ©2021 John Wiley & Sons, Inc.
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Learning Objectives (4 of 5)
Data
Management
Electronic
Document,
Record, and
Content
Management
Information
Management
Data
Warehouses
and Data
Marts
Data
Governance
and Master
Data
Management
(MDM)
Copyright ©2021 John Wiley & Sons, Inc.
42
Information Management
• Information management is the process of collecting,
storing, managing, and maintaining data that is
accurate, timely, reliable, valid, available, unique, and
relevant to an organization
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Data Life Cycle and Data Principles (1 of 2)
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44
Data Life Cycle and Data Principles (2 of 2)
• Three general data principles relate to the data life
cycle perspective and help guide IT investment
decisions. These are:
1. Principle of diminishing data value
2. Principle of 90/90 data use
3. Principle of data in context
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Breaking
Down Data
Silos
• Data silo are standalone data stores.
Their data are not
accessible by other
ISs that need it or
outside that
department.
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Culture Must Change
• Moving from silos to collaboration requires a culture
change:
1. Publicly acknowledge shared goals
2. Embrace the “why”
3. Culture comes from the top
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Garbage In, Garbage Out
• Dirty data are data of such poor quality that they
cannot be trusted or relied upon for decisions
• Inaccurate Data
• Missing Data
• Poorly Designed Interfaces
• Nonstandardized Data Formats
• Outdated Data
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The Cost of Dirty Data
• Lost business
• Time spent preventing errors
• Time spent correcting errors
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Information Management Benefits
1. Improved decision quality
2. Improved accuracy and reliability of management
predictions
3. Lower time and cost
4. Better data quality
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Information Management : Questions
1.
2.
3.
4.
What are the stages of the data lifecycle?
What is the function of master data management (MDM)?
What are the consequences of not cleaning “dirty data”?
What is the “silo effect” and how does it affect business
performance?
5. What three factors are driving collaboration and information
sharing?
6. What are the business benefits of information management?
7. Why is it important to have good information management
practices?
Copyright ©2021 John Wiley & Sons, Inc.
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Learning Objectives (4 of 5)
Data
Management
Electronic
Document,
Record, and
Content
Management
Information
Management
Data
Warehouses
and Data
Marts
Data
Governance
and Master
Data
Management
(MDM)
Copyright ©2021 John Wiley & Sons, Inc.
53
Electronic Document, Record,
and Content Management
• Electronic content is a collection of documents,
records, and unstructured data available as a broad
range of digital assets, such as audio, video, flash,
multimedia files, and so on.
• Electronic document is any paper, electronic form, file,
email, fax, contract, lease, and so on actively being
worked on.
• Electronic record is any document that has been made
final and is no longer meant to be altered.
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Electronic Document Management, EDMS,
and Electronic Records Management
• Electronic document management is the electronic
storage, maintenance, and tracking of electronic
documents and electronic images of paper-based
information.
• Electronic document management system is a
software system for creating, organizing, storing, and
retrieving different kinds of electronic documents.
• Electronic record management establishes policies and
standards for maintaining diverse types of records.
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Electronic Records Management Systems
• ERMS is the technology tool used to electronically manage the
creation and maintenance of records within classification
schemes, apply retention and disposal schedules, and control
access and use.
• ERMS can help a business by:
• Enabling the company to access and use the content
contained in documents.
• Cutting labor costs by automating business processes.
• Reducing the time and effort required to locate information
the business needs to support decision-making.
• Improving the security of content, thereby reducing the risk of
intellectual property theft.
• Minimizing the costs associated with printing, storing, and
searching for content.
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Enterprise Content Management and
ECMS
• Enterprise content management is the capture,
storage, retrieval, and management of a diverse set of
digital assets including documents, records, emails,
electronic communications, images, video, flash, audio,
and multimedia.
• Enterprise content management system (ECMS)
captures, preserves, and manages structured and
unstructured a wide variety of digital assets and
secures them digitally in compliance with policies.
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Choosing an EDMS, ERMS, or ECMS (1 of 2)
• When choosing an EDMS, ERMS, or ECMS it is important to
match the strategic needs of the company with the capabilities
of the system
• Critical differences between an EDMS and an ERMS:
1.
2.
EDMS users need to check in and check out stored
documents quickly and easily and unlock them for future
revision, while maintaining version tracking and histories of
access, whereas ERMS users require that records be kept
in their original format for retrieval for compliance or legal
reasons
Software security is essential in an ERMS, but only
desirable in a EDMS.
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Choosing an EDMS, ERMS, or ECMS (2 of 2)
• An ECMS has a broader mission. It differs from EDMS and ERMS
in that:
1. It is designed to facilitate record lifecycle management,
information governance, and collaboration.
2. An ECMS also provides a single source of trusted
information. It also provides version control and
synchronization, along with intuitive search and
discovery functions.
3. An ECMS also can integrate with other applications to
deliver viewable content across multiple platforms,
along with security and optimized business processes
in its content storage and retrieval systems
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Electronic Document, Record,
and Content Management: Questions
1.
Define the term “electronic content.”
2.
Describe the main differences between an electronic document and an
electronic record.
3.
Why do companies use an electronic records management system?
4.
Names three types of lawsuits that can be brought against a company
related to their electronic records.
5.
What characteristic of an ERMS allows employees to access and
change only the documents they are authorized to handle?
6.
What is the difference between an electronic document management
system (EDMS) and an electronic record management system (ERMS)?
7.
What is the shared goal of EDMS, ERMS, and ECMS?
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Copyright
Copyright © 2021 John Wiley & Sons, Inc.
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Operations Management
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Discussion 25
Description
25 points
Rubric Detail
Levels of Achievement
Criteria
Exceeds
Expectations
Meets
Expectation
Some
Expectations
Unsatisfactory
Quantity
5 to 6 points
3 to 4 points
1 to 2 points
0 to 0 points
Initial post and
two other posts
of substance.
Initial post and
one other post
of substance.
Initial post only.
Did not
participate.
5 to 6 points
3 to 4 points
1 to 2 points
0 to 0 points
Demonstrates
excellent
knowledge of
concepts, skills,
and theories
relevant to the
topic.
Demonstrates
knowledge of
concepts, skills,
and theories.
Demonstrates
satisfactory
knowledge of
concepts, skills,
and theories.
Did not
participate.
5 to 6 points
3 to 4 points
1 to 2 points
0 to 0 points
Discussion
post(s) exceed
expectations in
terms of support
provided and
extend the
discussion.
Discussion
post(s) meet
expectations in
terms of
support
provided.
Statements are
satisfactory in
terms of
support
provided.
Did not
participate.
6 to 7 points
4 to 5 points
1 to 2 points
0 to 0 points
Writing is well
organized, clear,
concise, and
focused; no
errors.
Some significant
but not major
errors or
omissions in
writing
organization,
focus, and
clarity.
Numerous
significant
errors or
omissions in
writing
organization,
focus, and
clarity.
Did not
participate.
Content
Support
Writing
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