Data Handling and Business Intelligence

DATA HANDLING AND
BUSINESS INTELLIGENCE

Contents
INTRODUCTION...........................................................................................................................1
MAIN BODY..................................................................................................................................1
PART 1............................................................................................................................................1
Current trends in data warehousing, business intelligence and data mining...............................1
Determining the decline in sales/profits over the years by evaluating the use of Excel for pre-
processing the data, analysing the data and visualising the data.................................................2
PART 2............................................................................................................................................7
2.1 Clustering using Weka...........................................................................................................7
2.2 Explain the most common methods of data mining which can be used by organization......9
2.3 Discusses the advantage or disadvantage of Weka tool over Microsoft Excel...................10
CONCLUSION..............................................................................................................................11
REFERENCES..............................................................................................................................12

INTRODUCTION
Data handling is the set of activities which helps an organisation to consider their data as
their assets and make effective and informed decisions using that data. This procedure includes
various activities such as data collection, data mining, classification and interpretation using
various software applications (Choi, Chan and Yue, 2016). The main aim of this report is to
build an understanding regarding current trends in the field of data handling and business
intelligence and developing a systematic understanding of predictive analytic software.
This report is divided into two sections; in first section, the software application of
Microsoft Excel will be used to interpret the data of superstore and then determine the reasons
behind decline in sales or profit. In the second section of this report, the data of audidealership
will be used with the help of Weka to develop clusters in the data set and will find emerging
patterns of customers.
MAIN BODY
PART 1
Current trends in data warehousing, business intelligence and data mining
Data warehousing is the concept of data handling in which data is being stored considering
the factors of security and availability (Höpken and et.al., 2015). For large organisation or for
companies having large transactions history like superstore has big data which is hard to store
using hard disk as it does not assist in quick data availability. In order to bridge this problem,
various current trends in market are emerging which helps in storing the large data sets with full
security and quick availability. These current trends are Hardware clustering and green data
centres which allows business organisations to store their big data and use it whenever it is
required using their mobile devices by enabling cloud services. XML data streams and agile
development are also few current trends in data warehousing.
Business intelligence is the concept which includes tools of integration and analysis of
data. Business intelligence tools help business organisations to strategically interpret their data
by identifying patterns and trends in the data in order to make informed and effective operational
decisions. The tools of BI uses a set process of Extract, transform and load. Current trends in the
field of BI are virtualisation, open source software, and database management system and
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