Data WarehouseAima First

8/16/2019 Data WarehouseAima First

1/34


2/34


3/34


4/34


5/34

Subject oriented


6/34

Subject oriented


7/34


8/34

Integrited


9/34


10/34

Time Varient


11/34

Time Varient


12/34


13/34


14/34


15/34


16/34


17/34


18/34


19/34


20/34


21/34


22/34

Architecture of DataWareHouse


23/34

Architecture of a DataWarehouse with a Staging Area

Architecture of a Data


24/34

Architecture of a DataWarehouse with a Staging Area

and Data Marts


25/34

Distributed Data WareHouse


26/34

Incorrect Data in the Datawarehouse.

• The architect needs to know what is to doabout incorrect data in the data warehouse.

• The rst assumtion is that incorrect data

arri!es in the data warehouse on ane"cetion basis.

• If the data is being incorrect#$ entered inthe data warehouse on a who#esa#e basis%

then• It is the dut$ of the architect to nd the

o&ending and make adjustment.


27/34

How to correct

• To correct the o&ending an architect can dothree things.

• '"am#e( suose on ju#$ ) *s +,, is made into oerationa# s$stem on ju#$ - a snashot

taken in data warehouse and on ju#$ )+ itdisco!ered that it was a entr$ of -+, ratherthan +,, on ju#$ ).

• Then

• choice ). go back to ju#$ - and udate -+,insite of +,,. but it can create rob#em if an$reort has been taken between ju#$ - to ju#$ )+.


28/34

How to correct

• choice -.

• 'nter o&setting entr$ i.e make twoentr$ rst debit +,, then credit -+,.

some time it a#so can create rob#em.• hoice /.

• *eset the account to the roer !a#ue.

•

but it wi## not correct the error.• So deending on the situation $ou can

make an$ decision.


29/34

Structuring Data in DataWarehouse

• The sim#est and most common data structurefound in the data warehouse is The sim#estcumu#ati!e structure i.e dai#$ transactions beingreorted from the oerationa# en!ironment.

• '"am#e( jan )% jan- jan/ data• *o##ing summar$ data

• After that the$ are summari0ed into data warehouse records%

• '"am#e( *o##ing summar$ data• Week) data% week- data% month) data month-

data.


30/34

*eorting and the architecteden!ironment

• 1nce the data warehouse has been constructed a##reorting and infromationa# rocessing wi## be donefrom there.

• ). 1erationa# reorting for c#erica# #e!e#• It focus on the #ine item2detai#ed information3.• '"am#e( A cashier has to check who#e da$

transaction in the e!ening for ba#ance check.• -. Data ware house reorting for management #e!e#.• It focus on summar$ information.•

'"am#e( A bank !ice resident has to take decisionhow man$ ATM machine has to #ace in thatarticu#ar cit$ so he does not need one da$transactions but he needs one month or one $earsummar$ of data to take decision.


31/34

4urging Ware house Data

• Data urging is nothing but de#eting$our data from DW.

• Data does not just our into a dataware house. It has its own #ife c$c#ewithin the data warehouse.

• It does not means it is fu##$ remo!edit means it ro##ed u to high #e!e# ofsummar$. Where detai#s is #ost.


32/34

5ranu#arit$

• *efers to the #e!e# of detai#s of the Data

• Dua# #e!e# of 5ranu#arit$(6

• ). 7ow 7e!e# of Detai#2More detai#s3

• -. High 7e!e# of detai#2 #ess detai#s i.eSummar$3

• Most#$ Data in Data warehouse is in High #e!e#

• 8ut it has 7ow 7e!e# of Detai# a#so for atomic9uer$.


33/34

Data 5ranu#arit$

• Data Granularity• A signicant di&erence between an oerationa# s$stem

and a data warehouse is the granu#arit$ of the datastored.

• An oerationa# s$stem t$ica##$ stores data at the

#owest #e!e# of granu#arit$( the ma"imum #e!e# of detai#.• Howe!er% because the data warehouse contains data

reresenting a #ong eriod in time% sim#$ storing a##detai# data from an oerationa# s$stem can resu#t in ano!erworked s$stem that takes too #ong to 9uer$.

• A data warehouse t$ica##$ stores data in di&erent#e!e#s of granu#arit$ or summari0ation% deending onthe data re9uirements of the business. If an enterriseneeds data to assist strategic #anning% then on#$ high#$summari0ed data is re9uired.


34/34

5ranu#arit$

• The #ower the #e!e# of granu#arit$ of data re9uired b$the enterrise% the higher the number of resources2secica##$ data storage3 re9uired to bui#d the datawarehouse. The di&erent #e!e#s of summari0ation inorder of increasing granu#arit$ are(

• urrent oerationa# data• Historica# oerationa# data• Aggregated data• Metadata• urrent and historica# oerationa# data are taken%

unmodied% direct#$ from oerationa# s$stems.Historica# data is oerationa# #e!e# data no #onger9ueried on a regu#ar basis% and is often archi!edonto secondar$ storage.

Documents

Data WarehouseAima First