Data Handling and Business Intelligence

Data Handling And Business
Intelligence

Contents
Contents...........................................................................................................................................2
INTRODUCTION...........................................................................................................................1
MAIN BODY..................................................................................................................................1
PART 1............................................................................................................................................1
Current trends in data warehousing, business intelligence and data mining...............................1
Evaluating the use of Excel for pre-processing the data, analysing the data and visualising the
data...............................................................................................................................................2
PART 2............................................................................................................................................8
2.1 Workings of Weka.................................................................................................................8
2.2 Explain the most common methods of data mining which can be used by organization....11
2.3 Discusses the advantage or disadvantage of Weka tool......................................................12
CONCLUSION..............................................................................................................................13
REFERENCES..............................................................................................................................15

INTRODUCTION
Data handling involves the gathering, processing data, evaluating data and eventually
displaying data with graphs or diagrams. The creation of information comes to us quite naturally.
They send a number to anyone who asks them and use accordingly (Ahsan and Bais,
2018). Business Intelligence is a collection of methods, systems, and innovations that turn raw
data into usable information that motivate efficient business activities. It's a scripting language
that transforms data in knowledge and intelligence that is admissible. They cover the broadest
possible fields such as marketing, accounting, economics, technology, computer science,
anthropology, art history, medical science and biology where they can use data handling or
business intelligence techniques. This report based of data analysis of given information and
some common data mining tools which are used by organizations. In addition, discuss the
advantage or disadvantage of WEKA tool with support of database argument.
MAIN BODY
PART 1
Current trends in data warehousing, business intelligence and data mining
The concepts of data warehousing, business intelligence and data mining are related to
each other which helps modern business organisations to collect, store and classify data so that it
can be analysed in such a way that beneficial insights for business can be gained and suitable
decisions can be made. Data warehousing is a process which involves storing the large data in a
secured manner so that it can be used in future (Mohammed, Naugler and Far, 2015). For various
organisations, their data is their asset due to which it becomes even more important to protect
their data from theft. There are various current trend which are enhances the practice of data
warehousing. These trends are increased enablement of self service data access using cloud
services. This current trend provides the suitability to the data owner to access the data whenever
it is required from any digital electronic device. Other current trends for data warehousing are
growth of NoSQL Adoption and Big Data Analytics in the Cloud.
Business intelligence is the combinations of all the technologies which are used by
business organisations to collect, integrate, analyse and present their business information.
Among the various current trends in BI, the most influential is self service BI and analytics.
According to this technology, organisations which are of small scale can use business
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intelligence tools and techniques by themselves and do not require external assistance. This trend
is focused to reduce the BI expenses of small scale organisation which does not own large data.
Other current trends in this field are big data innovation through social media which develop
customer analytics and text analytics which enables business to interpret Social Media Sentiment
(Mitrovic, 2020).
Data mining is the procedure in which an individual can mine the pre existing data by
using BI tools to generate hidden and analytic information from that data. Current trends in this
field are visual data mining, enhancement of a standardised language for data mining and
integration of data mining with data warehousing (Imhoff and White, 2011).
Evaluating the use of Excel for pre-processing the data, analysing the data and visualising the
data
Microsoft Excel is a software application which helps in recording and analysing
numerical information so that numerical data can provide information in a much more
understandable way. This software application is used for Superstore which is facing decline in
their sales and profits over the years.
Data pre processing
The data set of superstore is first pre processed using Excel. Data pre processing is a
technique which helps in cleaning the data so that it can be analysed without any error. The first
step which is taken to pre process the data is to find the missing values. By the shortcut key of
Shift + F4, all the missing values are first identified and then they are filled as the average of
their column. Secondly, in order to transform the data, all the numeric amount values are
formatted to 2 decimal points in order to bring familiarity. Then in last step of data pre
processing, the data set of superstore is reduced to a certain level using Pivot tables. In the pivot
table only those variables are selected which can impact the profit or sales of superstore.
Data analysis and visualisation
Once the data is pre processed, it is important to analyse it in such a way that it can fulfil
the aim of identifying the reasons due to which sales and profit of this company are decreasing
(Macaulay, Sekharan and Wang, 2017). For analysing, first all the numerical variables are
summed together according to their year using the Excel function of “=SUM()”. By using this
function sales, profit, discount, shipping cost, unit price and order quantity are summed on the
basis of 4 year 2009, 2010, 2011 and 2012. And then respective graphs are also developed.
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