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ITECH7406 Business Intelligence And Data Warehousing
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ITECH7406 Business Intelligence And Data Warehousing
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Course Code: ITECH7406
University: Federation University
MyAssignmentHelp.com is not sponsored or endorsed by this college or university
Country: Australia
Question:
What are the BI reporting solution/dashboards you will 10 need to develop for the Senior Executives of chosen data Set– You must have at least two types of analytics i.e Predictive/prescriptive/ descriptive
Based on your BI analysis and insights gained from the data set, make logical recommendations on how to improve the environment.
Report is well-written and presented professionally, containing:
Title page 1
Executive Summary (outlining the scope of report, key findings and recommendations)
Table of Contents
Appropriate use of headings within report
Answer:
Introduction:
The research report is based on the data analysis on a data set of environmental issues. The data analysis is based on the collection of five data set. The data sets are collected from “UN data” website. The data sets contain the historical data of five chosen countries of different continents. The selected common countries are- Australia (Oceania), Germany (Europe), Japan (Asia), Turkey (Europe) and United States of America (North America). All the chosen countries are the UN certified countries. The latest data of time period 2011 to 2015 are gathered for specific analysis.
The secondary data sets are real world data sets. The five data sets involve mainly three variables- Country name, Year and amount of green-house gas in that country. Five data sets include five distinguishable types green-house gases that are – Carbon di-Oxide, Methane, Hydrofluoric Carbon, Sulphur hexa-fluoride and Perfluorocarbons. For the ease of analysis, the analysis merged the data sets and then again split the data set country wise.
The prototype of the business information would be analysed using the dashboard (Calof, Richards & Smith, 2015). The crucial factor of the research report is to apply any analytic software such as SAP for presenting various sorts of analytic issues. The analysis is executed with SAP business predictive and objective analytics. It designs necessary visualizations like dashboards and predictive models for various types of analytical problems. The forecasting and simulative model is executed carried out for the analysis. Two different types of analysis such as descriptive analysis and predictive analysis are executed in this report.
Research Objectives:
The research report is based on the analysis of business information. The data analysis informs exploration, extraction and analysis of enterprise. The insights are achieved form the data analysis and logical recommendation about enhancing the environment. The analysis would depict the dashboards and predictive analysis that would make logical recommendations about improving the environment.
Background:
The case study is related critical environmental issues such as Global worming with the help of dashboards. The dashboards depict the presence of green house gases in the span of 2011 to 2015. The purpose of the report is to improve visual analytics and to predict the country wise emission of green house gases depending on the globalisation.
Scope of the Research Analysis:
The analysis takes an administrative part for the better sustainability of the environment. The Senior executive is interrogated to make preparation for the meeting with the board of association. Before, the commencement of such types of meeting, the Senior executive is allowed to provide the reports of perspective and descriptive analysis. To encounter the issues of environment caused by global warming, the meeting would talk on the accessibility, monitoring and preferable measures of database information. Hence, the proposed system must be capable of searching the challenges that are crucial to be notified by the board members.
Data description:
Value
Storage
Missing Value Count
Missing Value Weight
Role
Total Weight
Country or Area
nominal
string
0
0
input
25
Year
ordinal
integer
0
0
input
25
CH4_Value
continuous
number
0
0
input
25
CO2_Value
continuous
number
0
0
target
25
HCF_Value
continuous
number
0
0
input
25
SF6_Value
continuous
number
0
0
input
25
PCFs_Value
continuous
number
0
0
input
25
KxIndex
continuous
integer
skip
The data set has a total of 7 variables. The five chosen countries are the Australia, Germany, Japan, Turkey and United States of America. The numerical variables are- amount of Carbon di-oxide (CO2), amount of Methane (CH4), amount of Hydrofluoric Carbon (HCF), amount of Sulphur Hexafluoride(SF6) and number of Perfluorocarbons (PCFs). The green house pollutants are measured according to the historical data of 2011, 2012, 2013, 2014 and 2015.
Impact of green-house gases in the environment:
Greenhouse gases are those gases that trap heat in the atmosphere of the Earth. The emission of greenhouse gases like CO2 or Methane creates the climate concerns. Mainly three properties of the green house gases such as Concentration, longevity in the atmosphere and strength of impact make themselves more vulnerable for the balance of the earth. These gases are known as the warmer of the earth thickening the blanket of the Earth. The erosion of Ozone layer is the direct affect of these green-house gases. It permits dangerous ultra-violet ray of the Sun to penetrate in the surface of the earth (Revkin, 1992). Many critical and syndromic diseases such as skin cancer, leukaemia and skin pigmentation are caused due to it. Besides, melting of polar ices, unnecessary natural calamities and scarcity of greenery are the vibrant outcomes of the greenhouse gases.
Carbon di-Oxide (CO2): Carbon dioxide originates from the solid wastes, wooden products, chemical factories and moreover from burning fossil fuels (Yeh & Bai, 1999). It is the major green house gas. CO2 majorly therefore accused as global warming.
Methane (CH4): Methane is emitted during the production and transport of oil, natural gas and coals. Live-stocks and other agricultural practices generate organic waste in municipal solid waste landfills (Soussana et al., 2007).
HCF, SF6 and PCFs: Hydrofluorocarbons, perfluorocarbons and sulphur hexafluoride are the synthetic and powerful greenhouse gases emitted from several industrial processes. Fluorinated gases are used as the substitute of stratospheric Ozone-depleting materials such as Chol Fluro Carbons (CFC), hydrochlorofluorocarbons and types of halons (Hansen & Sato, 2004). These gases are emitted in lower quantities produced from industries, air conditions or refrigerator (Baasandorj, Hall & Burkholder, 2012). These fluorinated gases are generally emitted in small quantities. However, these are potent green-house gases. That is why, these gases are referred to as High global warming potential gases.
Selected Analysis Process:
The business information reporting solution are chosen to represent the predictive data analysis as it can help to map the data set and helps the users to make the analysis report (Eckerson, 2010). The method enables to go in-depth of the data set for detailed examination of the report. As per needs. Business information reporting therefore is an effective solution that for its easiness and flexibility (McCue, 2014). It also allows several effective filters that could be applied for the analysis. Above all, the BI reports could be send and received in any format of the documents.
Data Analysis:
Descriptive Statistics:
The descriptive of summary analysis the overview of historical insights. Descriptive analysis is a statistical analysis that summarizes the raw data and helps to easily interpret the data. The descriptive analysis is beneficial as it assists in learning important details from the past behaviours. It leads to account future consequences and the impacts. Minimum, maximum, average (mean) and standard deviation are the considered measures of descriptive statistics here. The percentage change or share of the variables is also a special type of visualization of descriptive statistics regarded here. For business purpose, the descriptive statistics provide the benefit to represent the total stock in the inventory, mean expense, level of production, amount of sales and financial condition of the organisation (Deka, 2016).
Carbon di-Oxide (CO2):
The amount of lowest CO2 emission in all the countries is found to be 347747 litres and highest CO2 emission is 5569520 litres in all the countries in the time period 2011-2015. The average CO2 emission of the 5 years in 5 chosen countries is 1665660 litres.
The influence of CO2 is maximum in 2013 and minimum in 2015 among all the 5 years in the chosen 5 countries.
Methane (CH4):
The amount of lowest CH4 emission in all the countries is 32673.3 litres and highest CH4 emission is 672102 litres in all the countries in the time period 2011-2015. The average CH4 emission of the 5 years in 5 chosen countries is 256584 litres.
The influence of CH4 is minimum for 2015 and maximum in 2011 among all the 5 years in the chosen 5 countries.
Sulphur hexa-fluoride (SF6):
The amount of lowest SF6 emission in all the countries is 125.002 litres and highest SF6 emission is 9187.41 litres in all the countries in the time period 2011-2015. The average SF6 emission of the 5 years in 5 chosen countries is 3075.83 litres.
The influence of SF6 is minimum for 2013 and maximum in 2011 among all the 5 years in the chosen 5 countries.
Hydrofluoric Carbons (HCF):
The amount of lowest HCF emission in all the countries is 3432.64 litres and highest HCF emission is 157207 litres in all the countries in the time period 2011-2015. The average HCF emission of the 5 years in 5 chosen countries is 45178.8 litres.
The influence of HCF is minimum for 2011 and maximum in 2015 among all the 5 years in the chosen 5 countries.
Perfluoro Carbons (PACFs):
The amount of lowest PACFs emission in all the countries is 120.088 litres and highest PACFs emission is 6897.84 litres in all the countries in the time period 2011-2015. The average PACFs emission of the 5 years in 5 chosen countries is 2213.15 litres.
The influence of PACFs is minimum for 2015 and maximum in 2011 among all the 5 years in the chosen 5 countries.
Prescriptive Analysis:
The prescriptive analysis comprehends optimization and simulation algorithms for advising on the possible results and answers. Prescriptive analysis indicates patterns and suggests the possible way-outs to find the answers of next time (Gröger, Schwarz & Mitschang, 2014). The analysis helps to prescribe several good and effective possible measures that could be used for the guidance of the solution. Prescriptive analytics attempts to quantify the influence of the future decisions and forecasts to determine future scenario (Bertsimas & Kallus, 2014). The implementation of probable measures advised by predictive analysis resolve the problems. Such types of analytics can be utilised to apprehend the beneficial suggestions.
Firstly, the comparative bar chart and then simulation process to optimize the considered variables helps to construct the perspective analytics. Secondly, the business information dashboard modifies the traditional business information reports and depicts in the form of predictive performance. The BI dashboard reporting and predictive performance reporting system follows two methods that are – verifying the stability of the process and providing expected predictive response in case of stable process (Holbrook, Block & Fitzsimons, 1998).
The evaluation of clustering of emissions of five types of global warming gases depicts that total amount of global warming gases is maximum in 2012, followed by 2011. The fraction share of global warming gases is equal in 2014 and 2015. The lowest amount of total emitted gases is in 2013.
The applied simulation process indicates that the predictive model having CH4 gas = 203122, HCF gas = 45178.8, PCFs = 2213.15, SF6 gas = 3075.83 in year 2012 results the estimated emitted CO2 gas –
Minimum value = 348004
Maximum value = 5569520
Average CO2emitted = 1820620
Distribution Fitting:
Carbon di-Oxide (CO2):
The distribution of the CO2 emission in the selected countries indicate that the emission varies from less than 500000 litres to more than 5500000 litres almost in all the years except 2012. The range of emission is more of less year wise stable as per ranges of amounts among all the 5 countries. The variation is least in 2012 between two countries.
Methane (CH4):
The trend fitting of the CH4 emission in the chosen countries refer that the emission varies from less than 50000 litres to over 650000 litres per year in these countries for 2011. However, the emission ranges from 650000 litres to more than 100000 litres among the 5 countries in the years 2012 to 2014. In 2015, the range of emission is the countries again ranges from 650000 litres to 50000 litres. The higher range also depicts lower CH4 emission in some countries.
Hydro fluoric Carbon (HCF):
The distribution fitting of HCF refers that the range of emission is growing year after year. The total emission was below 150000 litres in those 5 countries. However, it is higher than 150000 litres in 2014 and more than 160000 litres in 2015. The emission amount of HCF also has increased in the countries that have lower emission amounts in the previous years.
Sulphur hexa-fluoride (SF6):
The distribution of SF6 indicates that the range of emission is decreasing year after year. In 2011, the range of SF6 emission in different countries was found to be highest as varying over the interval of more than 9000 litres to less than 500 litres. The range of the emission in 2012 is less than 2011 varying in the interval of less than 7000 litres to less than 500 litres. The emission in 2013 and 2014 have almost equal range of SF6 emission. The emission of the gas in 2015 is least. The highest emission for any country is less than 6000 litres and lowest emission for any country is 2000 litres.
Perfluoro Carbons (PCFs):
The distribution of presence of PCFs in the air refers that PCFs are mostly emitted in 2011 with a high range of almost 7000 litres to below 500 litres. The range of PCFs in 2012, 2013 and 2014 have comparatively equal and lower range of emission. The maximum presence of PCFs for any country is found to be 6000 litres to 5500 litres and minimum presence of PCFs for any country is found to be less than 500 litres. The highest presence of PCFs of the air in any country is maximum noted as 5500 litres to 5000 litres while minimum remains almost equal.
Prediction and Forecasting with dashboards:
The forecasting and future prediction are comprehended by double exponential method. The country wise presence of green house gases is presented with the help of dashboards. The following dashboard summarizes the business information in a simple view utilising several database sources (Gualtieri et al., 2013). The meeting committee would like to monitor the real-time information and KPI’s. The analysis is accessible for different purposes also. The dashboard reporting enables the research team to drill down utilising dynamic graphs and predictive plots of 2016.
The dashboard representation enables divergent data exploration and analysis process that can be used to compare data from various divisions or separate entities (MacGregor, 2013). Hence, dashboards are the understandable format of visualisation to all.
Carbon di-Oxide (CO2):
Dashboard1:
The forecasted emitted CO2 in 2016 is found to be-
Australia: 105000 litres
Germany: 790000 litres
Japan: 1187500 litres
Turkey: 391000 lires
United States of America: 5495000 litres
Logical Recommendation:
1) Australia should maintain the lower CO2 emission as of 2015.
2) United States of America should control the emission of CO2 from factories that generate luxurious items.
3) Turkey and Germany should restrict the growth of population and control CO2 emission from the vehicles.
4) Japan should maintain the decreasing trend of CO2 with proper governance of respective government.
Methane (CH4):
The forecasted emitted CH4 in 2016 is found to be-
Australia: 100000 litres
Germany: 54700 litres
Japan: 307500 litres
Turkey: 50500 lires
United States of America: 652000 litres
Logical Recommendation:
1) All the countries have decreasing trends of methane emission. These countries should follow the way in which Australia is maintaining the carbon emission.
2) Climate changing and air quality changing awareness is necessary for taking controlled measures.
Hydrofluoric Carbon (HCF)
The forecasted emitted HCF in 2016 is found to be-
Australia: 12000 litres
Germany: 11190 litres
Japan: 12500 litres
Turkey: 5125 lires
United States of America: 168000 litres
Logical Recommendation:
1) Except Turkey, the presenece of HCF in the air is gradually increasing in other countries. It is the concerning issue.
2) These countries should focus on energy saving machines that are environment friendly in nature.
Sulphur Hexa-fluoride (SF6):
The forecasted emitted SF6 in 2016 is found to be-
Australia: 132.5 litres
Germany: 3725 litres
Japan: 2112 litres
Turkey: 2350 lires
United States of America: 5750 litres
Logical Recommendations:
1) Sulphur hexa-fluoride is gradually decreasing in United States of America. All the other countries are producing more SF6 in recent years that should be controlled.
2) The people of these countries should be well aware about chemical wastages.
3) The government of these countries should take policies to control the impact of chemical and laboratory wastages (Saad, 2001).
Per fluoric-carbons (PCFs):
The forecasted emitted PCFs in 2016 is found to be-
Australia: 142 litres
Germany: 250 litres
Japan: 3275 litres
Turkey: 75 lires
United States of America: 5100 litres
Logical Recommendation:
1) The presence of PCFs in the air of Germany and Japan is going to be incraesed in 2016 whereas rest of the countries are producing lesser PCFs next year.
2) The use of airconditioners and refrigerators should be controlled in those countries (Kolovos et al., 2010).
3) The consciousness of the people is essential in this case.
Conclusion:
According to the data visualization, a proper suitable decision support is undertaken. The analysis helps to experience the usability of SAP analytics tools with respect to data. Prediction and future forecasts are found. Descriptive and Prescriptive analysis helped to design the necessary prototypes. The key indicator variables are found to be year and amount of Carbon dioxide gas.
All the chosen countries are developed or highly developing countries. The countries of higher population must have higher amount of household wastages and chemical wastages. It causes the presence of higher amount of greenhouse gases in the air. The overview of all types of 5 gases helps to draw conclusion that the generation of greenhouse gases is mostly in United States of America followed by Japan, Germany and Turkey respectively. The emission is comparatively least for Australia. Especially the emission of Carbon dioxide is very significant in United States of America. The emission and presence of Methane and poisonous fluoric gases is significant in Turkey and Germany too. The year wise prediction refers that the presence of green house gases was mostly observed in 2012 among all the chosen years from 2011 to 2015
References:
Baasandorj, M., Hall, B. D., & Burkholder, J. B. (2012). Rate coefficients for the reaction of O (1 D) with the atmospherically long-lived greenhouse gases NF 3, SF 5 CF 3, CHF 3, C 2 F 6, cC 4 F 8, n-C 5 F 12, and n-C 6 F 14. Atmospheric Chemistry and Physics, 12(23), 11753-11764.
Bertsimas, D., & Kallus, N. (2014). From predictive to prescriptive analytics. arXiv preprint arXiv:1402.5481.
Calof, J., Richards, G., & Smith, J. (2015). Foresight, competitive intelligence and business analytics—tools for making industrial programmes more efficient. ???????, 9(1 (eng)).
Deka, G. C. (2016). Big data predictive and prescriptive analytics. In Big Data: Concepts, Methodologies, Tools, and Applications (pp. 30-55). IGI Global.
Eckerson, W. W. (2010). Performance dashboards: measuring, monitoring, and managing your business. John Wiley & Sons.
Gröger, C., Schwarz, H., & Mitschang, B. (2014, May). Prescriptive analytics for recommendation-based business process optimization. In International Conference on Business Information Systems (pp. 25-37). Springer, Cham.
Gualtieri, M., Rowan Curran, A., TaKeaways, K., & To, M. T. B. P. P. (2013). The Forrester Wave™: Big Data Predictive Analytics Solutions, Q1 2013. Forrester research.
Hansen, J., & Sato, M. (2004). Greenhouse gas growth rates. Proceedings of the National Academy of Sciences of the United States of America, 101(46), 16109-16114.
Holbrook, M. B., Block, L. G., & Fitzsimons, G. J. (1998). Personal appearance and consumption in popular culture: A framework for descriptive and prescriptive analysis. Consumption, Markets and Culture, 2(1), 1-55.
Kolovos, A., Skupin, A., Jerrett, M., & Christakos, G. (2010). Multi-perspective analysis and spatiotemporal mapping of air pollution monitoring data. Environmental science & technology, 44(17), 6738-6744.
MacGregor, J. (2013). Predictive Analysis with SAP®. SAP Press.
McCue, C. (2014). Data mining and predictive analysis: Intelligence gathering and crime analysis. Butterworth-Heinemann.
Revkin, A. (1992). Global warming: understanding the forecast. New York: Abbeville Press.
Saad, G. H. (2001). Strategic performance evaluation: descriptive and prescriptive analysis. Industrial Management & Data Systems, 101(8), 390-399.
Soussana, J. F., Allard, V., Pilegaard, K., Ambus, P., Amman, C., Campbell, C., … & Flechard, C. (2007). Full accounting of the greenhouse gas (CO2, N2O, CH4) budget of nine European grassland sites. Agriculture, Ecosystems & Environment, 121(1-2), 121-134.
Yeh, A. C., & Bai, H. (1999). Comparison of ammonia and monoethanolamine solvents to reduce CO2 greenhouse gas emissions. Science of the Total Environment, 228(2-3), 121-133.
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