Transcript Chapter 1 - Zhangxi Lin

ISQS 3358, Business Intelligence
Anatomy of Business Intelligence
Zhangxi Lin
Texas Tech University
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Learning Objectives
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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 and relate them to DSS
Understand the major issues in implementing business
intelligence
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Case: Toyota Motor Sales USA
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Challenge: how to reduce vehicle transit cost
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Problem:
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Inability to deliver cars to dealers timely
Computers generated tons of directionless reports and data with little help
Unable to make timely decisions
Solution: Data warehouse
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Average: $8/day, $72-80/car, 9-10days/transit
Total $144-160 million/year
Use right technologies provided by a right vendor following correct concepts
– Oracle’s data warehouse + Hyperion’s BI platform
Lesson learned: data cleansing is important
Results
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Discovered that the company was billed twice in some occasions
Increase the volume of cars by 40% between 2001-2005
In-transit time was reduced 5%
Market share increased
According to IDC Inc. the return on the BI investment was 506%
Changing Business Environments
and Computerized Decision Support
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The Business Pressures-Responses-Support Model
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The business environment
Organizational responses: be reactive, anticipative,
adaptive, and proactive
Computerized support
 Closing the Strategy Gap: One of the major objectives
of BI 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 for achieving them
Changing Business Environments
and Computerized Decision Support
A Framework for
Business Intelligence (BI)
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Business intelligence (BI)
A conceptual framework for decision support.
It combines architecture, databases (or data
warehouse), analytical tools and applications
A Framework for
Business Intelligence
A Framework for
Business Intelligence (BI)
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The Origins and Drivers of Business
Intelligence
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Organizations are being compelled to capture,
understand, and harness their data to support
decision making in order to improve business
operations
Managers need the right information at the right
time and in the right place
A Framework for
Business Intelligence (BI)
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BI’s Architecture and Components
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Data Warehouse
Business Analytics
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Automated decision systems
Performance and Strategy
A Framework for
Business Intelligence (BI)
A Framework for
Business Intelligence (BI)
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BI’s Architecture and Components
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Data Mining
A class of information analysis based on
databases that looks for hidden patterns in a
collection of data which can be used to predict
future behavior
A Framework for
Business Intelligence (BI)
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BI’s Architecture and Components
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business (or corporate) performance
management (BPM)
A component of BI based on the balanced
scorecard methodology, which is a framework for
defining, implementing, and managing an
enterprise’s business strategy by linking
objectives with factual measures
A Framework for
Business Intelligence (BI)
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BI’s Architecture and Components
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User Interface: Dashboards and Other
Information Broadcasting Tools
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Dashboards
A visual presentation of critical data for executives to
view. It allows executives to see hot spots in seconds
and explore the situation
A Framework for
Business Intelligence (BI)
The
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Benefits of BI
Time savings
Single version of truth
Improved strategies and
plans
Improved tactical
decisions
More efficient processes
Cost savings
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Faster, more accurate
reporting
Improved decision making
Improved customer service
Increased revenue
A Framework for
Business Intelligence (BI)
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The Business Value of BI
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How BI Can Help
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Assess their readiness for meeting the challenges posed by
these new business realities
Take a holistic approach to BI functionality
Leverage best practices and anticipate hidden costs
Key Issues and Framework for BI Analysis
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How can enterprises maximize their BI investments?
What BI functionality do enterprises need, and what are they
using today?
What are some of the hidden costs associated with BI
initiatives?
Main BI Topics
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Data warehousing – Making historical data available for analytics
Data preparation – Extraction, transformation and loading
Query - a collection of specifications that enables you to focus on
a particular set of data.
Online Analytical Processing (OLAP) - a capability of information
systems that supports interactive examination of large amounts
of data from many perspectives.
Reporting - generates aggregated views of data to keep the
management informed about the state of their business.
Data mining - extraction of knowledge by utilizing software that
can isolate and identify previously unknown patterns or trends in
large amounts of data.
ISQS 3358 Business Intelligence
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Intelligence Creation and Use,
and BI Governance
Business Intelligence
BI Applications:
- Data warehousing
-Data mining
- BPM
- OLAP
- etc.
Data
Business
Analytics
Executives
Managers
Operators
BI Users
Data
Business
Environment
Decisions
Intelligence Creation and Use
and BI Governance
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BI Governance
The project prioritization process within
organizations
Intelligence Creation and Use
and BI Governance
A typical set of issues for the BI governance
team is to address
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Creating categories of projects (investment, business
opportunity, strategic, mandatory, etc.)
Defining criteria for project selection
Determining and setting a framework for managing
project risk
Managing and leveraging project interdependencies
Continually monitoring and adjusting the composition of
the portfolio
Intelligence Creation and Use
and BI Governance
Intelligence Gathering
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How modern companies ethically and legally organize
themselves to glean as much information as they can
from their:
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Customers
Business environment
Stakeholders
Business processes
Competitors
Other sources of potentially valuable information
Intelligence Creation and Use
and BI Governance
Intelligence Gathering
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In order to be useful in decision making and improving the
bottom line, the data must be:
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Cataloged
Tagged
Analyzed
Sorted
Filtered
Case: AOL search data scandal (2006)
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AOL
 On August 4, 2006, AOL Research released a compressed text
file on one of its websites containing twenty million search
keywords for over 650,000 users over a 3-month period, intended
for research purposes, which was posted only three days before
pulled down.
 While none of the records on the file are personally identifiable,
the New York Times was able to locate an individual from the
released and anonymized search records by cross referencing
them with phonebooks or other public records.
Questions:
 Is it ethically fine to collect data about the rivals?
 How to protect the confident data from the espionage of
competing counterparts?
BI Product Providers
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Microsoft
SAS
IBM
Oracle
SyBase
Business Objects
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BI Tools Survey
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ISQS 3358 Business Intelligence
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List of BI tools
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No.
Tool
Version
Vendor
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Oracle Enterprise BI Server
7.8
Oracle
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Business Objects Enterprise
XI r2
Business Objects (now
SAP)
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SAP NetWeaver BI
7.0
SAP
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SAS Enterprise BI Server
9.1.3
SAS Institute
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TM/1 & Executive Viewer
9.1
Applix (now IBM)
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BizzScore Suite
WebFocus
7.2
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EFM Software
Information Builders
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Excel, Performance Point,
Analysis Server
2007/2005
Microsoft
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QlikView
Microstrategy
Hyperion System
Actuate
Cognos Series 8
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9
9.1
8.3
QlikTech
Microstrategy
Hyperion (now Oracle)
Actuate
Cognos (now IBM)
ISQS 3358 Business Intelligence
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Microsoft SQL Server
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SQL Server is a client-server based, relational database engine. That
puts it head-to-head with the likes of IBM’s DB2 and Oracle’s Oracle…
or so Microsoft dearly wants us to believe.
The problem is that, while DB2 and Oracle are unquestionably
enterprise-level products, SQL Server has for years been dogged by
the suspicion that it can’t really cut the mustard.
SQL Server Products
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SQL Server 2005 Editions
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Microsoft SQL Server 2000
Microsoft SQL Server 2005
Microsoft SQL Server 2008
SQL Server Express
SQL Server Workgroup
SQL Server Developer
SQL Server Standard
SQL Server Enterprise
SQL Server Compact
ISQS 3358 Business Intelligence
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The Major Theories and
Characteristics of Business Intelligence
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Some Theories of BI
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A factory and warehouse
The information factory
Data warehousing and business intelligence
Teradata advanced analytics methodology
Oracle BI system
The Major Theories and
Characteristics of Business Intelligence
The Corporate
Information
Factory
The Major Theories and
Characteristics of Business Intelligence
Teredata
Advanced
Analytics
Methodology
The Major Theories and
Characteristics of Business Intelligence
Toward Competitive
Intelligence and Advantage
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Competitive Intelligence (CI)
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CI implies tracking what competitors are doing by gathering
material on their recent and in-process activities
Competitive strategy in an industry
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low-cost leader
market niche
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Sustaining competitive advantage through building brand
and customer loyalty using BI applications
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Case: MSI’s Netbook (http://en.wikipedia.org/wiki/Netbook)
Toward Competitive
Intelligence and Advantage
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The Strategic Imperative of BI
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Barriers to entry of a new competitor are being significantly
diminished
Because of the Web revolution and increasing
globalization, companies throughout the world are
challenging major players in industries
The ability to deliver goods worldwide is making it easier for
potential competitors to get products and services to more
customers almost anywhere
Companies are finding better or less expensive suppliers
all over the globe
The Different Users of Business
Intelligence
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There are many different users who can benefit from
business intelligence
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Executives – Those who focus on the overall
business
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Business Decision Makers – Usually focused on
single areas of the business (finance, HR,
manufacturing, and so forth)
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Information Workers – Typically managers or staff
working in the back office
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Line Workers – Employees who might use BI without
knowing it
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Analysts – Employees who will perform extensive
data analysis
Business Scorecards
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The Purpose of a Scorecard
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A scorecard should give an executive a visual
representation of the health of an organization
in a single glance
The scorecard is of sufficiently high level to
represent major business operations and their
goals
The data in a scorecard should be as recent as
possible to make them more actionable
Benefits to the Executive
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In a single glance, the executive can see a wide
swath of the business (finance, manufacturing,
sales, marketing, and more)
Immediate value is gained without the need for
the executive to perform analysis
Executives see not just actual values, but
comparisons to plans or prior results
The Contents of a Scorecard
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Scorecards usually contain some or all of the
following elements:
 Key Performance Indicators (KPIs)
 KPI actual values compared to historical values
(for trend analysis)
 KPI actual values compared to a forecast or
budget amount
 Rankings of different departments, locations,
products, and so forth
Dashboards
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The Purpose of a Dashboard
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A dashboard is designed to allow decision
makers to see a variety of data that affects their
divisions or departments
This data may be in the form of scorecards,
charts, tables, and so forth
The dashboard is generally customized for
each user
More targeted and detailed than a scorecard
Benefits to Decision Makers
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Decision makers see a variety of information
targeted to their department
 This allows decision makers to focus only on
the items over which they have control
Information is more detailed than that of a
scorecard
The tools in the dashboard often have better
analytic capabilities than a scorecard
The Contents of a Dashboard
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A Dashboard generally contains a variety of
different views of data
The data is generally KPIs and shows trends,
breakdowns, and comparisons against a
forecast or historical data
The dashboard often consists of charts and
tables, and may include scorecard elements as
well
Reports
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The Purpose of Reports
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Reports allow a much broader audience to benefit
from the data in a BI solution
Reports may be static, requiring no training
 Reports may also allow a limited amount of
interactivity
Reports can be presented in a variety of formats,
allowing for easier distribution
The Purpose of Custom Application
Integration
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An application used by line workers may include
business intelligence without the worker
realizing what is happening
 A sales clerk may get a list of targeted
recommendations to make based on what the
customer is buying
 A loan officer may be presented with the level
of risk associated with granting a loan to a
particular customer
The Contents of Custom Application
Integration
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Custom applications may include predictive
output from data mining models
Custom applications can show history and
trends for the current customer, supplier, and so
forth
Custom applications may allow easy ways for
users to explore the data for relationships
Analytic Applications
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The Purpose of Analytic Applications
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Analytic applications free analysts from building
complex models and writing complex queries
Analysts are free to focus on the data and
discover relationships and drivers behind
numbers
Rich visualizations allow much easier
understanding of trends and relationships
The Contents of Analytic Applications
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Analytic applications typically have no limits;
analysts can see everything
Analytic applications can view and analyze all of
an organization’s data in a number of ways
Analytic applications are powerful, but not as
easy to use as other mechanisms
OLTP vs. OLAP
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Online transaction processing systems (OLTP)
Systems that handle a company’s routine ongoing
business
Online analytic processing (OLAP)
An information system that enables the user, while at a
PC, to query the system, conduct an analysis, and so on.
The result is generated in seconds
ISQS 3358 Business Intelligence
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Successful
Business Intelligence Implementation
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Appropriate Planning and Alignment with the Business
Strategy
Establish a BI Competency Center (BICC) within the
Company
Real-time, On-Demand BI Is Attainable
Developing or Acquiring BI Systems
Justification and Cost/Benefit Analysis
Security and Protection of Privacy
Integration of Systems and Applications
Conclusion:
Business Intelligence Today and Tomorrow
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Today’s organizations are deriving more value from BI
by extending actionable information to many types of
employees, maximizing the use of existing data assets
Visualization tools including dashboards are used by
producers, retailers, governments, and special agencies
More and more industry-specific analytical tools will flood
the market to perform almost any kind of analysis and to
facilitate informed decision making from the top level to
the user level
A potential trend involving BI is its possible merger with
artificial intelligence (AI)
Application Cases in the Book
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Case 1.1 – Intelligence Price Setting Using
Automated Decision Support
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Case 1.2 - Predictive Analytics Helps Texas Collect
Taxes
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http://www.longs.com
Using Price-optimization programs by SAS
Using data mining software from SPSS
Case 1.3 - France Telecom Business Intelligence
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“Business Intelligence Competence Center”
http://www.intelligentsolutions.com
http://www.dmreview.com