ddb presentation2data warehousing
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Data Warehousing
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The Data Warehouse DefinitionB. Imnon:
A data warehouse is a subject oriented, integrated, non-
voatie, and time-variant coection of data in su!!ort of
management"s decisions.
#. $haudhiri % &. Da'a:
Data warehousing is a coection of decision su!!ort
technoogies, aimed at enabing the (nowedge wor(er)e*ecutive, manager, ana'st+ to ma(e better and
faster decisions.
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Data Warehouse Subject-Oriented
Organized around major subjects, such ascustomer, product, sales.
Focusing on the modeling and analysis of datafor decision makers, not on daily operations ortransaction processing.
Provide a simple and concise view aroundparticular subject issues by ecluding datathat are not useful in the decision supportprocess.
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Data Warehouse Integrated !onstructed by integrating multiple, heterogeneous
data
"ources
# relational or other databases, flat files, eternal data
$ata cleaning and data integration techni%ues areapplied.
# &nsure consistency in naming conventions, encoding
structures, attribute measures, etc. among differentdata
sources# 'hen data is moved to the warehouse, it is converted.
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Data Warehouse Time Variant
(he time horizon for the data warehouse issignificantly longer than that of operational systems.
# Operational database) current value data.# $ata warehouse data) provide information from a
historical perspective *e.g., past +- years/ &very key structure in the data warehouse
# !ontains an element of time# 0ut the key of operational data may or may not contain
1time element2.
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Data Warehouse Non-Volatile
3 physically separate store of data
transformed from the operationalenvironment.
Operational update of data does not occur inthe data warehouse environment.
# $oes not re%uire transaction processing,recovery, and concurrency control mechanisms
# 4e%uires only ) loading and access of data.
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Decision Support and OLA !Na"athe# 5nformation technology to help the knowledgeworker *eecutive, manager, analyst/ make faster
and better decisions.
# 'ill a -6 discount increase sales volume sufficiently7# 'hich of two new medications will result in the best
best outcome) higher recovery rate 8 shorter hospitalityrate7
# 9ow did the share price of computer manufacturers
correlate with %uarterly profits over the past - years7
On:ine 3nalytical Processing *O:3P/ is an elementof decision support system *$""/.
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Data Warehouse !Na"athe#
3 decision support database that is maintainedseparately from the organisation;s operationaldatabases. 3 data warehouse is a
# subject oriented,# integrated,# timevarying,
# nonvolatile
collection of data that is used primarily in theorganisational decision making.
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Wh$ separate data %arehouse&
Performance
# (he operational $0s are tuned to support known O:(Pworkloads# "upporting O:3P re%uires special data organisations,
access methods and implementation methods
Function# (he decision support re%uires data that may be missing
from the operational $0s# $ecision support usually re%uires consolidating data frommany heterogeneous sources
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OLT "s' OLA
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oas of a Data Warehouse
The data warehouse must ma(e an organisation"s
information easi' accessibe
The data warehouse must !resent the organisation"sinformation consistent'
The data warehouse must be ada!tive and resiient tochange
The data warehouse must be a secure bastion that!rotects our information assets
The data must serve as the foundation for im!roveddecision ma(ing
The business communit' must acce!t the data
warehouse if it is to be deemed successfu.
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Data Warehouse Architecture
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Another iew of the DW Architecture
!erationa
#ource
#'stems
#ervices:
$ean, combine, and
standardi/e
$onform dimensions
0
3&124#12I$1#
Data #tore:
5at fies and
reationa
tabes
6rocessing:
#orting and
se7uentia
!rocessing
Data 8art 9
DI810#I0A;
Atomic and
summar' data
Based on a singe
business !rocess
Data 8art 9< =
)#imiar' designed+
Ad >oc 3uer' Toos
2e!ort Writers
Ana'tic
A!!ications
8odeing:
5orecasting
#coring
Data mining
1*tract
1*tract
1*tract
Data
#taging
Area
;oad
;oad
Data
6resentation
Area
DW Bus:
$onformed
facts %
dimensions
Access
Access
Data
Access
Toos
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Data Warehouse "s' Data (art
&nterprise warehouse) collects all information
about subject *customer, products, sales, assets,personnel/ that span the entire organisation
# 4e%uires etensive business modelling
#
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To (eet the )e*uirements %ithin DW
(he data is organised differently, i.e.1multidimensional2# starjoins schemas# snowflake schemas
(he data is viewed differently (he data is stored differently# vector *array/ storage
(he data is indeed differently# bitmap indees# join indees
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Dimensional (odelling + ,asic oncepts
Fact
# 1something not known in advance2,# an observation# many facts *but not all/ have numerical,
continuously values
e.g., the price of a product, %uantity
3ttribute# 1describe a characteristic of a tangible thing2# 1we do not measure them, we usually know them2# usually tet fields, with discrete valuese.g., the flavour of a product, the size of a product
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$< # 0asic !oncepts = $imension
# a business perspective from which data islooked upon
# 1a collection of tet like attributes that arehighly correlated2
e.g. Product, "tore, (ime
>ranularity
# the level of detail of data contained in the datawarehousee.g. $aily item totals by product, by store
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./ample o0 a Dimensional (odel
Th St d d T l t 1
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The Standard Template 1uer$
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The Time Dimension
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8utidimensiona Data
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A #am!e Data $ube
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5acts
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5acts and Additive 6ro!ert'
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#emiadditive fact 1*am!e
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0umeric 8easures of Intensit'
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1nd