1.
OLAP
OLAP is nothing but Online Analytical
Processing. As we have discussed about OLAP and OLTP Detailed description is
down below.
1.1.
What is OLAP?
Online Analytical Processing Server
basically works on the multidimensional data model. It performs
multidimensional analysis of business data and sophisticated data modelling.
The chief component of OLAP is the OLAP server which resides between a client
and database management system. It
allows higher authority to get an access of information through fast and
consistent access to data.
1.2.
Types of OLAP
There are four types of OLAP Servers:
Ø Relational OLAP
Ø Multidimensional OLAP
Ø Hybrid OLAP
Ø Specialized SQL servers
1.2.1.
Relational
OLAP
Relational OLAP is also known as
ROLAP which is nothing but the OLAP server which maps multidimensional
operations to standard relational operations. ROLAP servers are placed between
relational back-end server and client front end tools.
ROLAP has following features:
ü Implementation of aggregation navigation
logic
ü Optimization
for each DBMS back end.
ü Additional
tools and Services.
1.2.2.
Multidimensional
OLAP
Multidimensional OLAP is commonly
known as MOLAP which utilizes the multidimensional operation. It uses array
based multidimensional storage engines for multidimensional views on the data.
Many MOLAP severs uses two levels of data storage representation to handle
dense sparse data sets.
1.2.3.
Hybrid
OLAP
It is combination of both ROLAP and
MOLAP.
It offers following features:
ü Higher Scalability of data of ROLAP
ü Faster computation of MOLAP.
It is commonly known as HOLAP.
1.2.4.
Difference
between ROLAP and MOLAP
ROLAP:
·
Data
Retrieval is very slow.
·
Uses
relational table.
·
Available
space in data warehouse is enough for it.
MOLAP
·
Data
retrieval is fast.
·
Uses
sparse array to store data.
·
Maintains
a separate database for data cubes.
1.3.
OLAP Operations
As discussed in above “what is OLAP“,
it is based on multidimensional view of data.
Different types of OLAP operations
are as follows:
Ø Roll – up
Ø Drill – Down
Ø Slice – dice
Ø Pivot (rotate)
1.3.1.
Roll
– Up
Roll – up performs aggregation on
data cube in any of the following ways:
Ø Dimension Reduction: In this one
dimension is reduced that is hierarchical order is reduced or rolled up.
Ø Or by increasing dimensions by
hierarchical order.
The following diagram
illustrates roll – up:
Rollup is always performed on
hierarchy. For example here in above example locations are in “cities” and are
rolled up to “countries”. Aggregations performed on cities that sum of the
items of cities.
1.3.2.
Drill
– Down
Drill – Down is the reverse operation
of roll – up because here we go from higher form to lower form.
The concept of Hierarchy was “Day
> Month > Quarter > Year”, and here same is happening as quarter have
been divided into months that is nothing but reverse hierarchy. So the
aggregate function has been divided according to months.
1.3.3.
Slice
and Dice
Slice is an
action performed when you want one slice of information. For example we have
data cube where time is in quarters is a dimension and cities as one dimension
and items as another dimension. So if want data cube consisting of items and
locations in quarter 1.
Here Slicing has been done for time
Q1 for all items and locations.
Dice is
another sort of action performed when we want a particular block of data it can
more than two dimensions. For example if we require small data cube which has
condition that time dimensions to be Q1 and Q2, Locations as Toronto and
Vancouver and moreover items to be Mobile and Modem
It is a kind of Sub Data Cube. Sub
Data Cube derived from a data cube.
1.3.4.
Pivot
Pivot means rotation of the table. So
data inside data cube will be rotated along the rotational axes just to provide
alternate presentation of data.
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