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Data Warehousing andData Mining

Data Warehouse Design

Physical Design

Bitmap Indexing

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Contain a large number of dataorganised in a table structure, i.e. inthe form of rows and columns

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Read Write Tables (High volume useof Insert, !date, Delete statements"

Read #nl$ Tables % &tatic Data

'ggregate Tables

Dimension Tables

act Tables

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Inde)es hel! to *uic+l$ locate !ieces ofinformation about a to!ic which arescattered around a number of

resources. or e.g, the inde) of a boo+tells what !ages of the boo+ refer to aconce!t listed in the inde)es.

Inde)es are created in DatabasesDatawarehouses for e-cientidentication of the re*uested rows

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the act of classif$ing and !roviding an inde)in order to ma+e items easier to retrieve

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/ Tree (/inar$ Tree" Inde)ing

Hash Table

/itma! Inde)ing

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0ormall$ used for #1T2 a!!lications(man$ read3write o!erations"

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/3trees are alwa$s height balanced, with all leafnodes at the same level

!date and search o!erations a4ect onl$ a few dis+!ages, so !erformance is good.

/3trees +ee! related records on the same dis+ !age,which ta+es advantage of localit$ of reference.

/3trees guarantee that ever$ node in the tree will befull at least to a certain minimum !ercentage. This

im!roves s!ace e-cienc$ while reducing the t$!icalnumber of dis+ fetches necessar$ during a search oru!date o!eration over man$ thousands of records.

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Contains a 5fact table5, !lus a numberof 5dimension tables5 whose +e$s areforeign +e$s of the fact table.

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How would $ou e-cientl$ answer the*uer$6 5ind the total sales ofraincoats for each location last $ear.5

7ou ma$ assume suitable inde)es.

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0umber of relations can be large %8oin si9e estimation is di-cult.

Dimension tables are often small,es!eciall$ when considering onl$ thetu!les matching a select o!eration.

#ften data can be assumed to be

static (a sna!shot of the o!erationaldata". This means that we have theo!tion to !recom!ute.

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&u!!ose there are onl$ : di4erentlocations in our !revious e)am!le.

Then we ma$ re!resent the locations of 0

fact table tu!les using onl$ ;0 bits. However, a (clustered" inde) on location

seems to re*uire at least 0 log 0 bits.

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or each !ossible value(of 5location5" and eachtu!le, store a bit that is