ddb presentation2data warehousing

7/26/2019 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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ddb presentation2data warehousing

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