Data Handling and Business Intelligence

Data Handling and Business
Intelligence

INTRODUCTION...........................................................................................................................3
PART 1............................................................................................................................................3
Describing the current trend in Data Warehousing, business intelligence and data mining.......3
Determining the decline in sales and profit over the years..........................................................4
Evaluate the use of excel for pre- processing the data and its visualizing the data.....................7
PART 2..........................................................................................................................................10
2.1 Describing the conjunction with Weka through an example...............................................10
2.2 Common data mining methods that can be used in business with real world examples.....12
2.3 Stating advantages and disadvantages of the WEKA over the excel..................................13
REFERENCES..............................................................................................................................15

INTRODUCTION
Data Handling is the process which is helps to make sure that research data is stored and
archived in a secure manner during and after the conclusion of every research. Therefore, in the
same manner, the current study will help to analyses the data which is already provided and
enhance the overall knowledge as well. Further, it is the scripting language which is also used in
order to transform the data in a knowledge and intelligence. Study will present the current trend
in data warehousing, business intelligence and data mining. Further, it will evaluate the use of
excel for pre- processing the data, analyzing the data through the figures and tables. In part-II,
report will describe working with Weka and then analyze the most common methods of data
which are used by the firm. Lastly, it will analyze the advantage and disadvantage of Weka tool
PART 1
Describing the current trend in Data Warehousing, business intelligence and data mining
Data mining, Business intelligence and data Warehousing are used by most of the
companies in order to gain high competitive advantage over a business. So, the current trends of
these three concepts are as mention below:
Data Warehousing: One of the finest trend which is run from 2019 onward for the
company. It means that a warehouse that is especially constructed by integrating the data from a
multiple heterogeneous sources which support the analytical reporting, structure and ad hoc
queries as well as help the company to take better decision (Déraspe and et.al., 2016). Basically
it is used for analytical purpose as well as for business reporting where a range of data is put in
consolidated manner that helps to provide solution.
Business Intelligence: This is refer to the technology and application which is used for
collection, integration analysis and presentation of business information. Further, its main
purpose is to provide support the business decision making (Larson and Chang, 2016). For
example, business intelligence technologies mainly includes the data warehouse and data
discovery tools in order to create a big data for the company which help to make better decision
and provide immediate solutions as well.

Data Mining: Another biggest trend of this modern era which help top companies to turn
raw data into an useful information. Such that by using the software where its pattern is changes
in large batches of information so that business may learn much about the customers (Tan,
Steinbach and Kumar, 2016). Through this, many company also uses the best marketing
strategies which help to increase the sales as well as decrease cost. Therefore, another company
used this technology for manufacturing engineering, CRM and fraud detection. Overall, this
technique will help a business to increase the sales and enhance the overall financial performance
of a business.
Determining the decline in sales and profit over the years
Sales
Province /
region
Atlan
tic
North
Carolin
a
Northwest
Territories
Onta
rio
Prari
e
Queb
ec West
Yuk
on
Gran
d
Total
Alberta
1704
791.4
9
17047
91.49
British
Columbia
1892
757.7
8
18927
57.78
Dawson
4853
34.2
8
48533
4.28
Elon
116376.
48
11637
6.48
Georgina
2530
83.35
25308
3.35
Hanover
9677
84.21
96778
4.2135
Manitoba
1372
848.7
8
13728
48.78
New
Brunswick
68421
1.523
5
68421
1.52
Newfound
land
10292
4.07
10292
4.07
Northwest 83817.75 83817.