Data Handling And Business Intelligence Assessment 2

DATA HANDLING AND
BUSINESS INTELLIGENCE

TABLE OF CONTENTS
PART 1............................................................................................................................................1
Use of Excel for pre-processing the data, data analysis and data visualization. Determination
of decline in sales and profit using chart and graphs...................................................................1
PART 2............................................................................................................................................5
2.1 Conjunction with SPSS with screenshots and findings of K-means.....................................6
2.2 Most common data mining methods used in business with real world examples...............11
2.3 Discuss advantages/disadvantages of SPSS over Excel with theoretical arguments and
practical arguments....................................................................................................................12
REFERENCES..............................................................................................................................13

PART 1
Use of Excel for pre-processing the data, data analysis and data visualization. Determination of
decline in sales and profit using chart and graphs
Excel is one of the most important tool which is required to be used by organizations as it
helps in analysing and interpreting raw data into meaningful data that can be used by
organizations for various purposes such as decision making etc. Excel can be used for evaluating
raw information or data so that it can be processed easily and can be understood easily by its
users so that required and important information can be extracted from it (Martino, 2019). One of
the most important purpose because of which Excel is being used by organizations is pre-
processing in which data or information is entered into Excel in a manner in which it can be
understood properly. Excel provides rows and column in which data can be entered in such a
manner that its users can understand and use this data easily. Pre-processing data also help in
extracting important and useful part of Excel that can further help in extracting or evaluating any
kind of important information and gain other important information associated with it.
When pre-processing of data is done then in order to evaluate and extract important data
analysis of the data is done. Analysis of data is another important feature of excel (Kajáti, Miškuf
and Papcun, 2017). For analysis of data stored within Excel, Excel provides various kinds of in-
built formulas that can be used by users for analysis of data. Excel provides various kinds of
inbuilt features such as calculation of average, mean, mode, searching for value, etc. These
features can be used by users as per their convenience, requirement and use. But in order to make
analysis more presentable and easy to understand Excel provide visualization of data feature as
well. Using this feature, users can create graph, charts, histograms of their analysed data so that
extracted or analysed results can be understood in more accurate and effective manner.
For analysing and visualizing data in Excel, Excel provide various other features for
making extraction and interpretation of data more easy and one of those feature is Pivot tables
and charts (Becker and Gould, 2019). This feature of Excel help users in identifying and
selecting the data that they want to analyse and save that data in Pivot table so that users can
mold that data in any way they want, present any data they want, bring chances within data in
many manner users want without affecting actual an final data.
Excel is one of the most effective tool when it comes to pre-processing of data but has
some drawbacks as well such as in Excel values that are left bank can work as a barrier when it
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comes to analysis of data, any value in pre-processing of data is entered wrong them all the
analysis can go wrong and there is no feature in excel that can help in understanding that value
entered is wrong (Kajáti, Miškuf and Papcun, 2017). But despite of this, Excel is one of the best
and most appropriate or accurate tool that can be used for bingers when it comes to data storage,
analysis and visualization.
For analysing superstore data for analysing decline in overall sales and profit of store
over years, analysis of data using MS Excel will be done. In this analysis of data stored in Excel
will be done using in built Excel functions and using those functions and graphs in Excel
analysis of superstore data will be done and in order to understand results more clearly chart or
graph of those data will be developed for visualization of data analysed in order to identify
(Kajáti, Miškuf and Papcun, 2017). Below step by step process will clearly help in understand
decline in sales/ profit year by year in an accurate manner.
 First step is to apply filter option from in built functions of Excel on first row of dataset, so
that relevant data can be selected and analysed in an appropriate manner.
 Then in order to select appropriate sales data further filter can be applied on the data as per
the requirement for selecting year by year data, in order analyse and evaluate sales and profit
data year by year from huge set of data.
 After selecting sales and profit data individually for 2009, 2010, 2011, 2012, sum formula
can be applied to sales and profit data individually. This step can be repeated for all the four
years and for both sales and profit. This will provide appropriate data of sales year by year
and of profit year y year. Then in order to analyse this data visual representation of data will
be done by developing chart of analysed data so that appropriate information can be observed
and relationship between sales and profit can be analysed and evaluated.
 After development of charts and graphs of both sales and profit, both the visualized data will
be analysed. For the below data it has been analysed that there is relationship between profit
and sales i.e. increase of decrease in sales data has directly impacted and resulted in increase
or decrease in profitability data. From the graph it has been identified that sales of superstore
from 2009 to 2010 has reduced and result profitability of superstore has also reduced from
2009 to 2010. So in order to increase profitability of store overall sales of superstore can be
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