ECOM 500 RGC Data Management Analytic & Business Intelligence Discussion

Description

Select an international organization, outside of the KSA, that utilizes Business Intelligence (BI) and provide a brief description (e.g., mission, vision, values, and industry) of that organization. Then, address the following questions:

How does the organization use BI?
What benefits and drawbacks does this organization encounter when using BI?
How might your current or a past employer use BI?

Embed course material concepts, principles, and theories, which require supporting citations along with at least two scholarly peer reviewed references supporting your answer. Keep in mind that these scholarly references can be found by conducting an advanced search specific to scholarly references.

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IT for Management: On-Demand Strategies for
Performance, Growth, and Sustainability
Eleventh Edition
Turban, Pollard, Wood
Chapter 3
Data Management, Business Intelligence,
and Data Analytics
Learning Objectives (1 of 5)
Copyright ©2018 John Wiley & Sons, Inc.
2
Database Technologies: Databases
• Collections of data sets or records stored in a
systematic way
• Stores data generated by business apps, sensors,
operations, and transaction-processing systems (TPS)
• The data in databases are extremely volatile
• Medium and large enterprises typically have many
databases of various types
Volatile data changes frequently.
Copyright ©2018 John Wiley & Sons, Inc.
3
Database Technologies: Data Warehouses
• Integrate data from multiple databases and data silos,
and organize them for complex analysis, knowledge
discovery, and to support decision making
• May require formatting processing and/or
standardization
• Loaded at specific times making them non-volatile and
ready for analysis
Copyright ©2018 John Wiley & Sons, Inc.
4
Database Technologies: Data Marts
• Small-scale data warehouses that support a single
function or one department
• Enterprises that cannot afford to invest in data
warehousing may start with one or more data marts
Copyright ©2018 John Wiley & Sons, Inc.
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Database Technologies: BI
• Business Intelligence (BI)
o
o
Tools and techniques that process data and conduct statistical
analysis for insight and discovery
Used to discover meaningful relationships in the data, keep
informed of real time, detect trends, and identify
opportunities and risks
Copyright ©2018 John Wiley & Sons, Inc.
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Database Management Systems (DBMS)
• Integrate with data collection systems such as TPS and business
applications
• Organized way to store, access, and manage data
• Stores data in tables consisting of columns and rows, similar to
the format of a spreadsheet
• Standard database model adopted by most enterprises
• Functions include:
o
o
o
o
o
Data filtering and profiling
Data integrity and maintenance
Data synchronization
Data security
Data access
Copyright ©2018 John Wiley & Sons, Inc.
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Database Technologies: SQL
• Relational Database Management Systems (DBMS)
o
Provides access to data using a declarative language
• Declarative language
o
o
Simplifies data access by requiring that users only specify
what data they want to access without defining how they will
be achieved
Structured Query Language (SQL) is an example of declarative
language:
SELECT column_name(s)
FROM table_name
WHERE condition
Copyright ©2018 John Wiley & Sons, Inc.
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OLTP and OLAP Systems
Online Transaction Processing and Online Analytics Processing
• Online Transaction Processing (OLTP)
• Designed to manage transaction data, which are volatile & break
down complex information into simpler data tarbles and strike a
balance between transaction-processing efficiency and query
efficiency
• Cannot be optimized for data mining
• Online Analytics Processing (OLAP)
• A means of organizing large business databases
• Divided into one or more cubes that fit the way business is conducted
Copyright ©2018 John Wiley & Sons, Inc.
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Database Technologies: NOSQL
• Trend toward NoSQL Systems
o Higher performance
o Easy distribution of data on different nodes
• Enables scalability and fault tolerance
o Greater flexibility
o Simpler administration
Copyright ©2018 John Wiley & Sons, Inc.
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Popular DBMS
• DBMSs (mid-2016)
o
o
o
o
o
Oracle’s 12C Database
Microsoft’s SQL Server
IBM’s DB2
SAP Sybase Ase
PostgreSQL
Copyright ©2018 John Wiley & Sons, Inc.
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Data Management and Database
Technologies
1. Describe a database and database management system
(DBMS).
2. Explain what an online transaction-processing (OLAP)
system does.
3. Why are data in databases volatile?
4. Describe the functions of a DBMS.
5. Describe the purpose and benefits of data
management.
6. What is a relational database management system?
Copyright ©2018 John Wiley & Sons, Inc.
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Learning Objectives (2 of 5)
Copyright ©2018 John Wiley & Sons, Inc.
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Centralized and Distributed Database
Architecture
• Centralized Database Architecture
o
o
Better control of data quality
Better IT security
• Distributed Database Architecture
o
o
Allow both local and remote access
Use client/server architecture to process requests
Copyright ©2018 John Wiley & Sons, Inc.
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Dirty Data
Garbage In, Garbage Out
• Dirty Data
• Lacks integrity/validation and reduces user trust
• Incomplete, out of context, outdated, inaccurate, inaccessible, or
overwhelming
Copyright ©2018 John Wiley & Sons, Inc.
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Characteristics of Poor Quality or Dirty
Data
Characteristic
Description
Incomplete
Missing data
Outdated or Invalid
Too old to be valid or useful
Incorrect
Too many errors
Duplicated or in
conflict
Too many copies or versions of the same data—and the versions
are inconsistent or in conflict with each other
Non-standardized
Data are stored in incompatible formats—and cannot be
compared or summarized
Unusable
Data are not in context to be understood or interpreted correctly
at the time of access
Copyright ©2018 John Wiley & Sons, Inc.
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Data Life Cycle and Data Principles (1 of 2)
• Principle of Diminishing Data Value
The value of data diminishes as they age
o Blind spots (lack of data availability) of 30 days or longer
inhibit peak performance
o Global financial services institutions rely on near-real-time
data for peak performance
o
• Principle of 90/90 Data Use
o
o
As high as 90 percent, is seldom accessed after 90 days
(except for auditing purposes)
Roughly 90 percent of data lose most of their value after 3
months
Copyright ©2018 John Wiley & Sons, Inc.
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Data Life Cycle and Data Principles (2 of 2)
• Principle of data in context
o
o
The capability to capture, process, format, and distribute data
in near real time or faster requires a huge investment in data
architecture
The investment can be justified on the principle that data
must be integrated, processed, analyzed, and formatted in
“actionable information”
Copyright ©2018 John Wiley & Sons, Inc.
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Figure 3.11 Data life cycle
Copyright ©2018 John Wiley & Sons, Inc.
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Figure 3.12 An enterprise has transactional, master, and analytical data.
Copyright ©2018 John Wiley & Sons, Inc.
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Centralized and Distributed Database
Architectures
1. Describe the data life cycle.
2. What is the function of master data management
(MDM)?
3. What are the consequences of not cleaning “dirty
data”?
4. Describe the differences between centralized and
distributed databases.
5. Discuss how data ownership and organizational politics
affect the quality of an organization’s data.
Copyright ©2018 John Wiley & Sons, Inc.
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Learning Objectives (3 of 5)
Copyright ©2018 John Wiley & Sons, Inc.
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Data Warehouses: Enterprise data
warehouses (EDW)
• Data warehouses that pull together data from disparate
sources and databases across an entire enterprise
• Warehouses are the primary source of cleansed data
for analysis, reporting, and Business Intelligence (BI)
• Their high costs can be subsidized by using data marts
Copyright ©2018 John Wiley & Sons, Inc.
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Data Preparation: Procedures to Prepare
EDW Data for Analytics
• Extract from designated databases
• Transform by standardizing formats, cleaning the data,
integration
• Loading into a data warehouse
Copyright ©2018 John Wiley & Sons, Inc.
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Figure 3.15 Database, data warehouses and marts, and BI architecture.
Copyright ©2018 John Wiley & Sons, Inc.
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Data Warehouses: ADW
• Active Data Warehouse (ADW)
o
o
Real-time data warehousing and analytics
Transform by standardizing formats, cleaning the data,
integration
• They provide
Interaction with a customer to provide superior customer
service
o Respond to business events in near real time
o Share up-to-date status data among merchants, vendors, and
associates
o
Copyright ©2018 John Wiley & Sons, Inc.
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Data Warehouse Processing: Hadoop
and MapReduce
• Hadoop is an Apache processing platform that places
no conditions on the processed data structure
• MapReduce provides a reliable, fault-tolerant software
framework to write applications easily that process vast
amounts of data (multi-terabyte datasets) in-parallel on
large clusters (thousands of nodes) of commodity
software
o Map stage: breaks up huge data into subsets
o Reduce stage: recombines partial results
Copyright ©2018 John Wiley & Sons, Inc.
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Data Warehouses
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 active data warehouse (ADW)?
6. Why might a company invest in a data mart?
7. How can manufacturers and health care benefit from data
analytics?
8. Explain how Hadoop implements MapReduce in two stages.
Copyright ©2018 John Wiley & Sons, Inc.
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Learning Objectives (4 of 5)
Copyright ©2018 John Wiley & Sons, Inc.
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Data Analytics and Data Discovery
Defined
• Data Analytics is a technique of qualitatively or
quantitatively analyzing a data set to reveal pattersn,
trends, and associations that often relate to human
behavior and interaction, to enhance productivity and
business gain.
• Big data is an extremely large data set that is too large
or complex to be analyzed using traditional data
processing techniques.
Copyright ©2018 John Wiley & Sons, Inc.
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Four V’s of Data Analytics
1. Variety: The analytic environment has expanded from pulling
data from enterprise systems to include big data and
unstructured sources.
2. Volume: Large volumes of structured and unstructured data are
analyzed.
3. Velocity: Speed of access to reports that are drawn from data
defines the difference between effective and ineffective
analytics.
4. Veracity: Validating data and extracting insight that manager and
workers can trust are key factors successful analytics. Trust in
analytics. Trust analytics has grown more difficult with the
explosion of data sources.
Copyright ©2018 John Wiley & Sons, Inc.
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Data Analytics: Human Expertise is
Needed
• To interpret the output of analytics, Big Data Specialists
and Business Intelligence Analysts perform many tasks
o Data preparation for analysis through data cleansing
techniques, to eliminate duplicates or incomplete
data
o Dirty data degrade the value of analytics
o Data must be put into meaningful context
Copyright ©2018 John Wiley & Sons, Inc.
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Data Discovery: Data and Text Mining
• Creating Business Value
o Data Mining: software that enables users to analyze
data from various dimension or angles, categorize
them, and find correlative patterns among fields in
the data warehouse
o Text Mining: broad category involving interpreted
words and concepts in context
o Sentiment Analysis: trying to understand consumer
intent
Copyright ©2018 John Wiley & Sons, Inc.
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Data Analytics and Data Discovery
1. Why are human expertise and judgment important to data
analytics? Give an example.
2. What is the relationship between data quality and the value of
analytics?
3. Why do data need to be put into a meaningful context?
4. How can manufacturers and health care benefit from data
analytics?
5. How does data mining provide value? Give an example.
6. What is text mining? ?
7. What are the basic steps involved in text analytics?
Copyright ©2018 John Wiley & Sons, Inc.
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Learning Objectives (5 of 5)
Copyright ©2018 John Wiley & Sons, Inc.
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Business Intelligence: Key to competitive
advantage
• Across industries in all size enterprises
• Used in operational management, business process,
and decision making
• Provides moment of value to decision makers
• Unites data, technology, analytics, & human knowledge
to optimize decisions
• BI “unites data, technology, analytics, and human
knowledge to optimize business decision and ultimately
drive an enterprise’s success” (The Data Warehousing
Institute)
Copyright ©2018 John Wiley & Sons, Inc.
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Business Intelligence Challenges
• Challenges
o
o
Data selection and quality
Alignment with business strategy and BI strategy
• Alignment
Clearly articulates business strategy
o Deconstructs business strategy into targets
o Identifies PKIs
o Prioritizes PKIs
o Creates a plan based on priorities
o Transform based on strategic results and changes
o
Copyright ©2018 John Wiley & Sons, Inc.
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Figure 3.17: Business Intelligence Factors: Four factors contributing to increased
use of BI
Copyright ©2018 John Wiley & Sons, Inc.
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Business Intelligence Architecture
• Advances in response to big data and end-user
performance demands
• Hosted on public or private clouds
• Limits IT staff and controls costs
• May slow response time, add security and backup risks
Copyright ©2018 John Wiley & Sons, Inc.
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Electronic Records Management
• Business Records
o
Documentation of a business event, action, decision, or
transaction
• Electronic Records Management (EMR)
o
o
o
Workflow software, authoring tools, scanners, and databases
that manage and archive electronic documents and image
paper documents
Index and store documents according to company policy or
legal compliance
Success depends on partnership of key players
Copyright ©2018 John Wiley & Sons, Inc.
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ERM Practices and Standards
• Best Practices
o
o
Effective systems capture all business data
Input from online forms, bar codes, sensors, websites, social
sites, copiers, emails, and more
• Industry Standards
o
o
o
Association for Information and Image Management (AIIM;
www.aim.org)
National Archives and Records Administration (NARA;
www.archives.gov)
ARMA International (formerly the Association of Records
Managers and Administrators; www.arma.org)
Copyright ©2018 John Wiley & Sons, Inc.
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ERM Benefits: an ERM can help a
business
• Access and use the content contained in documents
• Cut labor costs by automating business processes
• Reduce time and effort to locate require information
for decision making
• Improve content security, thereby reducing intellectual
property theft risks
• Minimize content printing, storing, and searching costs
Copyright ©2018 John Wiley & Sons, Inc.
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ERM: Disaster Recovery, Business
Continuity, and Compliance
1. Does the software meet the organization’s needs? For example,
can the DMS be installed on the existing network? Can it be
purchased as a service?
2. Is the software easy to use and accessible from Web browsers,
office applications, and email applications? If not, people will not
use it.
3. Does the software have lightweight, modern Web and graphical
user interfaces that effectively support remote users?
4. Before selecting a vendor, it is important to examine workflows
and how data, documents, and communications flow throughout
the company.
Copyright ©2018 John Wiley & Sons, Inc.
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Business Intelligence and Electronic Records
Management
1. What are the business benefits of BI?
2. What are two data-related challenges that must be resolved for
BI to produce meaningful insight?
3. What are the steps in a BI governance program?
4. What does it mean to drill down into data, and why is it
important?
5. What four factors are contributing to increased use of BI?
6. Why is ERM a strategic issue rather than simply an IT issue?
7. Why might a company have a legal duty to retain records? Give
an example.
8. Why is creating backups an insufficient way to manage an
organization’s documents?
Copyright ©2018 John Wiley & Sons, Inc.
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Copyright
Copyright © 2018 John Wiley & Sons, Inc.
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no responsibility for errors, omissions, or damages, caused by the use of these programs
or from the use of the information contained herein.
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