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OLAP operations in Data warehousing.pptx
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- 7. Roll-up operation •It isalso called ‘aggregation.’ We can perform this operation in two ways. •Reduction of dimension: It is the system in which the cube reduces its dimension •Climbing up concept hierarchy. It is the system of grouping things based on their level.
- 10. made by RadmiloPesic & Branko Golubovic 10/74
- 11. Drill-down operation •It isthe opposite process of roll-up. It performs in 2 ways. •Increasing of dimension •Climbing down the concept hierarchy
- 14. made by RadmiloPesic & Branko Golubovic 14/74 Chicago Toronto Vancouver New York computer security phone home entertainment Q1 Q2 Q3 Q4 item (types) time (quarters) location (cities) 400 14 825 605 computer security phone home entertainment item (types) computer security phone home entertainment item (types) supplier=“SUP1” supplier=“SUP1” supplier=“SUP2” A 4-D data cube representation of sales data for AllElectronics
- 15. made by RadmiloPesic & Branko Golubovic 15/74 1560 440 395 400 14 825 605 Chicago Toronto Vancouver New York computer security phone home entertainment Q1 Q2 Q3 Q4 item (types) time (quarters) address (cities) computer security phone home entertainment item (types) computer security phone home entertainment item (types) Chicago Toronto Vancouver New York address (cities) Q1 Q2 Q3 Q4 time (quarters) 100 150 150 1000 2000 Canada USA address (countries) time (months) Jan March Feb <Vancouver,Q1,security> Roll-up on address Drill-down on time data for Q1
- 16. In a slicemethod, one dimension is chosen, and a subcube is generated. Two or more dimensions are selected in a dice operation, and subcubes are generated.
- 20. made by RadmiloPesic & Branko Golubovic 20/74 time, location, supplier time, item, location time, item, supplier item, location, supplier time, item, location, supplier time, location time, supplier location, supplier time, item item, location item, supplier time location item supplier all 0-D (apex) cuboid 1-D cuboid 4-D (base) cuboid 2-D cuboid 3-D cuboid Lattice of cuboids, making up a 4-D data cube
- 21. made by RadmiloPesic & Branko Golubovic 21/74
- 22. Pivot • The pivotoperation is also known as rotation. • It rotates the data axes in view in order to provide an alternative presentation of data. made by Radmilo Pesic & Branko Golubovic 22/74
- 23. Pivot • To providea substitute presentation of data, you need to rotate the data axes in this operation 23/74
- 25. made by RadmiloPesic & Branko Golubovic 25/74 1560 440 395 400 14 825 605 Chicago Toronto Vancouver New York computer security phone home entertainment Q1 Q2 Q3 Q4 item (types) time (quarters) location (cities) 2000 1000 USA Canada computer security phone home entertainment Q1 Q2 Q3 Q4 item (types) time (quarters) location (countries) 150 100 150 Chicago Toronto Vancouver New York computer security phone home entertainment item (types) time (months) location (cities) January February March April May June July August September October November December roll-up on location (from cities to countries) drill-down on time (from quarters to months)
- 28. made by RadmiloPesic & Branko Golubovic 28/74 1560 440 395 400 14 825 605 Chicago Toronto Vancouver New York computer security phone home entertainment Q1 Q2 Q3 Q4 item (types) time (quarters) location (cities) 395 605 USA Canada computer home entertainment Q1 Q2 item (types) time (quarters) location (cities) dice for (location=“Toronto” or “Vancouver”) and (time=“Q1”or “Q2”) and (item=“home entertainment” or “computer”) slice for time=“Q1” 400 14 825 605 Vancouver Toronto New York Chicago computer security phone home entertainment item (types) location (cities) 400 14 825 605 Vancouver Toronto New York Chicago computer security phone home entertainment item (types) location (cities) pivot