TEXTBOOK :Sharda
Ramesh, Delen Dursun, and Turban Efraim, “ Business Intelligence A Managerial
Perspective on Analytics ”, Pearson, Third Edition, 2014.
Please find attached file.-Key Terms:
Explain each of the “Key Terms” (Chapter 1: Page 32), briefly with examples.
(In different
Page)
-What is
Business Intelligence? Explain different components of Business Intelligence
with examples.
key_terms_.pdfbi_intro1.pptSAP University Alliances
Version
2.0
Authors
Klaus Freyburger
Peter Lehmann
Introduction to Business
Intelligence
© 2010 All Rights Reserved. SAP UA
SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Agenda
▪ What is Business Intelligence?
▪ What is a „Data Warehouse“?
▪ What are the benefits and challenges?
▪ What does „multi-dimensional“ mean?
▪ What is „OLAP“?
▪ OLTP versus OLAP
▪ Business Intelligence tool box
© 2010 SAP AG
Page 2
SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
© 2010 SAP AG
What is Business Intelligence?
Page 3
SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
What is Intelligence?
Definition:
1.The ability to learn or understand or deal
with new and trying situations
2.The ability to apply knowledge to
manipulate one’s environment
Source: Merriam-Webster’s Online Dictionary
© 2010 SAP AG
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SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
•
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?
© 2010 SAP AG
Page 5
SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Main Objective of Business Intelligence
▪ Support intelligence (e.g., knowledge of status)
© 2010 SAP AG
Page 6
SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
A Brief History of Information Systems
▪ ERP Systems
© 2010 SAP AG
Page 7
SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
© 2010 SAP AG
Information Systems in a Company!?
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BI1-M1 Introduction to
Business Intelligence
Definition: „Business Intelligence“
▪ „Business Intelligence“ covers strategies, processes and
technologies in order to achieve knowledge about status,
potentials and perspectives of a company out of heterogeneous
and distributed data.
?
© 2010 SAP AG
Definition Source: Institut für Business Intelligence (IBI),
http://www.i-bi.de/home/index.html
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SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Business Intelligence Turns Data into Knowledge
Decision
Offer product B to
customer Smith
Knowledge
Product A & B have
a 80% sales correlation
Information
Customer Smith
buys product A
Data
Product A
Product B
Customer Smith
© 2010 SAP AG
Page 10
SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Business Intelligence Stages
Source: Brobst, S. and J. Rarey, “Five Stages of Data Warehouse
Decision Support Evolution”, DSSResources.COM, 01/06/2003
© 2010 SAP AG
Page 11
SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Agenda
▪ What is Business Intelligence?
▪ What is a „Data Warehouse“?
▪ What are the benefits and challenges?
▪ What does „multi-dimensional“ mean?
▪ What is „OLAP“?
▪ OLTP versus OLAP
▪ Business Intelligence tool box
© 2010 SAP AG
Page 12
SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
What is a Data Warehouse?
▪ A data warehouse is the most common
data architecture for business intelligence.
▪ A data warehouse is a specific
company-wide data pool in order
to support decision makers.
–
Top management
Mid and lower management
Planners, controllers, …
…
© 2010 SAP AG
Data
Warehouse
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BI1-M1 Introduction to
Business Intelligence
Data Warehouse Characteristics
▪ “A Data Warehouse is a subject-oriented, integrated, time-variant and
nonvolatile collection of data in order to support management decisions,“
Bill Inmon (1996).
–
Subject-oriented
• The organization of data is guided by the view of decision makers on specific areas
of business.
–
Integrated
• The Data Warehouse contains data from different internal and external sources.
Important is the high quality of data, i.e., its correctness and consistency.
–
Time-oriented
• Data in a Data Warehouse has a time dimension, i.e. all data values and their
changes in time can be compared and analyzed along the time axis.
–
Nonvolatile
• As opposed to operational databases, data are stored persistently in a Data
Warehouse. Access is by reading the
data; analysis does not change the data.
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Data Integration Process
Data analysis and
analytical applications
– OLAP, MIS, cockpits, …
– Planning, scorecard, …
Multi-dimensional data
– Information models
– Aggregation
Data warehouse
– Data storage
– Administration
Extraction, transformation, loading
– Selection, extraction,
– Modification, loading
Source systems
– External data sources
– Internal data sources
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Business Intelligence Platforms – 2008
Source: Gartner 2008
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Business Intelligence Platforms – 2009
Source: Gartner 2009
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Business Intelligence Platforms – 2010
Source: Gartner 2010
© 2010 SAP AG
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SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Agenda
▪ What is Business Intelligence?
▪ What is a „Data Warehouse“?
▪ What are the benefits and challenges?
▪ What does „multi-dimensional“ mean?
▪ What is „OLAP“?
▪ OLTP versus OLAP
▪ Business Intelligence tool box
© 2010 SAP AG
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SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Benefit: Reduce Action Time
Added
Operational
Value Transaction
Added
Value loss
Data Available
Analysis Results
Available
Decision
Made
Data
access
time
Analysis
time
Decision
time
Action
Implemented
Implementation
time
Action time
Time
Source: Hackathorn, R.: Minimizing Action Distance (2003), http://www.tdan.com/view-articles/5132/
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Benefit: Reduce Action Time to Nearly Real Time
Added
Operational
Value Transaction
Data Available
Analysis Results
Available
Decision Made
Saved
Value
Action Implemented
Action Implemented
Saved Time
Time
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Other Benefits
▪ Increased
–
Information quality by a „single version of the truth“
Competitive ability
Customer satisfaction
Inter-company and inter-department collaboration
Alignment with business strategy
▪ Compliance with financial reporting regulations
–
Risk management
Financial consolidation
Corporate planning and forecasting
SOX (US), BASEL II (European Community), etc.
…
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Challenges (1)
▪ Data Quality
–
Precise
Subject-oriented
Complete
Accessable
Flexibility
Security and authorisation
Time dependencies
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Challenges (2)
▪ Business Terms – What do you mean?
–
„What is our revenue“?
„95% of our trains arrive just in time!“
“How many students will certainly finish?”
…
I have a
stock here
that could
really
excel !
This is
Madness!
I can‘t take
anymore
Good Bye
© 2010 SAP AG
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SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Challenges (3)
▪ Tools – easy to use?
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Challenges (4)
▪ Others
–
No clear project scope
No management project support
No appropriated IT infrastructure
Inadequate staff qualification
Lack of end user acceptance
…
© 2010 SAP AG
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SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Agenda
▪ What is Business Intelligence?
▪ What is a „Data Warehouse“?
▪ What are the benefits and challenges?
▪ What does „multi-dimensional“ mean?
▪ What is „OLAP“?
▪ OLTP versus OLAP
▪ Business Intelligence tool box
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Multi-dimensional (1)
A material number?
A telephone number?
Revenue in September 2007?
My boss‘ salary?
1388486
▪ A key figure without a relationship to any object makes
no sense!
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Multi-dimensional (2)
▪ San Francisco had 1,388,486 USD revenue in May 2007 by
selling Mountain Bikes
Month: May
Year: 2007
Group: Mountain Bike
© 2010 SAP AG
Revenue in USD:
1,388,486
Sales Organisation:
San Francisco
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SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Multi-dimensional (3)
Multi-dimensional means a key figure always relates to one or
more objects.
▪ Key figure: Revenue
▪ Object:
–
Month
Year
Sales Organisation
Material Group
© 2010 SAP AG
Values
→
→
→
→
May
2007
San Francisco
Mountain Bike
Page 30
SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Agenda
▪ What is Business Intelligence?
▪ What is a „Data Warehouse“?
▪ What are the benefits and challenges?
▪ What does „multi-dimensional“ mean?
▪ What is „OLAP“?
▪ OLTP versus OLAP
▪ Business Intelligence tool box
© 2010 SAP AG
Page 31
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BI1-M1 Introduction to
Business Intelligence
OLAP
On-line Analytical Processing is a software technology which
allows end-user driven, fast and interactive data analysis.
Revenue
1,388,486 USD
© 2010 SAP AG
Page 32
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BI1-M1 Introduction to
Business Intelligence
Excel PivotTable
▪ „What is the revenue in each country in 2007?“
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
© 2010 SAP AG
Excel PivotTable (1)
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BI1-M1 Introduction to
Business Intelligence
Excel Pivot Table (2)
„What is the revenue in each country per month?“
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
© 2010 SAP AG
Pivot Table (3)
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BI1-M1 Introduction to
Business Intelligence
© 2010 SAP AG
From Table View to a 3-Dimensional Cube
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BI1-M1 Introduction to
Business Intelligence
Hierachies Allow Subcubes in a Cube
▪ Product group → products
▪ Year → quarter → months
Example
▪ Country → sales organisation
© 2010 SAP AG
Page 38
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BI1-M1 Introduction to
Business Intelligence
© 2010 SAP AG
From Cube to Report: MS Excel
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SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
© 2010 SAP AG
From Cube to Report: SAP Business Explorer (1)
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BI1-M1 Introduction to
Business Intelligence
From Cube to Report: SAP Business Explorer (2)
click
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
© 2010 SAP AG
From Cube to Report: SAP Business Explorer (3)
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BI1-M1 Introduction to
Business Intelligence
Cube Navigation (1)
▪ Slice
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Cube Navigation (2)
▪ Rotation
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Cube Navigation (3)
▪ Rotation, Example
Material Group
and Country
visible, Year
restricted to 2007
Material Group
and Year visible,
all Countries
aggregated
© 2010 SAP AG
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SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Cube Navigation (4)
▪ Dice
© 2010 SAP AG
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SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Cube Navigation (5)
▪ Drill-Down / Roll-Up
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Cube Navigation (Summary)
▪ Rotation
▪ Slice
▪ Dice
▪ Drilldown
© 2010 SAP AG
Page 48
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BI1-M1 Introduction to
Business Intelligence
Is a Excel an OLAP Tool?
▪ CFOs & controllers love it
▪ Cheap
▪ MS Office component
▪ Easy to use
▪ Nice graphics
© 2010 SAP AG
Page 49
SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Is Excel an OLAP tool? What about…
▪ Concurrent users?
▪ Data volume?
▪ Processing performance?
▪ Aggregation behavior (fat client)?
▪ Authorizations?
▪ Metadata?
▪ Many data sources?
▪ Cell references?
▪ …
© 2010 SAP AG
Page 50
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SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Requirement for OLAP Systems
▪ Many concurrent users (1000+)
▪ Sophisticated authorizations and security
▪ Fast response time (< 5 sec)
▪ High data volumes (>100+ GB or TB)
▪ Multiple data sources
▪ Easy to use (slice, dice, drill-down, roll-up)
▪ Enhanced reporting functions
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Exercises
▪ OLAP navigation using Excel PivotTables
▪ OLAP navigation in SAP
– Business Explorer Analyzer (Excel)
– Business Explorer Web (Browser)
© 2010 SAP AG
Page 52
SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
BI Architecture
Data analysis and
analytical applications
– OLAP, MIS, cockpits, …
– Planning, scorecard, …
Multi-dimensional data
– Information models
– Aggregation
Data warehouse
– Data storage
– Administration
Extraction, transformation, loading
– Selection, extraction,
– Modification, loading
Source systems
– External data sources
– Internal data sources
© 2010 SAP AG
Page 53
SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Examples
MS Excel
PivotTable
SAP Business
Explorer Analyzer
SAP Business
Explorer Web
PivotTable
Excel with SAP
Add-In
Browser
PivotTable
SAP BI System
SAP BI System
Excel table or
local database
SAP BI Database
SAP BI Database
Presentation
Model Logic
Data Storage
© 2010 SAP AG
Page 54
SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Agenda
▪ What is Business Intelligence?
▪ What is a „Data Warehouse“?
▪ What are the benefits and challenges?
▪ What does „multi-dimensional“ mean?
▪ What is „OLAP“?
▪ OLTP versus OLAP
▪ Business Intelligence tool box
© 2010 SAP AG
Page 55
SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Information Systems
Strategic
Enterprise
Management
Corporate
Planning
Analysis
and Controlling
Vertical Integration
Accounting
Employee
Salary
Stocks
Disposition and
Planning
Customer
Invoices
Purchasing
Warehouse
Accounting
Supplier
Accounting
Supplier Management,
Production Planning,
Cost Planning, …
Sales
Personnel
Horizontal Integration
Administration I:
Value-Oriented
Processing
Administration II:
Amount-Oriented
Processing
Source: Mertens, P., Meier, M.: Integrierte Informationsverarbeitung (2009), 1.
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
OLTP versus OLAP
Strategic
Enterprise
Management
Corporate
Planning
On-line
Analytical
Processing
Employee
Salary
Stocks
Sales
Personnel
Horizontal Integration
© 2010 SAP AG
Disposition and
Planning
Customer
Invoices
Purchasing
Warehouse
Accounting
Supplier Management,
Production Planning,
Cost Planning, …
Supplier
Accounting
On-line
Transactional
Processing
Analysis
and Controlling
Accounting
Administration I:
Value-Oriented
Processing
Administration II:
Amount-Oriented
Processing
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BI1-M1 Introduction to
Business Intelligence
OLTP Versus OLAP (1)
OLTP
OLAP
– Optimized to get data in
– Optimized to get data out
– For management and
daily business
– For administration and daily
decisions
– Processes a small amount of
data per transaction
– Processes a large amount of
data per transaction
– Business-critical availability
– Less critical availability
– Data updates online
– Data updates regularly
– Data overwritten
– Data are time-dependent
© 2010 SAP AG
Page 58
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BI1-M1 Introduction to
Business Intelligence
OLTP Versus OLAP (2)
It is very hard to get all-in-one!
© 2010 SAP AG
Page 59
SAP UA
SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Agenda
▪ What is Business Intelligence?
▪ What is a „Data Warehouse“?
▪ What are the benefits and challenges?
▪ What does „multi-dimensional“ mean?
▪ What is „OLAP“?
▪ OLTP versus OLAP
▪ Business Intelligence tool box
© 2010 SAP AG
Page 60
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SAP BI Curriculum
BI1-M1 Introduction to
Business Intelligence
Where Are the End Users?
Corporate
Planning
Top Management
Analysis
and Controlling
Accounting
Supplier Management,
Production Planning,
Cost Planning, …
Customer
Invoices
Employee
Salary
Warehouse
Accounting
Supplier
Accounting
Middle Management
Purchasing
Sales
Personnel
Lower Management
Stocks
Horizontal Integration
© 2010 SAP AG
Strategic
Enterprise
Management
Disposition and
Planning
Administration I:
Value-Oriented
Processing
Administration II:
Amount-Oriented
Processing
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BI1-M1 Introduction to
Business Intelligence
© 2010 SAP AG
What Do They Do?
10%
Specialists
(Authors)
20%
Analysts
70%
Consumers
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BI1-M1 Introduction to
Business Intelligence
Consumers
▪ Get reports on a regular base
▪ Look over huge amount of data
▪ Occasionally stumble on something that proves
to be useful
▪ Sporadic usage of data
▪ Sometimes find areas for further exploration
▪ Heavy reliance on tools for displaying data
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Analysts
▪ Regular access to data
▪ Know what they are looking for
▪ Requirements known before search for data
starts
▪ Find small flakes of gold regularly
▪ Make use of tools for analysis and presentation
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Specialists (Authors)
▪ Requirements are known
▪ Irregular access to data
▪ Look over massive amounts of data
▪ Sometimes find huge nuggets of gold
▪ Unpredictable pattern of access
▪ Access detailed data regularly
▪ Look at relationships of data
▪ Make use of tools of discovery, analysis and
presentation
▪ Make results available to others (consumers,
analysts)
© 2010 SAP AG
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BI1-M1 Introduction to
Business Intelligence
Business Intelligence Tool Box
Source: Eckerson, W. (May 2006). Business intelligence 2006 – only the beginning.
What Works, 21.
© 2010 SAP AG
Page 66
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BI1-M1 Introduction to
Business Intelligence
Summary
▪ What is Business Intelligence?
▪ What is a „Data Warehouse“?
▪ What are the benefits and challenges?
▪ What does „multi-dimensional“ mean?
▪ What is „OLAP“?
▪ OLTP versus OLAP
▪ Business Intelligence tool box
© 2010 SAP AG
Page 67
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