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...................................................................................4
PART 2............................................................................................................................................8
By using audidealership.csv file show conjunction with Weka with the example of clustering.8
Explanation of commonly used data mining methods that can be used in business. Explain
them with real time example......................................................................................................11
Advantages and disadvantages of Weka....................................................................................14
CONCLUSION..............................................................................................................................15
REREFENCES..............................................................................................................................16

INTRODUCTION
Data Mining can be defined as a process through which pattern within large data sets are
discovered. It involves various kinds of methods at machine learning intersection, database
systems and statistics (Homocianu and Airinei, 2017). It can also be defined as a practise of
examining large number of pre- existing databases so that new information can be generated.
Today many organizations focus on data mining for data handing and extraction of new and
important data. For this business uses business Intelligence so that specific data can be identified
that can further be used for taking effective decisions. Business Intelligence can be defined as a
set of process, technologies, architecture that helps in converting raw data into meaningful data
which is fruitful in driving overall profitability of business. There are various kinds of software’s
that can be used by organizations that can be used for BI and transform data into actionable
knowledge and intelligence. It is one of the most important for retail sector organizations as it
helps them to analyse large volume of data and take appropriate and effective decisions so that
they can enhance their relationship with their customers and increase their overall profitability.
This assignment will lay emphasis on Analysis of superstore and audileadership data so that the
given data can be analysed and overall sales and profit of the organization can be identified other
than this different kinds of data mining methods will be explained with advantages and
disadvantage of Weka software will be discussed in this assignment.
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
There are various kinds of techniques, methods and formulas in Excel that can be used
for analysing and calculating profit and sales over years. It helps in evaluation of data so that
organizations can get a brief idea of their average profit and overall sales in last 4 to 5 years so
that this data can be used for further important decision making (Moro and et. al., 2020). Excel is
one of the most common software that can be used by organizations for calculations and analysis
of financial calculations, forecasting data and for various other purposes. Excel has various kinds
of inbuilt formulas that can be used for analysing the data and reaching to a conclusion. The
main and primary function of Excel is to organize all the information or data of the organization
in an appropriate manner. It is important to organize the data if formulas, techniques or methods
are required to be used for further analysis. Excel also provides an option of generating graphs or
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charts so that it becomes much easier for organizations to visualize their data and take
appropriate decisions accordingly. In order to analyse sales and profit of the organization over
years pivot table and graph method can be used.
Row Labels Sum of Sales
Average of
Profit
Furniture 5178590.542 68.11660673
2009 1472671.724 137.9565402
2010 1252518.416 21.35772727
2011 1268656.078 120.6278708
2012 1184744.324 -10.02715311
Office Supplies 3752762.1 112.3690738
2009 1035399.64 151.9643028
2010 910359.95 100.9771282
2011 796383.79 78.20144784
2012 1010618.72 116.7143313
Technology 5984248.182 429.2075157
2009 1701825.482 359.7878373
2010 1397208.679 447.037081
2011 1364905.113 519.0770085
2012 1520308.909 402.5972762
Grand Total 14915600.82 181.1844243
Figure 1 Average profit and sum of sales of last 4 years.
Data interpretation: Above graph has been made with the help of pivot table feature of Excel
with the help of which Average profit in last 4 years and overall sales in past 4 years have been
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