OLAP stands for Online Analytical Processing Server. It is a software technology that allows users to analyze information from multiple database systems at the same time. It is based on multidimensional data model and allows the user to query on multi-dimensional data (eg. Delhi -> 2018 -> Sales data). OLAP databases are divided into one or more cubes and these cubes are known as Hyper-cubes.
There are five basic analytical operations that can be performed on an OLAP cube:
- Drill down: In drill-down operation, the less detailed data is converted into highly detailed data. It can be done by:
- Moving down in the concept hierarchy
- Adding a new dimension
In the cube given in overview section, the drill down operation is performed by moving down in the concept hierarchy of Time dimension (Quarter -> Month).
- Roll up: It is just opposite of the drill-down operation. It performs aggregation on the OLAP cube. It can be done by:
- Climbing up in the concept hierarchy
- Reducing the dimensions
In the cube given in the overview section, the roll-up operation is performed by climbing up in the concept hierarchy of Location dimension (City -> Country).
- Dice: It selects a sub-cube from the OLAP cube by selecting two or more dimensions. In the cube given in the overview section, a sub-cube is selected by selecting following dimensions with criteria:
- Location = “Delhi” or “Kolkata”
- Time = “Q1” or “Q2”
- Item = “Car” or “Bus”
- Slice: It selects a single dimension from the OLAP cube which results in a new sub-cube creation. In the cube given in the overview section, Slice is performed on the dimension Time = “Q1”.
- Pivot: It is also known as rotation operation as it rotates the current view to get a new view of the representation. In the sub-cube obtained after the slice operation, performing pivot operation gives a new view of it.
- Types of OLAP Systems in DBMS
- Difference between OLAP and OLTP in DBMS
- Online Transaction Processing (OLTP) and Online Analytic Processing (OLAP)
- OLAP Guidelines (Codd's Rule)
- Difference between Data Mining and OLAP
- Lossless Decomposition in DBMS
- Introduction of Relational Algebra in DBMS
- Need for DBMS
- Commonly asked DBMS interview questions | Set 1
- Normal Forms in DBMS
- View Serializability in DBMS Transactions
- Relational Model in DBMS
- Commonly asked DBMS interview questions | Set 2
- Concurrency Control in DBMS
- Conflict Serializability in DBMS
- Recoverability in DBMS
- Last Minute Notes - DBMS
- ACID Properties in DBMS
- DBMS Architecture 2-Level, 3-Level
- Introduction of DBMS (Database Management System) | Set 1
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