Business Intelligence
Dr. Mahdi Esmaeili
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‫تعاریف متفاوت از هوش تجاری‬
‫• هوش تجاری مدیریت درست و موثر اطالعات برای‬
‫ً به ارتباط بین کاربر‬
‫هدفی تجاری است و اساسا‬
‫و سیستمهای فناوری اطالعات مربوط میگردد‬
‫• هوش تجاری عبارت است از شرح نیازهای سازمان‬
‫برای تجزیه و تحلیل به همراه گزارشدهی‬
‫• هوش تجاری رویکردی راهبردی است برای هدفگذاری‬
‫به صورت سیستماتیک‪ ،‬ردیابی‪ ،‬مخابره و نهایتا‬
‫ً‬
‫تبدیل و ترجمه سیگنالها و عالئم ضعیف کسبوکار‬
‫به یکسری اطالعات کاربردی که اساس تصمیمگیری‪-‬‬
‫های راهبردی شوند‬
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‫• هوش تجاری به عنوان تغییرشکلدهندهای آگاه و‬
‫روشمند است که دادههای مختلف را از منابع‬
‫مختلف دریافت و به شکلهای جدید تغییر میدهد‬
‫تا اطالعاتی نتیجهگرا و تجاری را فراهم کند‬
‫• هوش تجاری مبحث بسیار وسیع است که کارکردها‬
‫تعاریف متفاوت از هوش تجاری‬
‫معمول عنصر اصلی آن‬
‫ا‬
‫• هوش تجاری که انبار داده‬
‫محسوب میشود برای انجام تجزیه و تحلیلهای‬
‫پیچیده و بهبود عملکرد در جستجوهای پایگاه‬
‫داده – که شامل هزاران رخداد است‪ -‬ایجاد و‬
‫بهینهسازی شده است‪ .‬هوش تجاری در واقع برای‬
‫ایجاد ارزش در سازمانها بر پایه داده و به‬
‫بیان دقیقتر واقعیات میباشد‪.‬‬
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‫• هوش تجاری دسته وسیعی از برنامهها و تکنولوژی‪-‬‬
‫ها را دربر میگیرد که برای جمعآوری‪ ،‬ذخیره‪-‬‬
‫سازی‪ ،‬تجزیه و تحلیل و فراهم کردن دسترسی آسان‬
‫به دادهها به وجود آمده است تا کاربران بنگاه‬
‫را در اتخاذ تصمیمات درست تجاری کمک کند‪.‬‬
‫همچنین شامل مجموعهای از مفاهیم و روشها است‬
‫که تصمیمگیریهای تجاری را با استفاده از سیستم‪-‬‬
‫های کاربردی مبتنی بر حقایق بهبود میبخشد‪.‬‬
‫تعاریف متفاوت از هوش تجاری‬
‫• هوش تجاری ابزاری است که توسط بنگاهها برای‬
‫جمعآوری‪ ،‬مدیریت‪ ،‬تجزیه و تحلیل دادهها و‬
‫اطالعات اساسی و ساختیافته و یا غیر آن‬
‫استفاده میشود و این کار با به کارگیری‬
‫قابلیتهای فناوری اطالعات صورت میپذیرد‪ .‬هوش‬
‫تجاری همچنین از دادههای معتبر جمعآوری شده‬
‫حاصل از فرایندهای عملیاتی روزانه استفاده‬
‫کرده و با تبدیل این دادهها به اطالعات و دانش‬
‫از احتماالت و بیخبریها در بنگاه جلوگیری می‪-‬‬
‫کند‪.‬‬
‫‪4‬‬
‫• هوش تجاری با فرایندی سیستماتیک سروکار دارد‬
‫تا با تجزیه و تحلیل و مدیریت دانش و اطالعات‬
‫درون و برونسازمانی به فرایند تصمیمگیری یک‬
‫سازمان کمک کرده و آن را بهبود بخشد‪.‬‬
‫• هوش تجاری نه یک محصول است و نه یک سیستم‪ .‬در‬
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Transaction Processing System (TPS)
Office Automation Systems (OAS)
Individual Information System (IIS)
Organizational Information Systems (OIS)
Information System (IS)
Management Information System (MIS)
Decision Support System (DSS)
Strategic Information Systems (SIS)
Enterprise Information System (EIS)
Executive Information System (EIS)
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‫ده های مختلف مدیران و اهمیت تصمیم گیری‬
‫تصمیمات‬
‫راهبردی‬
‫مدیرانًاجرایی‬
‫(ارشد)‬
‫تصمیمات‬
‫تاکتیکی‬
‫‪SIS, EIS‬‬
‫مدیرانًوًکارمندانً ‪MIS, DSS‬‬
‫میانیً(یقهًسفیدها)‬
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‫تصمیمات‬
‫اجرایی‬
‫مدیرانًعملیاتیً‬
‫(فعالیتًهایًدفتریًوًتولیدی‬
‫‪OAS, TPS‬‬
BI decision-support applications facilitate many activities
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Multidimensional analysis, for example, online analytical processing (OLAP)
Click-stream analysis
Data mining (Mining for text, content, and voice)
Forecasting
Business analysis
Balanced scorecard preparation
Visualization
Querying, reporting, and charting (including just-in-time and agent-based alerts)
Geospatial analysis
Knowledge management
Enterprise portal implementation
Digital dashboard access
Other cross-functional activities
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Examples of BI decision-support databases
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Enterprise-wide data warehouses
Data marts (functional and departmental)
Exploration warehouses (statistical)
Data mining databases
Web warehouses (for click-stream data)
Operational data stores (ODSs)
Operational marts (oper marts)
Other cross-functional decision-support databases
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Engineering Stages
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Parallel Development Tracks (for Steps 5–14)
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Steps Performed in Parallel Development Tracks
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Core Team Roles and Responsibilities
Role
Major Responsibilities
Application lead developer
Designing and overseeing the development of the access
and analysis application (e.g., reports, queries)
BI infrastructure architect
Establishing and maintaining the BI technical infrastructure
Business Representative
Participating in modeling sessions, providing data
definitions, writing test cases, making business decisions,
resolving disputes between business units, and improving
the data quality under the control of the business unit
represented by this role
Data Administrator
Performing cross-organizational data analysis, creating the
project-specific logical data models, and merging the logical
data models into an enterprise logical data model
Data mining Expert
Choosing and running the data mining tool; must have a
statistical background
Data quality analyst
Assessing source data quality and preparing data-cleansing
specifications for the ETL process
Database administrator
Designing, loading, monitoring, and tuning the BI target
databases
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Core Team Roles and Responsibilities
Role
Major Responsibilities
ETL lead developer
Designing and overseeing the ETL process
Meta data administrator
Building or licensing (buying), enhancing, loading, and
maintaining the meta data repository
Project manager
Defining, planning, coordinating, controlling, and reviewing
all project activities; tracking and reporting progress;
resolving technical and business issues; mentoring the
team; negotiating with vendors, the business
representative, and the business sponsor; has overall
responsibility for the project
Subject matter Expert
Providing business knowledge about data, processes, and
requirements
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Extended Team Roles and Responsibilities
Role
Major Responsibilities
Application developer(s)
Coding the report programs, writing query scripts, and
developing the access and analysis applications
BI support (help desk staff)
Mentoring and training the business staff
Business sponsor
Championing the BI initiative and removing businessrelated roadblocks for the BI project team
ETL developer(s)
Coding the ETL programs and/or preparing the
instructions for the ETL tool
IT auditor or QA analyst
Determining the risks and exposures of the BI project
due to internal lack of controls or external forces
Meta data repository
developer(s)
Coding the meta data repository migration programs to
load the meta data repository database; providing meta
data reports and an online help function
Network services staff
Maintaining the network environment
Operations staff
Running the batch processes for the ETL cycles, the
access and analysis application, and the meta data
repository
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Extended Team Roles and Responsibilities
Role
Security officer
Major Responsibilities
Ensuring that security requirements are defined and
that security features are tested across all tools and
databases
Handling limited responsibilities on the BI project, such
Stakeholders (other
business representatives or as reviewing and ratifying the cross-organizational
standards and business rules the BI project team uses
IT managers)
or develops
Strategic architect
Managing the overall technical infrastructure for the
organization, including the BI technical infrastructure
Technical services staff
Maintaining the hardware infrastructure and the
operating systems
Testers
Testing programming code created by the developers
from the ETL, Application, and Meta Data Repository
tracks
Tool administrators
Installing and maintaining the developer tools and the
access and analysis tools
Web developer(s)
Designing the Web site and creating the Web pages for
displaying reports and queries on the intranet, extranet,
or Internet
Web master
Setting up the Web server and Web security
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Business Justification Components
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Benefit Categories
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Revenue increase
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Identification of new markets and niches
More effective suggestive selling
Faster opportunity recognition
Faster time to market
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Profit increase
• Better targeted promotional mailings
• Early warning of declining markets
• Identification of under-performing product lines
or products
• Identification of internal inefficiencies
• More efficient merchandise management
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Customer satisfaction improvement
• Improved understanding of customer
preferences
• Improved customer-to-product matching
• Up-selling to customers
• Increased repeat business
• Faster resolution of customer complaints
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Savings increase
• Reduction in wasted or out-of-date merchandise
• Reduction in requests for customized reporting
Market share gain
• Increased numbers of customers who defect from the competition
• Much higher customer retention rate as compared with previous
years and with the competition
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Risk Assessment
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The technology used for implementing the project
The complexity of the capabilities and processes to be implemented
The integration of various components and of data
The organization and its financial and moral support
The project team staff's skills, attitudes, and commitment levels
The financial investment in terms of ROI
Green = low risk—go ahead with the project
Yellow = medium risk—caution, proceed slowly
Red = high risk—stop, reevaluate before proceeding
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Basic Risk Assessment Matrix
Level of Risk
Variable
Green (Low)
Yellow (Medium)
Red (High)
Technology
Experienced with
mature technology
Minimal experience
with technology
New technology,
little experience
Complexity
Simple, minimal
workflow impact
Moderate, some
workflow impact
Mission critical, will
require extensive
reengineering
Integration
Stand-alone, no
integration
Limited integration
required
Extensive
integration required
Organization
Solid internal support
Supportive to a large
extent
Little internal
support
Project team
Business experience,
Some business
business-driven,
experience, businesstalented, great attitude driven, talented, fair
attitude
Financial
Investment
Possible ROI within a
very short time
Possible ROI within a
moderate time frame
No business
experience, only
technology-driven,
limited talent, bad
attitude
Possible ROI after a
few years
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Case Study: A Detailed Risk Assessment Matrix (1-3)
Level of Risk
Variable
Green (Low)
Yellow (Medium)
Red (High)
Project requirements:
ad hoc reporting
Supports every critical
ad hoc reporting
requirement
Supports most critical ad
hoc reporting
requirements
Fails to support critical
ad hoc reporting
requirements
Project requirements:
AS/400
Supports every key
business requirement
Supports most key
business requirements
Fails to support key
business requirements
Business workflow
support
Supports business
workflow seamlessly
Requires some manual
intervention
Requires significant
manual intervention
Architecture evaluation
Well-architected
application
Existence of some
architectural issues
Poorly architected
application
Extensibility into
subsequent releases
Fully extensible into
subsequent releases
Extensible for most
requirements
Not extensible into
subsequent releases
Logical data model:
completeness
All information
requirements met
Most information
requirements
documented
Significantly mis-sing
information
requirements
Logical data model:
extensibility
Fully extensible
Some extensibility issues
Not extensible
Meta data (business and
technical)
Complete and easily
maintainable
Incomplete or not easily
maintainable
Not incorporated
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Case Study: A Detailed Risk Assessment Matrix (2-3)
Level of Risk
Variable
Green (Low)
Yellow (Medium)
Red (High)
Physical data model:
completeness
Complete and tuned
Complete but not tuned
Incomplete, cannot be
evaluated
Physical data model:
extensibility for new
product types
Fully extensible for new Limited product type
product types
extensibility
Incomplete, cannot be
evaluated
Physical data model:
source system feeds
Acceptable design
support for source
systems
Performance or timing
concerns
Incomplete, cannot be
evaluate
Interfaces (external and
internal)
Supports external and
internal interfaces
Limited support for
external and internal
interfaces
Poor support for external
and internal interfaces
Analysis dimensions and
measures: adding new
product lines
Easy to add
Can be added, but
requires significant cube
reconstruction
Cannot be evaluated at
the current time
Analysis dimensions and
measures: adding new
tools for data analysis
Proposed cubes and set Proposed cubes and set of Proposed cubes and set
of dimensions sufficient dimensions provide
of dimensions
to support the business minimum sufficiency
insufficient
analysts
Use of meta data
repository
Fully developed
Limited meta data
support
No meta data support
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Case Study: A Detailed Risk Assessment Matrix (3-3)
Level of Risk
Variable
Green (Low)
Yellow (Medium)
Red (High)
Loading of the BI target
databases
Load procedures
established and
perform well
Load procedures poorly
documented or perform
poorly
Load procedures not
developed, cannot be
evaluated
Physical database issues
Effective and efficient
physical database
design
Minor issues with physical Physical database design
database design
incomplete, cannot be
evaluated
Performance issues
Conforms to stated
performance
requirements
Some performance issues Cannot be evaluated at
this time
Systems management
issues: maintenance
Support procedures
well established and
documented
Limited support
documentation
Support issues
Backup and disaster
Backup and disaster
recovery procedures
recovery procedures
developed and installed developed but not
installed
No thought given to
backup and disaster
recovery procedures
Security
implementation
Satisfies application
needs and is easy to
maintain
Security design
incomplete, cannot be
evaluated
Difficult to maintain
No support procedures
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Business Case Assessment Activities
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Deliverable Resulting (Step 1)
1.Business case assessment report
- Strategic business goals of the organization
- Objectives of the proposed BI application
- Statement of the business need (business problem or business
opportunity)
- Explanation of how the BI application will satisfy that need
- Ramifications of not addressing the business need and not committing
to the proposed BI solution
- Cost-benefit analysis results
- Risk assessment
- Recommendations for business process improvements to the
operational systems or to the operational business processes and
procedures
The assessment report should also have a one- or two-page executive
overview that summarizes the details of the report.
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Roles Involved in Step 1
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Business representative
Business sponsor
Data quality analyst
Project manager
Subject matter expert
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Risks of Not Performing Step 1
no strong business driver and does not
support a strategic business goal.
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