Data Mining Methods for Business

DATA HANDLING
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CONTENTS
INTRODUCTION...........................................................................................................................3
PART 1............................................................................................................................................3
Determine the sales and profit over years and evaluate the use of Excel for pre-processing the
data...............................................................................................................................................3
Demonstrate that how it can practically with use of Excel function such as if, Lookup, Pivot
table, charts and graphs................................................................................................................6
PART 2............................................................................................................................................9
Common types of data mining methods that can be used within a business...............................9
Advantages and disadvantages of Weka over Excel.................................................................12
CONCLUSION..............................................................................................................................13
REFERENCES..............................................................................................................................14
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INTRODUCTION
Data mining is based on the process of finding the patterns, correlations and anomalies
within large data set. In order to predict accurate result or outcome. The data mining process will
support for marketing assistant to increase the revenue of information, cut cost while improving
the customer relationship. Afterwards, it will reduce the various risks and so on. Data mining is
consider as important factor which consider the large volume of data or information. In another
word, data mining is exploring and analyzing the large amount of data which easily discover
meaningful pattern, rules and facts. It will consider as a discipline under specific data science
and offer from predictive analytics. Furthermore, it will described the sales information while
primary aim is to predict future result or outcome. In additional, data mining is an appropriate
technique to build machine learning model that power in term of artificial intelligence.
PART 1
Determine the sales and profit over years and evaluate the use of Excel for pre-processing the
data.
It is based on the data mining technique always support for calculating the sales and
profit over years. It provides a brief idea about the critical success of modern data drive
organization. It is powerful tool that transform enterprise, however, it is also implementing the
process to meet the specific need of business. Sometimes, it is frequently stand in the better way
to successful process data mining.
Excel is consider as standard for spreadsheet software that enable to calculate the budget,
financial forecasting and various data entries. The primary function is to organise large amount
of data or information in proper manner. Furthermore, it can easily analyse the data to create
graphs, charts. In order to represent in visualise manner.
Row Labels Average of Profit Sum of Sales
Furniture 68.11660673 5178590.542
2009 140.1369955 1469508.194
2010 20.65391403 1250043.046
2011 115.326226 1258336.514
2012 -5.173357143 1200702.788
Office Supplies 112.3690738 3752762.1
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2009 153.4285381 1031244.56
2010 97.14263473 885095.79
2011 80.42802855 816902.13
2012 117.6447423 1019519.62
Technology 429.2075157 5984248.182
2009 337.0125974 1668572.052
2010 474.5130402 1416503.546
2011 518.2162105 1380213.417
2012 398.3725568 1518959.168
Grand Total 181.1844243 14915600.82
Figure 1
Data Interpretation
By using excel, it can be calculating the Average profit and sum of sales. It can be
identified the profit and sales of furniture. Furthermore, it also identified the average profit in
year wise so that it become easier to identify the accurate information of furniture.
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