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Vs. OLAP. Geography heirarchy Sales campaigns Other dimension Products Time Sales, profit, costs, key numbers, etc. Sales organization Star Scheme.

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Presentation on theme: "Vs. OLAP. Geography heirarchy Sales campaigns Other dimension Products Time Sales, profit, costs, key numbers, etc. Sales organization Star Scheme."— Presentation transcript:

1 vs. OLAP

2 Geography heirarchy Sales campaigns Other dimension Products Time Sales, profit, costs, key numbers, etc. Sales organization Star Scheme

3 Snowflake Scheme Geography heirarchy Sales campaigns Other dimension Products Time Sales, profit, costs, key numbers, etc. Sales organization Products Time Other dimension Other dimension Geography heirarchy Sales organization

4 Data Warehouse Geography heirarchy Sales campaigns Other dimension Products Time Sales, profit, costs, key numbers, etc. Sales organization Products Time Other dimension Other dimension Geography heirarchy Sales organization

5 Relational OLAP Data Warehouse SQL queries are generated graphically. Flexible, but neither fast nor user-friendly. User Interface

6 Multidimensional OLAP Data Warehouse User Interface Hyper Cube Build the cube. Lots of Data. Slow. Everything must be predefined. Every click is a query. Fast, but not flexible. Limited number of dimensions.

7 Hybrid OLAP Data Warehouse User Interface Hyper Cube Every click is a query. Fast, but not flexible. Limited number of dimensions. Drill-through when needed. Slow, and not user-friendly.

8 Data Warehouse User Interface QlikView file

9 Relational database inside QlikView document. Data Warehouse User Interface QlikView file Data Warehouse is not required. Any data source will do.

10 Data Source User Interface QlikView file Load the data… then work off-line!

11 User Interface QlikView file

12 Every click is a query. Extremely fast, and very flexible. Click ! The selection propagates through the relational database. The technology used is called AQL. User Interface

13 AQL™ The patented AQL technology performs its associations when a QlikView user makes a query through the point- and-click interface. As a value or several values (in a dimension) are selected, QlikView makes a split second association showing only values (in other dimensions and measures) associated with the current selection. Simultaneously, graphs and tables (holding one or several general expressions), are calculated to show the result of the current selection.

14 Any number of Virtual hypercubes (Pivot tables, Diagrams, Gauges etc.) can be put in the QlikView document. These are calculated on demand, i.e. on every click. User Interface

15 MOLAP –Limited number of dimensions –Not Flexible ROLAP –Not User-friendly HOLAP –A poor combination of the two above methods Summary

16 Data warehouse not necessary Unlimited number of dimensions Possibility for several hypercubes talking to each other Flexible User-Friendly Summary


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