Data Handling: Analysis, Pre-processing, and Visualization

Data Handling
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Table of Contents
INTRODUCTION...........................................................................................................................3
PART 1............................................................................................................................................3
PART 2............................................................................................................................................8
2.1 Specific example of clustering...............................................................................................8
2.2 Data mining methods that are used in business...................................................................13
2.3 Pros and cons of using SPSS over Ms- Excel.....................................................................14
CONCLUSION..............................................................................................................................16
REFERENCES..............................................................................................................................17
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INTRODUCTION
Data set refers to collection of data and it consists of raw data. The businesses uses data in
order to obtain relevant outcomes from it (Chau and Phung, 2017). Then, decisions are taken on
basis of results obtained from it. In this data mining means process by which raw data is
transformed into useful info. This helps in gathering relevant info which is used by business.
There are many data mining techniques used. It depends in business needs. For example- Ms
Excel, SPSS, etc. are some tools for data mining. The data must be presented into graphs, tables,
etc. to present to audience.
The report will lay emphasis on analysing data of supermarket. Also, it will be explained
about data mining techniques and use of SPSS over excel.
PART 1
In this a data set is to be analysed of super store in order to find out decline in sales and
profits of store in all 4 years. Thus, for that MS excel will be used in which data will be analysed
and interpreted. Besides that, pivot tables will be used to analyse data in effective way. This is
because pivot table is easier to use and understand. It will also help in identifying pattern and
trend in sales and profits.
PIVOT TABLES
Year 2012
Interpretation- it is interpreted from data that in 2012 the avg sales from delivery truck was
5274.7 and from express air was 1312.5. In regular air mode of transport sales done was 1190.5.
Now, in terms of profit it delivery truck it was 137.5 and in express air was 218.6 and in regular
air profit was 160.4. Also, it is found that avg sales of 2012 from all three was 1767.9 and avg
profit was 162.9
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Year 2011
Interpretation- the table shows that in 2011 avg sales through delivery truck was 5674.5 and
by express air it is 1000.0 and regular is 1145.9. The avg profit obtained from truck is 351.9 and
express air is 114.9 and regular is 175.4. Furthermore, avg total sales is 1716.6 and profit is 190.
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Year 2010
Interpretation- the above table state that avg sale from delivery truck is 5042.8 from express
air is 1276.6 and by regular is 1091.5. Also, avg profit from truck is 240.9 and by express is
198.0 and via regular is 153.0. Along with that, total avg sales is 1662.8 and in avg profit is
170.4 in 2010.
Year 2009
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