OLAP deals with Historical Data or Archival Data. Historical
data are those data that are archived over a long period of time.
Example: If we collect last 10 years data about flight reservation,
The data can give us many meaningful information such as the trends in
reservation. This may give useful information like peak time of travel, what
kinds of people are traveling in various classes (Economy/Business)etc.
Historical Data or
Archival Data
Infrequent updates
Analytical queries
require huge number of aggregations
Integrated data set
with a global relevance
Updates are very rare here. Analytical queries requires huge
number of aggregations. In analytical queries the performance issue is mainly
in query response time. Query need to access large amount of data and require
huge number of aggregation.
OLAP Queries have significant importance in strategic
decision making. This helps the top level management in decision making.
Examples for OLAP Queries
How is the profit
changing over the years across different regions?
Is it financially
viable continue the production unit at location X?
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