MBUS673 - Business Intelligence
Chapter 1
An Overview of Business
Intelligence, Analytics, and
Decision Support
Contents and coverage:
• Managerial approach

Concepts, models etc.
• Hands-on realization

Software tools
Jason C. H. Chen, Ph.D.
Professor of MIS
School of Business Administration
Gonzaga University
Spokane, WA 99258
chen@jepson.gonzaga.edu
Data Mining
– Rapid Minder (free download) one user only
with full features
Business Performance Management
– AHP (Analytical Hierarchy Process) web version
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Dr. Chen, Business Intelligence
What is “Business Intelligence”?
Event Driven Alert - A Scenario
• Three transactions were posted in a credit
account while the account holder was
traveling in summer 2010:
• ”Business intelligence is the process of
making better decisions in an environment
that provides data and reporting that is
timely, reliable, consistent and
understandable in a useful format or
presentation”.
 Ranch 99 San Jose, California $102.33 Aug. 1, 2010


Exxon
Exxon
Austin, Texas $99.12 August 3, 2010
Houston, Texas $120.44 August 5, 2010
• What action will you (the credit company)
take and why?
• How the scenario can be detected?
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More Questions
Questions Posed in a BI seminar
• Why BI is on the agendas of the majority of
CIOs
• “I am not sure what BI really is these days,
but our execs tell me we need it.”


the question really is …
• “Why is BI suddenly such a hot topic with
our senior management team? We are
already using several end-user tools and yet
they want more!”
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because CIOs have become extremely aware of
BI’s importance in providing a competitive
differentiator at all levels of the business.
____________
• What is the primary goal of BI at the
enterprise level?

5
is to deliver _________
critical business information and
analysis from all data sources in context and in a
timely manner.
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1
DECISION MAKING
Goal of Business and Its Supporting
Decision Making Processes…
• Reasons for the growth of decision-making
information systems
People need to analyze large amounts of information
People must make decisions quickly
 People must apply sophisticated analysis techniques,
such as modeling and forecasting, to make good
decisions
 People must protect the corporate asset of
organizational information

MIS/
IT
Information
Decision
Making

Problem
Solving
Revenue/
Profit
DB,
____
DW
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DBQ: Explain the difference between transactional
information and analytical information. Be sure to
provide an example of each
DECISION MAKING
• Transactional information encompasses all of the
information contained within a single business
process or unit of work, and its primary purpose is
to support the performing of daily
_____ operational
________
tasks.
• Model – a
simplified
representation or
abstraction of
reality

Examples of transactional information include
withdrawing cash from an ATM or making an airline
reservation.
• Analytical information encompasses all
organizational information, and its primary
purpose is to support the performing of _________
managerial
analysis tasks.
• IT systems in
an enterprise

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Examples of analytical information include trends, sales,
and product statistics.
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Decisions in the Business
Major Roles of Information Systems
Decision Characteristics
Unstructured
Support of
Strategic
Advantage
(BI/BA/EIS)
Semistructured
Support of
Managerial
Decision Making
(DSS)
Structured
Support of
Business Operations (TPS)
Planning and Control of
Overall Organizational
Direction by Top Management
Strategic
Management
Tactical
Management
Operational
Management
Planning and Control
of Organizational
Subunits by Middle
Management
Planning and Control of
Day to Day Operations by
Supervisory Management
Which type of decision(s) is the target of BI?
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Enterprise Information Portals and DSS
Internet
History of the role of Information Systems
Extranet
Intranet
Enterprise Information Portal Gateway
1950-1960
1960-1970
Data
Processing
Management
Reporting
1970-1980
Decision
Support
1990 and
Beyond
1980-1990
Strategic &
End User
2010 and
Beyond
Electronic/Mobile BI/BA/ Social
Media
Commerce
Enterprise Information Portal User Interface
Search
Agents
OLAP
Data
Mining
DSS
What-If Models
Sensitivity Models
Goal-Seeking Models
Optimization Models
Knowledge
Management
Electronic
Data
Processing
- TPS
Database Management Functions
Data
Mart
_____
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Operational
Database
Other
Business
Applications
Analytical
_______
Database
Knowledge
Base
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Decision
Support
Systems
- Ad hoc
Reports
End User
Computing
Exec Info Sys
Expert Systems
SIS
E/M
Business &
Commerce
-Internetworked
E/M-Business &
Commerce
Analytical/
Predictive
Information;
Knowledge,
Social
Communication
 (PCs invented) 
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• Understand today's turbulent business
environment and describe how organizations
survive and even excel in such an environment
(solving problems and exploiting opportunities)
• Understand the need for computerized support of
managerial decision making
• Describe the business intelligence (BI)
methodology and concepts
• Understand the various types of analytics
Magpie Sensing Employs Analytics to
Manage a Vaccine Supply Chain
Effectively and Safely
• Company background
• Problem
• Proposed solution and results
• Answer & discuss the case questions
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Opening Vignette…
Opening Vignette…
Questions for the Opening Vignette
Questions for the Opening Vignette
1. What information is provided by the descriptive analytics
employed at Magpie Sensing?
2. What type of support is provided by the predictive
analytics employed at Magpie Sensing?
3. How does prescriptive analytics help in business decision
making?
4. In what ways can actionable information be reported in
real time to concerned users of the system?
5. In what other situations might real-time monitoring
applications be needed?
1. What information is provided by the descriptive analytics
employed at Magpie Sensing?
2. What type of support is provided by the predictive
analytics employed at Magpie Sensing?
3. How does prescriptive analytics help in business decision
making?
4. In what ways can actionable information be reported in
real time to concerned users of the system?
5. In what other situations might real-time monitoring
applications be needed?
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Opening Vignette…
Learning Objectives
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Management
Information
Systems
(DBMS)
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• 1. What information is provided by the
descriptive analytics employed at Magpie
Sensing?
• 2. What type of support is provided by the
predictive analytics employed at Magpie Sensing?
• The predictive analytics use the descriptive data to
alert users when a unit is not configured properly
for storing the products. It also sends an alert when
average temperature and compressor cycle runs
signal that a temperature may go out of range (for
example, after a power failure) or that there may
have been a human error, such as failure to shut a
door.
• These analytics tell users about a problem that may
occur, giving them time to prevent the problem.
• The descriptive analytics monitor and report the
properties of the cold storage system, including
the set point of each thermostat, the typical range
of temperatures in the system, and the duty cycle
of each compressor. These values tell trained
personnel whether each storage unit is properly
configured for storing particular products.
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• 3. How does prescriptive analytics help in business decision
making?
• Prescriptive analytics guides decision makers to the
alternative with the greatest benefits. In Magpie’s cold chain
system, prescriptive analytics uses data about storage unit
performance to help buyers select the best storage units. And
based on data about storage system efficiency and product
sensitivity, prescriptive analytics guides decisions about
where to distribute particular products in the supply chain.
• 4. What are possible ways to report actionable information
in real time to the concerned users of the system?
• The system uses shippable wireless monitors. These
continuously measure temperature, humidity, and location
and transmit the data to the computer that analyzes the data.
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• 5. What other situations might need real-time monitoring
applications?
• Answers will vary, but students should consider other
systems where current performance provides information
about changes or decisions that would improve future
performance.
• Examples include monitoring inventory levels at a
manufacturing company to determine when to replenish
stocks, monitoring sales in a store to identify when and
how to adjust the mix of products, and monitoring patient
status in a hospital to identify situations where different
treatment is required or devices are malfunctioning.
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Fig. 1.1: Business Pressures – Responses – Support Model
1.2 Changing Business Environment &
Computerized Decision Support Model
[Business Pressure]
• Companies are moving aggressively to
computerized support of their operations =>
Business Intelligence
• Business Pressures–Responses–Support
Model
Business pressures result of today's competitive
business climate
 Responses to counter the pressures
 Support to better facilitate the process for
making (or improving) better decision
[Response/Action]
[IT/Computerized
Support]

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Be Reactive, Anticipative,
Adaptive, and Proactive
Managers must respond quickly,
innovatively,
agile.
_________ and be ______
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AHP and
Data mining tool
(Rapid-Miner)
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Table 1.1 Business Environment Factors that
Create Pressures on Organizations
The Business Environment
• The environment in which organizations
operate today is becoming more and more
complex, creating:
FACTOR
DESCRIPTION
Markets
Strong competition
Expanding global markets
Blooming electronic markets on the Internet
Innovative marketing methods
Opportunities for outsourcing with IT support
Need for real-time, on-demand transactions
Desire for customization
Desire for quality, diversity of products, and speed of delivery
Customers getting powerful and less loyal
More innovations, new products, and new services
Increasing obsolescence rate
Increasing information overload
Social networking, Web 2.0 and beyond
Growing government regulations and deregulation
Workforce more diversified, older, and composed of more women
Prime concerns of homeland security and terrorist attacks
Necessity of Sarbanes-Oxley Act and other reporting-related legislation
Increasing social responsibility of companies
Greater emphasis on sustainability
Consumer
demand
opportunities, and
problems.
 Example: globalization.

Technology

Societal
• Business environment factors:

markets, consumer demands, technology, and
societal.
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Managers must respond quickly, innovate, and be agile.
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Organizational Responses
Closing the Strategy Gap
• One of the major objectives of
computerized decision support is to
facilitate closing the gap between the
current performance of an organization and
its desired performance, as expressed in its
mission, objectives, and goals, and the
strategy to achieve them.
• Be Reactive, Anticipative, Adaptive, and
Proactive
• Managers may take actions, such as






Employ strategic planning.
Use new and innovative business models.
Restructure business processes.
Participate in business alliances.
Improve corporate information systems.
… more [in the book]
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(AHP and
Current
performance
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1.2 A Framework for Business
Intelligence (BI)
Gap? Data mining tool Rapid-Miner)
Desired
performance
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1.3 A Framework for Business Intelligence (BI)
• BI is an evolution of decision support concepts over
time.

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Meaning of EIS/DSS…
Then: Executive Information System
Now: Everybody’s Information System (BI)
• BI systems are enhanced with additional visualizations,
alerts, and performance measurement capabilities.
• BI's major objective is to enable easy (interactive)
access to data (and models) to provide business
managers with the ability to conduct analysis.
information (and
data to ___________
• BI helps transform _______,
knowledge), to __________
action.
decisions and finally to ________.
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Business Intelligence (BI) – cont.
The Process of BI
• BI is an umbrella term that combines architectures, tools,
databases, analytical tools, applications, and methodologies
• The first is the business aspect of BI


the need to get the most value out of information.
this need hasn’t really changed in over fifty years (although the
increasing complexity of the world economy means it’s ever
harder to deliver).
• The second is the IT aspect of BI

what technology is used to help provide the business need. This
obviously does change over time — sometimes radically.
• In summary, BI helps transform data, to information (and
knowledge), to decisions and finally to action.
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Data
Warehouse
+
•Situations
•Performance
Informed and
better
Decisions
ACTIONS
(DW vs. DB)
Definition of BI:
•BI can be considered as an integrated solution suite, where its
power and functionality may be utilized by anyone who touches
data within a particular context.
•In general, BI is the application of end-user query, reporting,
dashboards, and other non-programming technologies to provide
information that is not available to the business using traditional
programming methods and services. (The New Era of Enterprise BI, Mike Biere, 2001)
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Fig. 1.2: The Evolution of BI Capabilities
A Brief History of BI
• The term BI was coined by the Gartner
Group in the mid-1990s
• However, the concept is much older





1970s — MIS reporting — static/periodic reports
1980s — Executive Information Systems (EIS)
1990s — OLAP, dynamic, multidimensional, ad-hoc
reporting -> coining of the term “BI”
2010s - Data/Text/Web Mining; Web-based Portals,
Dashboards, Big Data, Social Media, and Visual
Analytics
2020s - yet to be seen
Video: History of Business Intelligence (10m 36s)
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• Metadata:

The Architecture of BI
data about data – data dictionary of a database
• ETL:

Extraction, transformation and load (raw data) – taking data from a
transactions processing system, cleaning it up, and moving to a data
warehouse.
• A BI system has four major components:
warehouse with its source data
1. a data _________,
analytics (or analytical environment)
2. business ________,
a collection of tools for manipulating, mining, and
analyzing the data in the data warehouse;
 3. business performance
_________ management
_________ (BPM) for
monitoring and analyzing performance
interface (e.g., dashboard)
 4. a user _______

• Data Warehouse:


Mostly historical data for analysis of corporate performance, can contain
current data for online transaction processing – e.g. Teradata warehouse
system
• Data Marts:

Smaller (particular subject or department) and more focused than a data
warehouse - marketing data mart as a subset of a corporate data
warehouse
• DSS:

Decision Support System - System to help managers in decision making,
e.g., for mortgage loan decisions, project selections, etc.
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Fig. 1.3: A High-level Architecture of BI
1.
2.
Components in a BI Architecture
3.
warehouse is the cornerstone
• The data ___________
of any medium-to-large BI system.
Originally, the data warehouse included only
historical data that was organized and
summarized, so end users could easily view or
manipulate it.
 Today, some data warehouses include access
to current data as well, so they can provide
real-time decision support (for details see
Chapter 2).

4.
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Data Marts and the
Data Warehouse
Position of the Data Warehouse Within the
Organization
and Load
(We will experience it using Rapid-Miner.)
Legacy
systems feed
data to the
warehouse.
Legacy Systems
Finance
Data Mart
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Marketing
Data Mart
ETL
Operational Data
Store
Accounting
Data Mart
ETL
Operational Data
Store
Organizational
Data
Warehouse
Operational Data
Store
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Dependent data mart with operational data
store: a three-level architecture
Data marts:
Sales
Data Mart
Operational Data
Store
The
warehouse
feeds
specialized
information
to
departments
(data marts).
Independent data mart data
warehousing architecture
ETL: Extract, Transform
Mini-warehouses, limited in scope
ODS provides option for
obtaining current data
L
L
T
T
E
Separate ETL for each
independent data mart
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E
Data access complexity
due to multiple data marts
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Single ETL for
enterprise data warehouse (EDW)
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Simpler data access
Dependent data marts
loaded from EDW
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Logical data mart and real time
warehouse architecture
ODS and data warehouse
are one and the same
Components in a BI Architecture
• Business analytics are the tools that help users
transform data into knowledge (e.g., queries,
data/text mining tools, etc.).
L
T
E
Near real-time ETL for
Data Warehouse
Data marts are NOT separate databases,
but logical views of the data warehouse
 Easier to create new data marts
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Business Analytics –
another perspective
Components in a BI Architecture
• Business Analytics (BA) is an ________
umbrella term including
warehousing business ____________
intelligence , enterprise
data ___________,
information management, enterprise performance
management, analytic applications, and governance, risk,
and compliance.
technologies and
• Business Intelligence (BI) is a set of ____________
processes used to describe business performance.
___________
• Companies find success through better use of analytics.
• Many companies offer similar products and user
comparable technologies.
• Business processes are among the last remaining points of
differentiation.
fact
• Focus on ____-based
management to drive decision making.
• Business Performance Management (BPM),
which is also referred to as corporate performance
management (CPM), is an emerging portfolio of
applications within the BI framework that provides
enterprises tools they need to better manage their
operations (for details see Chapter 3).
• User Interface (i.e., dashboards) provides a
comprehensive graphical/pictorial view of
corporate performance measures, trends, and
exceptions.
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Business Intelligence vs.
Business Analytics
What's The Difference? Business Analytics vs
Business Intelligence
• Business Analytics (BA) is a close cousin of Business
Intelligence (BI). Both are meant to help companies
make better decisions by analyzing business data. The
difference is in their methods, and in the general
direction of their analysis.
• Business Intelligence, the most common form,
data from the present and the
concentrates on ______
immediate past, and drawing conclusions from that.
• Business Analytics makes more of an effort to predict
the future using more complex tools relying heavily on
statistics to neural nets.
anything from _________
• Business Intelligence

traditionally focuses on using a consistent set of metrics to
performance
both measure past ___________and
guide business planning
_______.
• Business Analytics

insights and understanding of
focuses on developing new ________
business performance
What’s the difference between Business Analytics and Business
Intelligence? The correct answer is: everybody has an opinion,
shouldn’t care
but nobody knows, and you _________
http://it.toolbox.com/blogs/inside-erp/whats-the-difference-business-analytics-vs-business-intelligence-58672
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While the terms business intelligence and business analytics are
often used interchangeably, there are some key differences:
BI vs BA
Answers the questions:
Includes:
Business Intelligence
What happened?
________
Business Analytics
When ?
_______
Will it happen again?
Who ?
_______
What will happen if we change x?
many ?
How ______
What else does the data tell us that
never thought to ask?
Reporting (KPIs, metrics)
Statistical/Quantitative Analysis
Business Analytics (cont.)
• Davenport and Harris
suggest that companies
who are successful
competing with business
analytics have these five
capabilities:
Why did it happen?
Automated Monitoring/Alerting Data Mining
(thresholds)
Predictive Modeling
Dashboards
Multivariate Testing
Scorecards

OLAP (Cubes, Slice & Dice,
Drilling)




Data Mining
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Ad hoc query
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Hard to duplicate
Uniqueness
Adaptability
Better than competition
Renewability




Table 1.2 Business Value of BI Analytical Applications
Business Value
Customer
segmentation
What market segments do my
customers fall into, and what are their
characteristics?
Personalize customer relationships for
higher satisfaction and retention.
Propensity to buy
Which customers are more likely to
respond to my promotion?
Target customers based on their need
to increase their loyalty to your
product line.
Also, increase campaign profitability
by focusing on the most likely to buy.
Customer
profitability
What is the lifetime profitability of my
customer?
Make individual business interaction
decisions based on the overall
profitability of customers.
Fraud protection
How can I tell which transactions are
likely fraudulent?
Quickly determine fraud and take
immediate action to minimize cost.
Customer attrition
Which customer is at risk of leaving?
Prevent loss of high-value customers
and let go of lower-value customers.
Channel
optimization
What is the best channel to reach my
customer in each segment?
Interact with customers based on their
preference and your need to manage
cost.
Faster, more accurate reporting (81%)
Improved decision making (78%)
Improved customer service (56%)
Increased revenue (49%)
• See Table 1.2 for a list of BI analytics
applications, the business questions they answer
and the business value they bring.
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Business Question
50
• The ability to provide accurate information when
needed, including a real-time view of the
corporate performance and its parts
• A survey by Thompson (2004)
if more than one-third of the time and money
spent on a project is spent on technology, the
project becomes an IT project rather than a KM
project.
Analytic
Application
valuable,
rare,
non-imitable,
non-transferable,
non-substitutable,
combinable, and
exploitable
The Benefits of BI
• According to Davenport and Prusak point
33 1/3 % rule,”
out in their “________
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–
–
–
–
–
–
–
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KM Project vs. IT Project

• Characteristics of strategic
resources are:
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1.4 Intelligence Creation and Use
Data Warehouse
A Cyclical Process of
Intelligence Creation And
Use
 Data warehouse and BI
initiatives typically
follow a process similar
to that used in military
intelligence initiatives
depicted in this figure.
 Pre-condition:
a data warehouse
must be in place.
Source: A. Ziama and J. Kasher (2004), Data Mining Primer for the Data Warehousing Professional. Dayton, OH: Teradata.
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Fig. 1.4: Process of Intelligence Creation and Use.
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Intelligence Creation and Use
BI Governance Issues/Tasks
• Steps Involved


Data warehouse deployment (pre-condition)
Creation of intelligence
1.
Identification and prioritization of BI projects
– By using ROI and TCO (total cost ownership-benefit
analysis)
– This process is also called BI governance
2.
3.
4.
• BI Governance

5.
Who should do the prioritization?
Partnership between functional area heads and/or
product/service area leaders (middles)
Partnership between customers and providers
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• Stealing corporate secrets, CIA, …
• Transaction processing systems are constantly
involved in handling updates (add/edit/delete) to
what we might call operational databases.
Intelligence vs. Espionage
• Intelligence
The way that modern companies ethically and legally
organize themselves to glean as much as they can from
their customers, their business environment, their
stakeholders, their business processes, their competitors,
and other such sources of potentially valuable
information



• Problem – too much data, very little value


Use of data/text/Web mining (see Chapters 4, 5)
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Transaction Processing vs. Analytic Processing
(OLTP vs. OLAP)
ATM withdrawal transaction, sales order entry via an
ecommerce site – updates DBs
Online transaction processing (OLTP) handles routine
on-going business
ERP, SCM, CRM systems generate and store data in
OLTP systems
efficiency
The main goal is to have high _________



More on OLTP vs. OLAP
Routine sales reports by product, by region, by sales
person, etc.
Often built on top of a data warehouse where the data is
not transactional
effectiveness (and then, efficiency) –
Main goal is ____________
provide correct information in a timely manner
More on OLAP will be covered in Chapter 2
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• Online analytic processing (OLAP) systems are
involved in extracting information from data stored
by OLTP systems

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1.5 Transaction Processing vs. Analytic Processing
(OLTP vs. OLAP)
Intelligence and Espionage

Create categories of projects (investment,
business opportunity, strategic, mandatory, etc.)
Define criteria for project selection
Determine and set a framework for managing
project risk
Manage and leverage project interdependencies
Continuously monitor and adjust the composition
of the portfolio
Fig. Extra-a: A simple
database with a relation
between two tables.
For those have database
background.
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• The figure depicts a relational
database environment with two
tables.
• The first table contains information
about pet owners; the second,
information about pets. The tables
are related by the single column
they have in common: Owner_ID.
• By relating tables to one another,
redundancy of
we can reduce ____________
data and improve database
performance.
• The process of breaking tables
apart and thereby reducing data
redundancy is called
normalization
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_______________.
10
OLTP vs. OLAP (cont.)
OLTP vs. OLAP (cont.)
• In order to keep our transactional databases running quickly and smoothly, we
may wish to create a data warehouse. A data warehouse is a type of large
database (including both current and historical data) that has been
denormalized
_____________ and archived.
• Denormalization is the process of intentionally combining some tables into a
single table in spite of the fact that this may introduce duplicate data in some
columns.
• Most relational databases which are designed to handle a high number of reads
OLTP
and writes (updates and retrievals of information) are referred to as ________
(OnLine Transaction Processing) systems.
• OLTP systems are very efficient for high volume activities such as cashiering,
where many items are being recorded via bar code scanners in a very short
period of time.
• However, using OLTP databases for analysis is generally not very efficient,
because in order to retrieve data from multiple tables at the same time, a query
joins must be used.
containing ________
Fig. Extra-b: A combination of the tables into a single dataset.
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• The figure depicts what our simple example data might look like if it were in a
data warehouse. When we design databases in this way, we reduce the number
of joins necessary to query related data, thereby speeding up the process of
analyzing our data.
OLAP (OnLine Analytical
• Databases designed in this manner are called __________
Processing) systems.
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OLTP vs. OLAP (cont.)
1.6 Successful BI Implementation
• Transactional systems and analytical systems have conflicting purposes
when it comes to database speed and performance. For this reason, it is
difficult to design a single system which will serve both purposes. This
is why data warehouses generally contain archived data. Archived data
are data that have been copied out of a transactional database.
• Denormalization typically takes place at the time data are copied out of
the transactional system. It is important to keep in mind that if a copy of
the data is made in the data warehouse, the data may become out-ofsynch . This happens when a copy is made in the data warehouse and
______
then later, a change to the original record is made in the source database.
• Data mining activities performed on out-of-synch records may be
useless, or worse, misleading.
• An alternative archiving method would be to move the data out of the
transactional system. This ensures that data won’t get out-of-synch,
however, it also makes the data unavailable should a user of the
transactional system need to view or update it.
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• Implementing and deploying a BI initiative is a
lengthy, expensive, and risky endeavor!
• Success of a BI system is measured by its
widespread usage for better decision making
• The typical BI user community includes


Not just the top executives (as was for EIS)
All levels of the management hierarchy
 Provide what is needed to whom he/she needs it
• A successful BI system must be of benefit to the
enterprise as a whole…
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BI for Business Strategy
BI - Alignment with Business Strategy
• Strategy should be aligned with BI/DW – has the
capability to execute the initiative by establishing a
BI Competency Center (BICC) which can:
• To be successful, BI must be aligned with the
company’s business strategy (think about IS/IT
Triangle Strategy Model).


BI cannot/should not be a technical exercise for the
information systems department

• BI changes the way a company conducts business
by



improving business processes, and
transforming decision making to a more
data/fact/information driven activity


• BI should help execute the business strategy and
not be an impediment for it!
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
65
Demonstrate linkage – BI to strategy.
Encourage interaction between the potential business users
and the IS organization.
Both sides have a lot to learn from each other
Serve as a repository and disseminator of best BI practices
among the different lines of business.
Advocate and encourage standards of excellence.
Help stakeholders understand the crucial role of BI.
Facilitate a real-time, on-demand agile environment. (see
next slide)
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Real-Time, On-Demand BI Is Attainable
Issues for Successful BI
• The demand for “real-time” BI is growing!
• Is “real-time” BI attainable? (Continental Airlines
case to be discussed in chapter 2)
• Technology is getting there…
• Developing vs. Acquiring BI systems
• Justifying via cost-benefit analysis


It is easier to quantify costs
Harder to quantify benefits

• Security and Protection of Privacy
• Integration of Systems and Applications



Automated, faster data collection (RFID, sensors,… )
Database and other software technologies (agent, SOA,
…) technology is advancing
Telecommunication infrastructure is improving
Computational power is increasing while the cost for
these technologies is decreasing
• Trend -> Business Activity Management (BAM)
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1.7 Analytics Overview
BI Implementation Considerations
• Analytics?
• Developing or acquiring BI systems


BI shell?
 In-house versus outside consultants

Something new or just a new name for …
“The process of developing actionable decisions or
recommendations for actions based upon insights generated
from historical data.”
• A Simple Taxonomy of Analytics
• Justification and cost-benefit analysis
• Security and protection of privacy
• Integration of systems and applications

Descriptive
___________/Reporting
Analytics

Predictive Analytics
__________

PrescriptiveAnalytics
__________
 Knowing what is happening in the organization and understanding
some underlying trends and causes of such occurrences.
 Aims to determine what is likely to happen in the future.
 The goal is to recognize what is going on as well as the likely
forecast and make decisions to achieve the best performance possible.
• Analytics or Data Science?

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Business-oriented vs. Science/technical-oriented
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Analytics Overview
[2]
Business Analytics
[1]
Descriptive/
[3]
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Fig. 1.5: Three Types of Analytics
Outcomes Enablers Questions
Descriptive
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Predictive
Prescriptive
What happened?
What is happening?
What will happen?
Why will it happen?
What should I do?
Why should I do it?
•
•
•
•
•
•
•
•
•
•
•
Business reporting
Dashboards
Scorecards
Data warehousing
Well defined
business problems
and opportunities
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Data mining
Text mining
Web/media mining
Forecasting
Accurate projections
of the future states
and conditions
Optimization
Simulation
Decision modeling
• Expert systems
Best possible
business decisions
and transactions
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Introduction to Big Data Analytics
End-of-Chapter Application Case
• Big Data?





Nationwide Insurance Used BI to
Enhance Customer Service
Not just big!
Volume
Variety
Velocity
structured, unstructured, or in a stream
Questions for Discussion
1. Why did Nationwide need an enterprise-wide data
warehouse?
2. How did integrated data drive the business value?
3. What forms of analytics are employed at Nationwide?
4. With integrated data available in an enterprise data
warehouse, what other applications could Nationwide
potentially develop?
• Two aspects for studying “Big Data”

storing and __________
processing /analyzing “Big Data”
_______
computation to the data instead of pushing
• Push ___________
data to a computing mode.
• More on big data and related analytics tools and
techniques are covered in Chapter 6.
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• 1. Why did Nationwide need an enterprise-wide
data warehouse?
• With more than 100 business units offering a
variety of products, Nationwide experienced
duplication of effort in gathering data, analyzing it,
and generating reports. Data-processing
environments were widely dissimilar, and there was
extreme data redundancy, resulting in higher
expenses.
• Mergers and acquisitions only added to the
difficulty and cost. A single, authoritative data
warehouse would apply best practices and provide
clean, consistent, and complete data.
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• 2. How did integrated data drive the business
value?
• Integrated data about customers improved marketing
campaigns and better targeted communications, which
improved customer satisfaction and retention, as well as
contributing to a gain in sales.
• Integrated financial data made financial reporting faster
and more efficient and added tools for better risk
assessment and decision support.
• Integrated data following mergers fostered smoother
integration of businesses. Integrated data for reporting
gave agents easy access to reports within seconds rather
than days, significantly improving productivity.
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• 3. What forms of analytics are employed at
Nationwide?
• It uses the three basic types of business analytics.
• The company’s data warehouse supports
descriptive analytics for all functions. For
example, the data describes customer behavior,
financial performance, and policy information.
• It uses predictive analytics in the Customer
Knowledge Store to identify the kinds of customer
interaction that are important for customers at
different points in their lives.
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• 3. (cont.)
• At the level of prescriptive analytics, the Financial
Performance Management system applies
financial data to a decision support system.
• You may identify additional examples of these
three categories. Optionally, you may also refer to
analytics applied to different domains, such as
marketing analytics, financial analytics, and even
insurance analytics.
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13
From Data to Knowledge:
How Can Organization Gain Competitive Advantage?
(Survive and Prosper in the Digital Economy)
• 4. With integrated data available in an enterprise
data warehouse, what other applications could
Nationwide potentially develop?
• The case described customer relationships and
financial reporting.
• Other areas of decision making for an insurance
business would include the development and
pricing of products, regulatory compliance, hiring,
risk management, and the location of facilities.
Data
process
Information
Available
-As a product
NOT byproduct
Decision
Making
Accessible
context,
experience
D. B.
Reusable
D.B.:
Structured: R-DBMS
Unstructured: Document Mgt. Systems
automate
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informate
Useable
Sharable
Collaborative
Organizational
Knowledge
K.B
D.W
Dr. Chen, Business Intelligence
Quality
Information
innovate
CRM
Accounting
Finance
Operations
Manufacturing
-As core intellectual capital
NOT merely a few smart employers
External
customers
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Plan of the Book
• Introduction

Chapter 1
• Data Foundations

Chapter 2
• BI & Analytics

Chapters 3-6
• Emerging Trends

Chapter 7
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