Data Warehousing and Analytics: A Comprehensive Report

Desklib provides solved assignments and past papers to help students succeed.

Assignment 3

Table of Contents
Introduction.................................................................................................................................................3
Task1...........................................................................................................................................................3
1.1...............................................................................................................................................................3
1.2...............................................................................................................................................................7
1.3..............................................................................................................................................................10
1.4..............................................................................................................................................................11
Task2.........................................................................................................................................................14
2.1..............................................................................................................................................................14
2.2..............................................................................................................................................................15
2.3..............................................................................................................................................................21
Task3.........................................................................................................................................................24
3.1..............................................................................................................................................................24
3.2..............................................................................................................................................................24
3.3..............................................................................................................................................................25
3.4..............................................................................................................................................................26
3.5..............................................................................................................................................................27
Conclusion.................................................................................................................................................29
References.................................................................................................................................................29
Figure 1 EDA design.....................................................................................................................................4
Figure 2 Result of EDA.................................................................................................................................5
Figure 3 Bar Chart EDA................................................................................................................................6
Figure 4 Correlation Matrix Test................................................................................................................7
Figure 5 Decision Tree Model Process.........................................................................................................8
Figure 6 Local Repository Weather AUS......................................................................................................9
Figure 7 Decision Tree.................................................................................................................................9
Figure 8 Regression Process......................................................................................................................10
Figure 9 cross-validation process...............................................................................................................12
Figure 10 Cross-validation decision tree model.........................................................................................12
Figure 11 Accuracy logistic regression.......................................................................................................13
Figure 12 example set of the cross-validation of the logistic regression...................................................14
Figure 13 Data warehouse architecture....................................................................................................15
Figure 14 Data warehouse Architectural Design.......................................................................................17
Figure 15 result 3.1....................................................................................................................................24

Figure 16 result 3.2....................................................................................................................................25
Figure 17 result 3.3....................................................................................................................................26
Figure 18result 3.4.....................................................................................................................................27
Figure 19 result3.5 (a)................................................................................................................................28
Figure 20 result 3.5(b)...............................................................................................................................28

Introduction
In system, programming data warehousing is a term which is used for reporting and analytical
research having business intelligence as a core factor. It is some kind of large information
storage center called repository system contains a variety of information by obtaining from a
different type of online resource. This system has a number of the layer that plays an important
role in the development of the system from core rough data to cleanest data. The concept for
the development of warehouse system using a different type of tools and techniques has been
covered in this report. Detail analysis for tableau and Rapid Tool has also been considered.
Task1
1.1
The analytical analysis for the given data of weatherAUS.CSV is being processed using the Rapid
Minor analytical tool. There are several types of tool that could process the same kind of work
but Rapid Minor is one of the best and easy to use tools which didn’t require specific session for
training for the use or performing specific insightful data. The Rapid master provides extensive
knowledge to the nontechnical experts for analysis of data by processing several tasks with the
help of operators. Any required data files have been extracted from the database of system and
thus is being read with making use of CSV operator. Making use of some specific operators a
user can extract and prepare a graphical structure and make use in some different file.

Figure 1 EDA design
After running the EDA process result of the analytical research could be extracted and recorded.
The below-given diagram represents the result.
Figure 2 Result of EDA

Figure 3 Bar chart EDA
Correlation

Figure 4 Correlation Matrix Test
1.2
A decision process tree provides graphical representation for all possible decision in a given
condition. It seems like a decision tree because the first and starting box is single and having a
number of sub-branches for a solution. Using Rapid Miner tool a Decision Tree is being

developed. It is one of the easiest tool needed no expertise for use and offers an effective
solution.
Figure 5 Decision Tree Model Process
During the development of a decision tree, it is required to retrieve all important data from
given CSV namely eatherAUS.csv. After completion of that, it is required to set up the role of
variables of Rain and Date. On the basis of training data, a decision tree is being developed.
After running the process of decision making a decision tree will be generated. The decision
tree is much faster and easy to make use for making critical decisions.

Figure 6 Local Repository Weather AUS
Figure 7 Decision Tree
1.3
Here in this task, it is required to develop a logistic regression model on the basis of the given
data set. It is a common term especially used for predictive analysis and model design. Apart

from logistics, there is some certain extension available which quite complex than logistic. The
biggest advantage of using this is the preparation of a model using binary executable codes.
Figure 8 Regression Process
In the development of logistic regression process and development, all useful data set would be
extracted from the repository system. After extraction of whole data sets variables to show the
rain variable in CSV file in context to date has been plotted. Now as per requirement a
regression model on the basis of given data set is being developed on and once the
development is being completed a well-optimized model is created. It is quite an easier model
for any type of system user.

1.4
This is one of the best possible cross investigation analytical approaches allow for the
combination of decision tree and logistic regression completely check for overall performance.
In general passing of the system, object requires training for start and end. There is also some
subsets tasks also is being developed using given attributes. The most important use of cross
investigation testing is to have clear and accurate testing over the used mode.

Figure 9 cross-validation process
Figure 10 Cross-validation decision tree model