Answer / suresh

Sr Relational Modelling Multi-Dimensional Modelling
1 Relational models can be very complex with hundreds
of tables having long chains of relationship among them.
Multidimensional modeling are very simple. Each of
the dimension table has a direct relationship with the fact
table
2 Normal data modeling is quite flexible. The
Multidimensional modeling has a rigid structure
3 One of the goals of relational modeling is to
confirm to the rules of normalization. In a normalized
database each data value is stored only once.
Multidimensional modeling are radically
denormalized. The dimension tables have a high number of
repeated values in their fields.
4 Standard relational models are optimized for On
Line Transaction Processing. OLTP needs the ability to
efficiently update data. This is provided in a normalized
database that has each value stored only once.
Multidimensional modeling are optimized for On Line
Analytical Processing. OLAP needs the ability to retrieve
data efficiently. Efficient data retrieval requires a
minimum number of joins. This is provided with the simple
structure of relationship in a Multidimensional modeling,
where each dimension table is only a single join away from
the fact table.
5 SQL queries required to manipulate relational data
MDX queries required to manipulate multi-
dimensional data
6 Tables are units of relational data storage.
Cubes are units of multi-dimensional data storage.
7 Table fields of particular data type store the
actual data. Dimensions and measures stores actual data.
8 Table size is measured in number of record set.
Cube size is measured in number of Cellsets. In
this sense, MS Excel Pivot Table can accommodate 2,040,000
cellsets (8000 * 255). Considering the summary data to be
reported, this is reasonably large. Pivot Table can report
at the most 8000 different items.

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multithreading??

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