Data Handling and Business Intelligence

DATA HANDLING AND
BUSINESS INTELLIGENCE

Contents
INTRODUCTION...........................................................................................................................1
Evaluating the use of Excel for pre-processing, analysing and visualising the data using
Superstore data and determining the decline in sales/profits over the years...............................1
2.1 Workings of WEKA..............................................................................................................7
2.2 Common data mining methods that can be used in business with real world example.......11
2.3 Advantage / disadvantage of Weka over Excel...................................................................12
CONCLUSION..............................................................................................................................13
REFERENCES..............................................................................................................................14

INTRODUCTION
Data handling and business intelligence are the concepts which allow business organisations
to collect and store their data so that it can be analysed and used for decision making process
(Hertrich and Mayrhofer, 2016). The main aim of this report is to build an understanding of
applying various analytic software which helps in a business organisation to mine their data in
order to extract meaningful information. In this report, software applications of Microsoft Excel
and WEKA are used in order to analyse the superstore and audidealership datasets. In the first
section of the report, the process of pre processing, analysing and visualising the data is
evaluated along with discussing upon current trends in data warehousing and mining.
In the second section of this report, clustering of audidealership data has been done along
with discussing various common methods of data mining. At last in this report, merits and
demerits of WEKA are analysed over Excel.
PART 1
Evaluating the use of Excel for pre-processing, analysing and visualising the data using
Superstore data and determining the decline in sales/profits over the years
Microsoft Excel is a computer application which allows its users to perform various
functions such as data warehousing and data mining. These functions are so popular in market
due to their affordability and suitability for businesses. There are various current trends in the
field of data warehousing, business intelligence and data mining which are analysed below:
In memory data base management system – This is the most influential current trend which
used by almost every organisation having big data. This management system allows its users to
record big data having complex variables. This trend removes the issue of memory restrictions.
System as a Software (SaaS) – Another current trend in the field of business intelligence is
SaaS. This current trend is an innovative technology which allows it users to access their data
base information for any digital device. This trend removes the restrictions of geographical
boundaries (Arganda-Carreras and et. al., 2017).
Web based Visualisation – This trend helps its users to mine the existing data set by using
visual tools such as tables, graphs and charts. By this technology, a data can be presented in such
a way that it can be understood by everyone. This issue removes the restriction of ineffective
communication and presentation.
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