Business Intelligence
An Introduction to
Business Intelligence
http://www1.chihlee.edu.tw/teachers/chienhua/
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What is Business Intelligence?
A Brief History of Business Intelligence
The Architecture of Business Intelligence
Major BI Tools and Techniques
The Benefits of Business Intelligence
Major BI Vendors
Issues for Successful BI
Central Themes of the Lecture
Demands from processing explosive
information
ERP/CRM/SCM
Internet
Gartner Says Business Intelligence
Software Market to Reach $17.1
Billion in 2016
Gartner Says Worldwide
Business Intelligence Software Revenue to
Grow 7 Percent in 2013
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Gartner: BI is #1 Priority for CIOs
Top 10 CIO Technology Priorities in 2015
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Explosion of Digitally Born Data
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Data Scale
"Big data" has increased the demand of information
management specialists - major companies have spent
more than $15 billion for this.
This industry is worth more than $100 billion and growing
at almost 10% a year.
4.6 billion mobile-phone subscriptions worldwide and
between 1 billion and 2 billion people accessing the
internet.
The world's effective capacity to exchange information
through telecommunication networks was 281 petabytes in 1986,
471 petabytes in 1993, 2.2 exabytes in 2000, 65 exabytes in 2007
It is predicted that the amount of traffic flowing over the internet
will reach 667 exabytes annually by 2013.
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Understand today’s turbulent business
environment and describe how organizations
survive and even excel in such an environment
(i.e., solving problems and exploiting
opportunities)
Understand the need for computerized support of
managerial decision making in implementing
business analytics
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Business Philosophy
Changing Business Environment &
Computerized Decision Support
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
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Business Pressures–Responses–
Support Model
Business Pressures–Responses–
Support Model
Increasing potential
to support
business decisions
End User
Business
Analyst
Data
Analyst
DBA
Decision
Making
Data
Presentation
Visualization Techniques
Data
Mining
Information Discovery
Data
Exploration
Statistical Summary, Querying, and Reporting
Data
Preprocessing/Integration,
Data
Warehouses
Data
Sources
What is Intelligence in Business?
What is the current status of the
business?
What’s going well?
What needs improvement?
What are the business’ strengths and
weaknesses?
Are there opportunities for innovation
or competitive advantage?
How do we improve our decision
making?
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BI refers to skills, technologies, applications and
practices used to help a business acquire a better
understanding of its commercial context.
Meaning of an evolution of decision support concepts over
time
BI's major objective is to enable easy access to data
(and models) to provide business managers with the
ability to conduct analysis
BI helps
transform
data, to information (and
knowledge), to decisions and finally to action
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Business Intelligence (BI)
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BI Answers Business Questions
Which Of My Customers Are Most Profitable?
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BI Answers Business Questions
Or,
Who Are
My
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BI Answers Business Questions
Which Products Cost The Most To Maintain?
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BI Answers Business Questions
Where
Can
We
Cut
Costs?
Half Of Our Marketing
Efforts Earn Us A Fortune
Could Someone Please Tell Us Which
Half That Is?
Business Intelligence Recipe
Start with your legacy data
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Turn That Data Into Intelligence
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Get The Information In Front Of
The Right Group
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Think Through Some New Strategies
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Watch For Results
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Adjust And Repeat As Needed
Turns:
Data Into Information
Information Into Knowledge
Knowledge Into Decisions
Decisions Into Profits
Business Intelligence Done Right
What is Business Intelligence?
A Brief History of Business Intelligence
The Architecture of Business Intelligence
Major BI Tools and Techniques
The Benefits of Business Intelligence
Major BI Vendors
Issues for Successful 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”
2005+ — Inclusion of AI and Data/Text Mining
capabilities; Web-based Portals/Dashboards
2011s — Yet to be seen
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A Brief History of BI
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Evolution of Business Intelligence
1
st
Generation – Traditional analytics (query and
reporting)
2
nd
Generation – Traditional generation (OLAP,
data warehousing)
2.5
nd
Generation – New traditional generation
3
rd
Generation - Advanced analytics
Rules, predictive analytics and real-time data mining
Stream analytics
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Business Intelligence Use
Cases
Traditional Analytics
1stGeneration Analytics (Query & Reporting)
2ndGeneration Analytics (OLAP, Data Warehousing)
Advanced Analytics/Optimization
Rules Predictive Analytics Real-time and traditional Data Mining
Stream Analytics*
Real-time, continuous, sequential analysis (ranging from basic to advanced analytics)
* In lieu of stream analytics, “embedded analytics,”although architecturally different, could potentially play the same role
“
New Traditional
”
Analytics
“2.5-Gen”Analytics (In-Memory OLAP, Search-Based)
Example Target Solutions: Fraud Detection / Risk CRM Analytic Supply Chain Optimization RFID / Spatial Data Other High-Volume Focus on what is
happening RIGHT NOW
Real-Time Threshold
Focus on what will happen Analytic applications that apply statistical relationships in the form of RULES
Focus on what did happen Turning data into information is limited by the relationships which the end-user already knows to look for.
Data mining to determine why something happenedby unearthing relationships that the end-user may not have known existed.
Source: Bill O’Connell IBM, Aug 2007
Evolution of Business Intelligence
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Evolution of Business Intelligence
Running Canned Reports Directly Against Operational DB Running Reports Against Nightly Copy of Operational DB (Reporting Server) Running Reports Against Real-time Copy of Operational DB (ODS) Composing and Running Ad hoc Reports Against Dimensionally Integrated Data (Relational Data Warehouse)
Free Form Analysis Using Dimensionally Integrated and Pre-Aggregated Data (OLAP Data Mart)
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From Chaos to Structure
Coupling
Cohesion
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Data Silos
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Business Intelligence Applications
RetailFinancial Services
Communications
Other Major Companies
• Leading Internet, Travel and Transportation Companies • 7 of the Top 10 Global Retailers • 3 of Top 5 Global Food and Drug Stores
Manufacturing
• 7 of Top 10 Global Manufacturing Companies
• 8 of Top 10 Global Telco Companies
Pharmaceuticals
• 9 of Top 10 Global Pharmaceutical Companies • 8 of the Top 10 Healthcare Companies • 7 of Top 10 Global Commercial Banks • 4 of Top 5 Diversified FSI • 4 of Top 5 Global Insurers
Governments
• Covering Federal, State, and Local Government Entities
Consumer Packaged Goods
• 5 of Top 7 Global Consumer Packaged Goods Companies
Customer Analytics
Customer profiling
Targeted marketing
Personalization
Collaborative filtering
Customer satisfaction
Customer lifetime value
Customer loyalty
Sales Channel Analytics
Marketing
Sales performance and pipeline
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Business Intelligence Applications
Supply Chain Analytics
Supplier and vendor management
Shipping
Inventory control
Distribution analysis
Behavior Analysis
Purchasing trends
Web activity
Fraud and abuse detection
Customer attrition
Social network analysis
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Business Intelligence Applications
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What is Business Intelligence?
A Brief History of Business Intelligence
The Architecture of Business Intelligence
Major BI Tools and Techniques
The Benefits of Business Intelligence
Major BI Vendors
Issues for Successful BI
A BI system has four major components:
a data warehouse, with its source data
business analytics, a collection of tools for
manipulating, mining, and analyzing the data
in the data warehouse;
business performance management (BPM) for
monitoring and analyzing performance
a user interface (e.g., dashboard)
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The Architecture of BI
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A High-Level Architecture of BI
The data warehouse is the cornerstone 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.
Business analytics are the tools that help users
transform data into knowledge
(e.g., queries,
data/text mining tools, etc.).
Components in a BI Architecture
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.
User Interface (i.e., dashboards) provides a
comprehensive graphical/pictorial view of
corporate performance measures, trends, and
exceptions.
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The BI Platform is the Key Component
of a Business Intelligence System
Business Intelligence Platform
Reporting boardsDash- AnalysisOLAP Advanced Analysis Alerting
Custom BI Applications
Operations Analysis
• Productivity Reporting • HR Reporting • Web Commerce Analysis
Supply Chain Management
• Inventory Analysis • Fulfillment Analysis • Distribution Cost Analysis
Financial Reporting Analysis
• P&L Reporting • Profitability Analysis • Financial Compliance Analysis
Customer Analysis • Customer Segmentation • Customer Profitability • Cross-sell / Up-sell Risk Analysis • Risk Management • Portfolio Risk Analysis • Fraud Detection
Sales Analysis
• Store / Geographic Analysis • Sales Pipeline Reporting • Sales Perf. / Quota Reporting
Vendor Performance Analysis
• Service Level Agreement • Chargeback Analysis • Relative Sales Analysis
Product Management
• Product Performance Analysis • Market Basket Analysis • Category Management
Data Warehouses and
Operational Systems
ERP Systems CRM Systems Web Systems Data Warehouse Data MartsBI Applications
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A High-Level Architecture of BI
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A Taxonomy for Data Mining Tasks
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What is Business Intelligence?
A Brief History of Business Intelligence
The Architecture of Business Intelligence
Major BI Tools and Techniques
The Benefits of Business Intelligence
Major BI Vendors
Issues for Successful BI
Tool categories
Data management
Reporting, status tracking
Visualization
Strategy and performance management
Business analytics
Social networking & Web 2.0
New/advanced tools/techniques to handle
massive data sets for knowledge discovery
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Major BI Tools and Techniques
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Some Sample Reports
Data Visualization Example
Product
Region
West
East
South
North
2011 2012 2013 2014
Milk
Donut
Sandwich
Soda
Beer
North
South
East
West
Time
The Sales$
by Soda by
West in Yr
of 2001
Sales Analysis
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Social Network Analysis
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Dynamic Dashboards
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Web Mining Success Stories
Amazon.com, Ask.com, Scholastic.com, …
Website Optimization Ecosystem
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What is Business Intelligence?
A Brief History of Business Intelligence
The Architecture of Business Intelligence
Major BI Tools and Techniques
The Benefits of Business Intelligence
Major BI Vendors
Issues for Successful BI
Business oriented social networks can go beyond
“advertising and sales”
Emerging enterprise social networking apps:
Finding and Recruiting Workers
Management Activities and Support
Training
Knowledge Management and Expert Location
• e.g., innocentive.com; awareness.com; Caterpillar
Enhancing Collaboration
Using Blogs and Wikis Within the Enterprise
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Implications of Business and
Enterprise Social Networks
Survey shows that best-in-class companies use
blogs and wikis for the following applications:
Project collaboration and communication (63%)
Process and procedure document (63%)
FAQs (61%)
E-learning and training (46%)
Forums for new ideas (41%)
Corporate-specific dynamic glossary and terminology
(38%)
Collaboration with customers (24%)
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Implications of Business and
Enterprise Social Networks
The ability to provide accurate information when
needed, including a real-time view of the
corporate performance and its parts
A survey by Thompson (2008)
Faster, more accurate reporting (81%)
Improved decision making (78%)
Improved customer service (56%)
Increased revenue (49%)
The following are examples of highlighting
companies that have successfully used BI
applications, and the business value they bring.
The Benefits of BI
Improving Sales through
Improved Customer
Service and Employee
Satisfaction
Key BI Characteristics:
Business Use:
Business Benefits:
INDUSTRY: RetailBUSINESS USERS: 10,000 and growing
OPERATING ENV.: Linux
DATABASE: Netezza (8+ TB); Oracle 10g (10+TB)
CUSTOMER SINCE: 2005
APPLICATIONS: Customer Retention Customer Extranet Market Basket Analysis Sales Analysis Revenue Forecasting Customer Profitability Analysis
• Using BI, Corporate Express has seen that the average order size doubles when the appropriate, complementary product is offered to a customer. • In June 2007, Corporate Express received the 2007 Best Practices Award
for Predictive Analytics from The Data Warehousing Institute • MicroStrategy used to monitor and analyze business performance at the
corporate and divisional levels
• Corporate Express customers view purchase history and backlog using at-a-glance dashboards and standard reports
Enhancing Profitability
and Expanding the
Business Through
Optimized Inventory and
Sales Analysis
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Key BI Characteristics:
Business Use:
Business Benefits:
INDUSTRY: RetailBUSINESS USERS: 2,000+
BI COMPONENTS: 33,500 Reports; 19,600 Business Metrics
OPERATING ENV.: Windows 2000/2003
DATABASE: Oracle 9i; 6+ TB
CUSTOMER SINCE: 2002
APPLICATIONS: Merchandise Analysis Transportation Management Warehouse Management
• Upper management has easy, constant access to key sales metrics, leading to faster, more informed decisions
• More efficient inventory control and management
• Substantial business growth attributed to better decision making and insight • PetSmart uses MicroStrategy to manage daily operations at each of its
stores across the United States.
• Every day, PetSmart executives, regional managers, marketers, and inventory managers use MicroStrategy dashboards to gauge the profitability of products and services and better manage inventory.
• PetSmart has reduced stock-outs, enhanced oversight of store performance, and increased revenue from PetSmart’s services business.
Applying BI to Many
Aspects of the
Business to Improve
Profitability, Sales
Performance, and
Customer Experience
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Key BI Characteristics:
Business Use:
Business Benefits:
INDUSTRY: RetailBUSINESS USERS: 10,000 and growing
OPERATING ENV.: Linux
DATABASE: Netezza (8+ TB); Oracle 10g (10+TB)
CUSTOMER SINCE: 2005
APPLICATIONS: Customer Retention Customer Extranet Market Basket Analysis Sales Analysis Revenue Forecasting Customer Profitability Analysis
• Using BI, Corporate Express has seen that the average order size doubles when the appropriate, complementary product is offered to a customer. • In June 2007, Corporate Express received the 2007 Best Practices Award
for Predictive Analytics from The Data Warehousing Institute • MicroStrategy used to monitor and analyze business performance at the
corporate and divisional levels
• Corporate Express customers view purchase history and backlog using at-a-glance dashboards and standard reports
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Analyzing Brand Costs
and Sales Trends to
Optimize Retail
Purchasing and Enhance
Revenue
Key BI Characteristics:
Business Use:
Business Benefits:
INDUSTRY: Retail BUSINESS USERS: 425+BI COMPONENTS: 500 Reports/month; 1,120 Total Metrics
OPERATING ENV.: Windows 2000
DATABASE: Oracle 9; 11+ TB
CUSTOMER SINCE: 2001
APPLICATIONS: Retail Cost Analysis & Inventory Planning Store Performance Analysis Asset Protection & Loss Prevention
• Foot Locker is improving merchandise purchasing and inventory management by analyzing costs, sales forecasts, trends, and performance across each of its brands
• Easy access to reliable data is enabling Foot Locker to detect issues earlier and make informed business decisions every day.
• Planners, Merchandise Managers, and Buyers analyze Cost of Goods Sold (COGS) and Gross Margin to optimize merchandise purchasing, inventory allocation, and distribution
• Track and monitor retail sales at the store and product SKU levels, across all brands
• Analyze asset protection and loss prevention across the entire enterprise
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What is Business Intelligence?
A Brief History of Business Intelligence
The Architecture of Business Intelligence
Major BI Tools and Techniques
The Benefits of Business Intelligence
Major BI Vendors
Issues for Successful BI
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In recent years, the landscape of BI vendors has
changed
Cognos acquired by IBM in 2008
• IBM also acquired SPSS in 2009
Hyperion acquired by Oracle in 2008
Business Objects acquired by SAP in 2009
Microstrategy
May be the only independent large BI vendor
Others include Microsoft, SAS, Teradata (mostly
considered a DW vendor)
Major BI Vendors
http://www.youtube.com/watch?v=MAbtc_PZOjs
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Gartner Magic Quadrant Customer Survey: Survey
of BI Customers in Support of the Gartner Magic
Quadrant Analysis for BI Platforms
BI Survey 7: BI Technology Rankings According
to the BI Survey 7 – The Largest Independent
Survey of BI, Involving Over 1,900 Companies
BI Product Survey: Evaluation and Survey
Conducted by Passioned International, a Leading
BI Analyst Firm in the Netherlands
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Gartner BI Platform Capability Evaluation:
Comprehensive, Point-by-point Evaluation of all
Major BI Products
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The BI Scorecard: Comprehensive Hands-on
Evaluation of BI Products by Cindi Howson,
Author, Industry Analyst, and President of ASK
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What is Business Intelligence?
A Brief History of Business Intelligence
The Architecture of Business Intelligence
Major BI Tools and Techniques
The Benefits of Business Intelligence
Major BI Vendors
Issues for Successful BI
Central Themes of the Lecture
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Issues for Successful BI
Developing vs. Acquiring BI systems
Developing everything from scratch
Buying/leasing a complete system
Using a shell BI system and customizing it
Use of outside consultants?
Justifying via cost-benefit analysis
It is easier to quantify costs
Harder to quantify benefits
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Issues for Successful BI
Security and Privacy
Still an important research topic in BI
How much security/privacy?
Integration of Systems and Applications
BI must integrate into the existing IS
• Often sits on top of ERP, SCM, CRM systems
Integration to outside (partners of the extended
enterprise) via the Internet –
• Customers, vendors, government agencies, etc.
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Business Intelligence Trends
1. Agile Information Management (IM)
2. Cloud Business Intelligence (BI)
3. Mobile Business Intelligence (BI)
4. Analytics
5. Big Data
Business Intelligence Trends
Business Intelligence 2.0 (BI 2.0)
Web Intelligence
Web Analytics
Web 2.0
Social Networking and Microblogging sites
Data Trends
Big Data
Platform Technology Trends
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Summary
BI should help execute the business strategy
and not be an impediment for it!
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.
A successful BI system must be of benefit to
the enterprise as a whole.
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