Data Handling and Business Intelligence

Data handling and business Intelligence

Table of Contents
INTRODUCTION...........................................................................................................................2
PART 1............................................................................................................................................2
Describing the current trend in data warehousing, business intelligence and data mining.........2
Presenting the sales and profit over the years..............................................................................3
Evaluating the use of excel for pre- processing the data, analyzing the data..............................4
PART 2............................................................................................................................................6
2.1 Providing the conjunction with Weka through an example...................................................6
2.2 Presenting the most common data mining methods used in business...................................8
2.3 Advantages and disadvantages of Weka over excel............................................................10
CONCLUSION..............................................................................................................................10
REFERENCES..............................................................................................................................12

INTRODUCTION
Business intelligence are those methods which are comply with advance technology
which actually convert raw data into a proper information in order to generate better sales for a
business. While on the other side, data handling is that process which makes sure that research
information is stored, archived and disposed off in safe manner to make sure that proper
conclusion is generated. Further, the current report is based upon the case study and provides the
importance of using Weka that helps to generate the better results. In the same way, the present
report will describe the current trends of advance technology such that Data warehousing,
business intelligence and data mining. Further, shows the decline in sales and profit through a
given data set and through an example, it also shows the conjunction with Weka. Lastly it
provide common data methods used in a business with a real world.
PART 1
Describing the current trend in data warehousing, business intelligence and data mining
In the modern era of digitalization, most of the company uses advance technology for
smoothing their business operations. In the same way, there are varieties of advance techniques
available in the market through which company run their overall operations and some of them
are as mention below:
Data Warehousing: A Data warehousing is a subject- oriented, integrated collection of
data which support management decision making process. Generally it is used for analytical
purpose and business reporting, therefore, it is a store historical data that is integrating by copies
of transaction from a disparate source (Furtado, 2020). Hence, with this advance technique,
business use real time data feeds for the report which uses the most current and integrated
information. Such that Redshift is the most popular cloud services tool from web services.
Business Intelligence: It is a process or collection of architectures and technologies who
help business to convert the input into output. This is actually used in business to help the
corporate executives, business managers and other operational workers in order to make the
work in better manner (Cheng, Zhong and Cao, 2020). On the other side, most of the company

uses business intelligence for cost cutting purpose as well as determine the new business
opportunity so that company will take better action accordingly. In order to run the business in
better manner, companies must have a skilled labor workforce and IT specialist who must
possess SQL programming, Problem solving techniques etc.
Data Mining: It is the process which is used by the companies in order to turn the raw
data into useful information. Thus, it is a process of findings pattern as well as correlations
within large data sets for predicts outcomes. Its main goal is to extract information from a data
set and also transform the information into a structural manner (Roiger, 2017). Thus, through this
software, most of the companies uses more about their customers in order to develop more
effective marketing strategies which in turn assist to increases sales and decrease cost as well.
Thus, it is consider one of the most important advance technique that is used by most of the
company to remain viable and top in competition.
Presenting the sales and profit over the years
Assessment of sales & profitability aspect in accordance with customer segment and product
category
Sum of Sales Sum of Profit
Total
Sum of
Sales
Total
Sum of
Profit
Customer
segment /
product category
Office
Suppli
es
Tech
nolog
y
Furni
ture
Office
Suppli
es
Tech
nolog
y
Fur
nitu
re
Small business
760009
.83
1126
714.3
24
9015
96.83
6
105306
.11
1816
84.41
2871
7.49
2788320.
99
315708.0
1
Consumer
691382
.23
1243
421.6
38
1128
807.2
14
88532.
29
1566
99.39
4272
8.26
3063611.
082
287959.9
4
Corporate
134131
5.63
2294
748.6
74
1862
840.5
74
203037
.38
3747
00.54
2200
8.08
5498904.
878 599746
Home Office
960054
.41
1319
363.5
47
1285
345.9
18
121145
.65
1732
29.18
2397
9.2
3564763.
875
318354.0
3