Data Handling and Business Intelligence

Data handling and business
Intelligence
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Contents
INTRODUCTION...........................................................................................................................3
PART 1............................................................................................................................................3
Describe the sales and profit over years and evaluate the use of Excel for pre-processing
information..................................................................................................................................3
Discuss about the concept that how practically used Excel function such as Pivot, if, Lookup,
Pivot table and charts...................................................................................................................6
PART 2............................................................................................................................................9
Discuss about the different type of data mining method and used for business purpose............9
CONCLUSION..............................................................................................................................17
REFERENCES..............................................................................................................................19
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INTRODUCTION
Data mining is a method or technique for analysing large amount of data, pattern and also
developed correlation between them. It is useful for predicating the accurate result or outcome. It
is consider as process that will support for estimating the revenue of information, cutting cost/
price. In order to improve the customer relationship. Data mining is conceptual based technique
that always support for analysing and exploring the data in order to generate accurate result or
outcome. The report will describe about the overall sales report whereas marketing assistant
track or record full details. Furthermore, the documentation will describe about the sales
information and implement Weka software to find out specific outcome. This technique will
consider an efficient that build a machine learning model and handle the processes in proper
manner.
PART 1
Describe the sales and profit over years and evaluate the use of Excel for pre-processing
information.
Data pre-processing: It is important phase in the data mining process where they can
process various data or information through machine learning. In order to gather large amount of
data or information. It can be analysing data which carefully screened for problem or issue. It can
be produced misleading result or outcome.
Weka Software: It is based on the data mining tool that provide facility to visualise data
which contain large collection of machine learning algorithms. It is an open source software that
issue under General public License (Drushku and et al 2019). In another way, it can be said that
conceptual process of unfolding pattern in large data set which will support for making right
business decision. In order to design an effective strategies for organization growth and
development (Mitrovic, 2020). Weka primarily expects the data file to be collected in the
attribute relation format so that it can easily convert into useful information. Weka platform
provide the different data mining technique such as clustering, filtering and classification. Main
feature of Weka is data pre-processing, prediction and clustering.
MS Excel: it is a type of spreadsheet program that allows one to enter numerical value into
columns, rows. Sometimes, it can be used numerical entries such as graphs, calculations,
estimation total revenue and statistical analysis (Isazad Mashinchi Ojo and Sullivan, 2019). The
spreadsheet is the most efficient that useful for student interactive activities, interactive lectures
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and instructor use for developing the materials. Excel is consider as calculator which help for
explore the mathematical equation and tell about the real world works for specific input
condition or range of possible values.
In this tables, it can be collected information about the particular product where how
much profit they can gain and total sales. In order to calculate the data year wise and also record
the profit. In this way, it help for increasing the capabilities to make better decision in future and
also gained more profitability in marketplace. These information will be collected through Excel
that provide the information or data and their significant result.
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
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
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