Data Warehousing and Business Intelligence for Environmental Analysis

This report focuses on utilizing Business Intelligence (BI) tools, specifically a dashboard, for environmental analysis and reporting. It examines energy consumption trends in the United States, the environmental impact of electricity, and applies both prescriptive and descriptive analytics to identify areas for improvement. The report includes a prototype BI application with a dashboard, showcasing key performance indicators and providing logical recommendations for enhancing environmental sustainability. The analysis covers aspects like energy consumption, temperature variations, and weather conditions to offer actionable insights for decision-making. The goal is to provide senior executives with the necessary information for meetings with the board, highlighting issues and potential solutions based on data-driven analysis. Students can explore similar solved assignments and past papers on Desklib.

Assignment 1: Business Intelligence and
Data Warehousing
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Executive Summary
The spot light of this research is on Business intelligence (BI) reporting solution or a
dashboard. BI is an information management tool, which is utilized for tracking the
metrics, KPIs, and other important data points that are appropriate for the business or
for any particular process. The data visualization in the dashboard simplifies the
complicated data sets. The research ensures to review and examine the environmental
issues. Subsequently, the scope of report is that the senior executive is interrogated for
making arrangements for the meeting with the board of association. Before, the
commencement of this meeting, the senior executive is required to present the
prescriptive and descriptive analysis reports. The analysis determines the issues to be
improved in the environment.

Table of Contents
1. Introduction........................................................................................................................................................... 1
1.1 Case Study........................................................................................................................................................ 1
1.2 Scope of the Solution...................................................................................................................................... 2
2. Energy Consumption........................................................................................................................................... 2
2.1 Impact of Electricity on Environment.............................................................................................................5
3. Selected Analytics................................................................................................................................................ 6
3.1 Prescriptive Analysis....................................................................................................................................... 7
3.2 Descriptive Analysis...................................................................................................................................... 10
4. Dashboad and its Explanation..........................................................................................................................12
4.1 Solution Overview.......................................................................................................................................... 14
4.2 Prototype of the Business Intelligence Application using Dashboard.....................................................14
5. Logical Recommendation to Improve the Environment.................................................................................16
6. Conclusion.......................................................................................................................................................... 18
References................................................................................................................................................................... 20

1. Introduction
This report projects on the business analytics project, for generating innovative
analytics solutions. The project will help the students to present their innovation and
creativity in applying SAP Business Object or Predictive Analytics, for designing useful
visualization solutions and to present the predictive models for various sorts of analytic
issues. Environmental issues is the discussed topic in this report, by using the business
Intelligence tool like, Dashboad. The important task of this report is to apply any of the
analytical tools for developing innovative analytics visualization solutions and predictive
models based on environment. For instance, water reduction, energy consumption,
climate change, greenhouse gas emission, carbon footprint, pollution dashboard and so
on.
The objective of this research is to have hands on experiences of using SAP
Analytics tools for exploring, extracting and analyzing the data of the enterprise.
Appropriate models will be drawn. Two different types of analysis such as Descriptive
analysis and Prescriptive analysis will be conducted in this report. The prototype of the
business intelligence will be designed for the application design. The key performance
indicators will be analyzed using the Dashboard, which will be created using an
appropriate tool. Depending on the BI analysis and gained insights with the help of data
set, logical recommendations will be made to improvise the environment. Justification
for the BI reporting solution/dashboard will be provided.
1.1 Case Study
This case study is related to environmental issues. The environmental issues can
be energy consumption, climate change, greenhouse gas emission, carbon footprint,
pollution dashboard, and so on. In this report the business Intelligence tool like,
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Dashboad is used for the help. The purpose is to improve visualization related to
analytics and to predict the data set depending on the environment. In this mainly water
reduction is concentrated.
1.2 Scope of the Solution
The senior executive is interrogated for making arrangements for the meeting
with the board of association. Before, the commencement of this meeting, the senior
executive is supposed to provide the prescriptive and descriptive analysis reports. The
meeting will talk on the accessibility of database information and what monitoring and
quick solutions can be supported for the encountered environmental issue. Therefore,
the proposed system must be capable of finding the issues which are important to be
noticed by the board members. Further, it needs analysis to act on the administration
part for improvements in the environment. Therefore, this report will help the company’s
senior executive for their meeting.
2. Energy Consumption
During 2000 to 2016, the United States of America's energy consumption has
increased. The year 2016 saw huge energy consumption, and has also resulted in high
consumption of natural gas and petroleum. Moreover, the industry sectors has
increased its electric power demands. ("U.S. energy consumption rose slightly in 2016
despite a significant decline in coal use", 2017).
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Figure: Energy consumption in the United States of America
The coal consumption has become low with 9% and has increased the renewable
energies like petroleum, nuclear fuel and natural gas. The highlight is that the United
States is largest energy consumer in the world.
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Figure: Information of Energy consumption, according to 2017 reports
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Figure: In 2016, Energy consumption (Dutton, 2018)
Figure: In 2016, Energy Generation ("About the U.S. Electricity System and its Impact
on the Environment", 2018)
2.1 Impact of Electricity on Environment
Though electricity is clean and is safe comparatively with other forms of energy,
the environment is affected due to the electricity generation and transmission. However,
every single electric power plants has environmental impact, especially the certain
power plants have higher impact. In the United States of America, the government has
passed certain laws which see to it that the impacts of electricity generation and
transmission are governed, to secure the environment. The Clean Air Act regulates the
emission of air pollutant emissions from several power plants. Additionally, the U.S.
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Environmental Protection Agency (EPA) is present for administrating the same act i.e.,
Clean Air Act. This act is standardized base in the emissions for the power plants via,
several programs like Acid Rain Program. The reduction of air pollutant emission has
decreased to a larger extent due to the stress on Clean Air Act, in the United States of
America.
The impact of power plants on the landscape is observed, where it determines
that all the power plants contain physical footprint (i.e., power plant’s location). Certain
power plants are relatively small because they are placed wither inside, on, or next to
the existing building, which makes the footprint small. Certain power plants which burn
solid fuels may have areas for storing the combustion ash. The power plants have large
structure, which alters the visual landscape i.e., as much as the structure is larger, there
are high possibilities that the power plant could have high impact on the visual
landscape. ("Electricity and the Environment - Energy Explained, Your Guide To
Understanding Energy - Energy Information Administration", 2018).
3. Selected Analytics
The Business Intelligence reporting solution or the dashboards are selected,
because it can help to map any data set and helps the users with the generation of
reports, as per their needs. The simple thing about this solution is the reports can be
generated with few mouse clicks. Even it is possible to go in-depth of the data for
detailed examination of the report. BI reporting is an effective solution which is flexible
and easy to use for differentiating with various dimensions of data that has to be
analyzed in different forms like, tabular, chart, pivot, reports comparison and so on. It
also provides several effective filters which could be applied for the analysis. Moreover,
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the reports of BI can even be automatically shared and emailed as Excel, CSV or PDF
attachments. Additionally, the body of the email can even have embedded HTML. Thus,
a group of users have report sharing facility ("Business Intelligence Reporting &
Dashboards", 2018).
For the business Intelligence reporting solution the prescriptive and the
descriptive analytics are selected and are discussed in the below sections.
3.1 Prescriptive Analysis
The Prescriptive Analytics utilizes optimization and simulation algorithms for
advising on the possible results and answers. This analysis supports to find the answer
of what has to be done next. Prescriptive Analytics provides advice for the possible
outcomes. It helps to prescribe various possible actions, which acts as a guidance for
the solution. Therefore, this type of analytics just provides good and effective advice.
Prescriptive analytics tries to quantify the impact of the future decisions for advising on
the possible outcomes, even before making any decisions. It generally not just predicts
what would happen, however it also ensure to determine why it would happen and
provides suggestions in terms of effective actions that can be implemented to resolve
the problem. This type of analytics can be used anytime required for providing helpful
advice for the users, for their problems ("Descriptive, Predictive, and Prescriptive
Analytics Explained", 2018).
The Business Intelligence dashboard modifies the traditional business
intelligence reports and represents it in the form of predictive performance metric
("Business Intelligence Dashboard Examples", 2018). For business intelligence
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dashboard reporting, the predictive performance reporting system is a method which
follows process based tracking system as follows:
1) Check the stability of the process, which produces the response.
2) If the process is stable, in such case provide a predictive response such
as in future what is expected if some steps are not taken.
The below analysis represents the analysis of environmental issues which are
determined, for the current year 2018.
The explanation of the dashboard is as follows:
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