business intelligence technologies (1)
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Business Intelligence Technologies
Donato MalerbaDipartimento di Informatica
Universit degli Studi, Bari, Italy
http:!!!.di.uniba.it"malerba
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Business Intelligence
Business Intelligence is a global term
for all the processes, techniques and
tools that support business decision-
making based on informationtechnology.
The approaches can range from a
simple spreadsheet to a major
competitive undertaking. ata mining is an important ne!
component of business undertaking.
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Business Intelligence Technologies
Data Sources
Paper, Files, Information Providers, Database Systems, OLTP
Data #arehouses Data $arts
Data %&ploration
OLAP, DSS, EIS, Querying and eporting
Data $ining
Information dis!overy
Data 'resentation
"isuali#ation Te!$ni%ues
Decision
$a(ing
Increasing potentialto support
business decisions
End User
Business
"nalyst
ata
"nalyst
B
"dmin
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Business Processes ata for support decision making
decisional
processes)agreement !ith a credit card*
managementprocesses
)grant a loan*
operational
processes
)transaction on
ban( account
)%&.: Ban(ing*
DSS o %IS
$IS
+'S
ifferent information systems support thedifferent processes
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DSS vs. EIS ecision #upport #ystems $##% and
&'ecutive Information #ystems $&I#%(
information systems designed to help
managers in making choices.
ifferent, yet interrelated applications " ## focuses on a particular decision,
!hereas an &I# provides a much !ider
range of information $e.g., information on
financials, on production history, and on
e'ternal events%.
##s appeared in the )*+s
&I#s appeared in the )*s.
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DSS vs. EIS The original &I#s did not have the
analytical capabilities of a ##
"n &I# is used by senior managers to
find problems/ the ## is used by the
staff people to study them and to offeralternatives0 $1ockart and elong, )*%
%IS DSS
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Where do Data Come From? The &I#s and ##s often lacked a strong
database component.
2ost organi3ational information gathering
!as $and is% directed to maintaining
current $preferably on-line% informationabout individual transactions and
customers.
2anagerial decision making requires
consideration of the past and the future,not just the present.
4e! databases, called data &are$ouses,
!ere created specifically for analytic use
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A Data Warehouse is ...
" data !arehouse is a subect-oriented,
integrated,
time-variant, and
nonvolatile
collection of data in support of management5sdecisions
Inmon, #..Building the Data Warehouse#ellesley, $/: 0%D +ech. 'ub. 1roup,2334
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su!ect"oriented ...
The data in the !arehouse is definedand organi3ed in business terms, and is
grouped under business'orientedsub(e!t $eadings, such as
customers
products
sales
rather than individual transactions.
)ormali#ationis not relevant.
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integrated ... The data !arehouse contents are defined such that
they are valid across the enterprise and its operationaland e'ternal data sources
5perational systems
Data !arehouse
The data in the !arehouse should be clean
validated
properly integrated
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time"variant ...
"ll data in the data !arehouse is time-
stamped at time of entry into the
!arehouse or !hen it is summari3ed
!ithin the !arehouse. This chronological recording of data
provides historical and trend analysis
possibilities.
6n the contrary, operational data is
over!ritten, since past values are not of
interests.
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nonvolatile ...
6nce loaded into the data !arehouse, the
data is not updated.
ata acts as a stable resource for
consistent reporting and comparativeanalysis.
6n the contrary, operational data is
updated $inserted, deleted, modified%.
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Which Data in the Warehouse?
" data !arehouse contains five types ofdata(
6urrent detail data
5ld detail data
7ightly summari8ed data
ighly summari8ed data
$etadata
*ranularityof the data( a key designissue
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Flo# o$ Data
5perational
%nvironment
6lean thedata
9eside in
!arehouse
'urge
Summari8e
/rchive
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An E%am&le o$ Data Integration
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