Today in our session we studied about a new function called OLAP Cube,
it stands for Online Analysis
Processing.
OLAP is software that is designed to allow users to navigate, retrieve
and present business or organisational data.
Advantages of OLAP:
·
The data is stored in a ready reporting format. There is no need to
write complex queries.
·
Fully interactive drag and drop sessions is usually provided too rather
than having to write a complex report that might take several hours.
·
The data is categorized into dimensions and the software used is
designed to work with numeric data where we can usually need to add up,
consolidate or sum the data such as sales per quarter, sales per year per
product.
·
Dimensions could be customers, products, regions, countries, and the
time dimension e.g. weekly, monthly, quarterly and annually. A solution usually
has many dimensions usually three or more and could be termed multidimensional.
OLAP Cube:
An OLAP cube is an array of data that is
understood in terms of its 0 or more dimensions. The data has a different
architecture from other forms of data storage.
There are two components – firstly the data built into a cube that
houses the multidimensional data and secondly access tools to build and
manipulate the data. The ability of OLAP cubes is to facilitate multifaceted
data analysis in response to complex business queries; it maintains some degree
of usefulness, as businesses accumulate increasingly large data volumes of
increasing complexity. Since OLAP cubes can be made up of more than three
dimensions (hypercube), in-depth analysis is enabled, allowing users to gain
comprehensive and valuable business insights. Virtually unlimited numbers of
dimensions can be added to the data structure (OLAP cube), allowing for
detailed data analysis. The data sets can be viewed from different angles or
pivots; a process if involving large data volumes, would take hours on a
relational database.
A cube is a specialized data store designed to handle multidimensional
data and the aggregated numerical data.
Some of the features of OLAP Cube are:
·
Consolidation – we can roll up or
sum the data to higher levels of abstraction e.g. local sales office, regional
office, and national office and so on.
·
Drill Down – we can navigate
down or up through the data with a few clicks.
·
Calculations – we can create
derived calculations such as profit margins, yields etc.
·
Pivot tables – we can also readily
view the data from different points or perspectives.
This is the analysis that what we did in class today. We divided the
data among Summary variable and Grouping variable. And we got the following
tables. In the OLAP Cube table by selecting different service provider, the
gender, connection type, internet we get the mean of all the selected data.
Case
Processing Summary
|
Cases
|
|||||
Included |
Excluded
|
Total
|
||||
N |
Percent
|
N
|
Percent
|
N
|
Percent
|
|
Usage
period In Months * Name of current
service provider * Connection Type *
Internet * Same service used by my circle * Gender of respondent
|
206
|
100.0%
|
0
|
.0%
|
206
|
100.0%
|
Monthly
expenditure on phone * Name of current
service provider * Connection Type *
Internet * Same service used by my circle * Gender of respondent
|
206
|
100.0%
|
0
|
.0%
|
206
|
100.0%
|
OLAP
Cubes
Name of current service
provider: Total
Connection Type: Total
Internet: Total
Same service used by my
circle: Total
Gender of respondent: Total
|
Sum
|
N
|
Mean
|
Std. Deviation
|
% of Total Sum
|
% of Total N
|
Usage
period In Months
|
2569
|
206
|
12.47
|
9.084
|
100.0%
|
100.0%
|
Monthly
expenditure on phone
|
72633.00
|
206
|
352.5874
|
184.64170
|
100.0%
|
100.0%
|
By:
Annie Basumatary
11020841070
Group G
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