Data Handling and Business Intelligence

DATA HANDLING AND
BUSINESS INTELLIGENCE

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................1
PART 1............................................................................................................................................1
By using data set of superstores analyse profit and sales over years and analyse it by using
Excel for pre- processing of data, also analyse and visualize the data........................................1
Demonstration of ways in which data can be practically analysed using Excel functions such
as Lookup, Pivot table, graphs and charts...................................................................................6
PART 2............................................................................................................................................9
2.1 By using audidealership.csv file show conjunction with Weka with the example of
clustering......................................................................................................................................9
2.2 explain data mining method that can be used in real business............................................11
2.3 Discuss advantage and disadvantage of weka over excel....................................................12
CONCLUSION..............................................................................................................................14
REREFENCES..............................................................................................................................15

INTRODUCTION
Data mining is a kind of process which is used by organizations for data analysis, finding
pattern within large amount of data set and for various other kind of purposes. It has become one
of the most important part of an organization as it helps them in decision making, predict future
sales and for many other purposes (Unat and et. al., 2016). Data handing and business
intelligence methods are majorly used for analysing and extracting information from large
amount of data so that new data can be used for bringing changes within business strategies in
order to enhance revenue and profitability of organizations. Today it has become one of the most
important and effective part of an organization and is used in different ways in many industries
but mostly Business intelligence is used. Business intelligence is a kind of process, method or
technology that helps an organization to use, convert, analyse and extract meaningful data from
raw data which further helps an organization to expand their business and increase profitability.
For retail sector organizations it is extremely important for they need to develop strategies by
predicting their future sales on the basis of their current sales. This assignment will focus on
analysis of superstore data in order to identify and analyse sales and profit of the organization.
This assignment will also focus on conjunction in Weka Software of audidealership data with the
help of clustering and lastly advantages and disadvantage of Weka over Excel.
PART 1
By using data set of superstores analyse profit and sales over years and analyse it by using Excel
for pre- processing of data, also analyse and visualize the data
Data mining is majorly used for data handing and conducting business intelligence
operations. There are various kinds of methods that are used for data mining that comes under
data handing and business intelligence such as database systems, machine learning intersection
and statistics and many more. In order to transform data or extract useful information from it
there are many kinds of software’s or tools that can be used by organizations which helps
organizations to bring changes within their current strategies. Excel is one of those tools which is
based upon Data mining technique (Sajitha, Minimol and Mini, 2019). Mostly Excel is used by
organizations for financial calculation like calculation of their profit and sales, forecasting or
predicting future sales and for many other purposes. It is one of the most common data mining
tool which is used by organizations as it has various kinds of inbuilt functions that can be used
by organizations for data analysis. It can be used by organization to study many years past data
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and analyse their sales and profitability in many ways. Not only this, Excel provides various
kinds of options for creating a pivot table, creating graphs and many more. It also has inbuilt
formula to search a value in a large data set as well (Zelinka and et. al., 2018). Excel is majorly
used for organizing and arranging the data in such a manner that it can used for further analysis.
In order to analysis sales and overall profit of the provided data Excel can be used.
 Below table will explain Average sales and Average profit of Superstore from 2009 to 2012
Row Labels
Average of
Sales
Average of
Profit
Furniture 3003.82282 68.11660673
2009 3287.21367 137.9565402
2010 2846.632764 21.35772727
2011 3035.062388 120.6278708
2012 2834.316565 -10.02715311
Office Supplies 814.0481779 112.3690738
2009 885.7139778 151.9643028
2010 778.0854274 100.9771282
2011 716.172473 78.20144784
2012 871.9747368 116.7143313
Technology 2897.941008 429.2075157
2009 3145.703293 359.7878373
2010 2631.278114 447.037081
2011 2916.463917 519.0770085
2012 2895.826493 402.5972762
Grand Total 1775.878179 181.1844243
Figure 1 Average sales and Average profit from 2009 year to 2012 year
Data interpretation: Average sales and average profit of super store can be calculated with the
help of pivot table and pivot graph. From the above graph it can be interpreted that average sales
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