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This dataset was meticulously gathered, organized and published by the Food and Agriculture Organization of the United Nations. This project is taken from

Animal agriculture and factory farming is a growing interest of the public and of world leaders.

  • Can you find interesting outliers in the data?
  • What are the fastest growing countries in terms of food productionconsumption?
  • Compare between food and feed consumption.

Advanced Work:

Students could perform advance work by integrating other datasets with the given dataset (i.e to explore following

  • World Food production and consumption by per capita?
  • world food production and consumption according to population density ( divided by population in each country ) in 2013 (particular year/s)
  • Inequality of Food production/ consumption by region/continents?
  • The global perspective of meat supply by region/continents? (Item Code 2731 to 2735 student have to check more carefully is there any item code which associated with meat).

Hint: Students could download the other datasets from the link above and then could

using VLOOKUP formula to import the required field.

Your task is to complete the following tasks:

Task 1- Background information

Write a description of the selected dataset and project, and its importance for the global leaders. Information must be appropriately referenced.

Task 2 – Reporting / Dashboards

For your project, perform the relevant l data analysis tasks listed under basic and advanced work and identify the BI reporting solution and/or dashboards you need to develop for the operational manager of the indicated firm.

Task 3 – Research

Justify why these BI reporting solution/dashboards are chosen in Task 2 (Reporting / Dashboards) and why those data sets attributes are present and laid out in the fashion you proposed (feel free to include all other  relevant justifications).

Note: To ensure that you discuss this task properly, you must include visual samples of the reports you produce (i.e. the screenshots of the BI report/dashboard must be presented and explained in the written report; use ‘Snipping tool’), and also include any assumptions that you may have made about the analysis in your Task2 (i.e. the report to the operational team of the company).

Task4 – Recommendations for CEO

The CEO of the consulting firm would like to improve the operations. Based on your BI analysis and the insights gained from “Data Set” in the lights of analysis performed in previous tasks, make some logical recommendations to the CEO, and justify why/how your proposal could enhance food related operations and could assist in achieving operational/strategic objectives with the help of appropriate references from peer-reviewed sources. [2-3 Pages].

Background Information

The datasets that have been selected contain information regarding the production as well as consumption of food all over the world (Hoyt, Snider & Thompson, 2016). The data is of 245 countries and territories. These datasets analyze the production of various food items such as Wheat, potatoes, fruits, various oils, alcohol, spices and many more from the year 1961 to 2013. These datasets also include the name of the countries, production in units, area codes, type of elements and item code.

According to various studies it has been found that population keeps growing every day, as a result, it is very important that a steady growth of food items is maintained all over the world. This has to be done in order to meet the basic demand of the entire population.   The organizations that have opened for producing food as well as distribute them need to carry out the evaluation of the demand against supply (Tsoi, Chan & Hirai, 2017). This particular project would be helpful for the organization in investigating of various questions related to the needs. Usage of Business Intelligence Platforms such as IBM Watson would help in exploring the insights out of unstructured as well as structured information for organization (Khoury, Achicanoy & Bjorkman, 2016). This data would help the organizations to access production of various food items in various regions.  

Comparison of food and Feed from the given dataset

From the above given dashboard, it can be said that for the available dataset the production of food is more than four times of the feed produced the different areas of the world.

Following are the top ten countries that produces most of the feed and food throughout the world according to the given dataset;

For the feed the top 10 countries or area is given by Spain, Germany, Italy, Greece, Hungary, China, Japan, United Kingdom, Sweden and lastly Philippines.

Again for the food the top ten countries in terms of the production  of food  are given by, Philippines, Japan, China, Sweden, Italy, Spain, United Kingdom, Germany, Hungary and Greece.

The supply of meat that has been done globally by various regions all over the world

For the meat supply there it can be stated that the in the year 1961 the meat was not even present in the top 10 produced/consumed foods where as in case of year 2013 it appears at the tenth position of top ten items in produced and consumed items.


From the dashboard provided above, it could be said that in the year 2013, China is the country that had supplied maximum amount of meat (Alexander, Brown & Arneth, 2016). This analysis has been done including various item codes like 2731, 2732, 2733, 2734 and 2735.  

 From the research of the given dataset, it has been found that production of cereals in a given timeframe of the dataset had increased constantly (Gao, Dontcheva & Adar, 2015). This can be found from the dashboard provided below. This dashboard had been obtained from the IBM Watson Platform. The production of various cereals had been doubled in year 1961 compared to other years.  

Most of the cereal is produced from Afghanistan.

The countries that have produced least amount of food items in the year 1961 are represented in the dashboard that has been given below.

 From the given diagram it can be found out that the areas or countries with least production of food items are Saint Kitts, Djibouti, Nevis, Darussalam, Kiribati, Brunei Dominica, Grenada, Saint Vincent, Maldives, Grenadines, Saint Lucia, Sao Tome and Principe (Tsoi, Chan & Hirai 2018).

The top 10 countries highest production of food items are depicted in the dashboard given below.  

This dashboard represents the 10 countries that had highest food production compared to other countries (Schierhorn, Meyfroidt & Kastner, 2016). These countries are United States of America, Japan and Italy, Germany, India, china mainland, France, United Kingdom, Poland, and Brazil. From the list, the least production was received from Poland.

The top and least ten countries that had produced the minimum amount of food items in year 2013 would be analysed below.

The 10 areas that had produced least amount of food items are given in the dashboard.

From the dashboard given above, it could be said that the countries present in the list of least food production are the same as the ones in year 1961 (Fetzel, Niedertscheider & Haberl, 2016). The areas are as follows Dominica, Nevis, Saint Kitts, Saint Vincent, Grenada, Kiribati, Antigua and Barbuda, Bermuda, Sao Tome and Principe, Samoa and Saint Lucia.

It is clear from the research that the countries like Brunei Darussalam, Maldives and Djibouti had improved a lot compared to other years in areas of food productivity.

Top 10 areas in the terms of productivity are

 From the dashboard given above it could be said that countries like India and China (mainland), Brazil, United States of America are leading in the given list of various countries that have producing maximum amount of food items all over the world.


From the dashboard given above for years 1961 as well as 2013, it could be said that has been constantly at the top in terms of production (Gasparri, Kuemmerle & Meyfroidt, 2016). The dashboard of year 1961 and 2013 depicts that countries have fluctuated their places in the list from Y1961 to Y2013. The graph clearly depicts that the food production has changed for the 10 countries that were on the top. Along with that, it has been found that countries like India and China have increased their production of food because of the increasing demand of the population.

Furthermore, from the obtained analysis it can be stated that India and China are the countries that have been developing rapidly in terms of food production in 1961 according to the provided dataset (Dwivedi, van Bueren & Ceccarelli, 2017). Along with this, these countries have shifted their positions from second and third place in year 1961 to first and second in 2013. This is because China and India are the countries that have the largest population; the population has been growing constantly since 1961. The increase in population requires more production of food items in order to meet the demands of the population (Ranganathan, Vennard & Waite, 2016). China has been keeping up its trend of high production of food since 42 years. Whereas, United States of America had taken the third position in year 2013 from its first position in 1961.

The dashboards given below depict top 10 products that have been in trend considering the consumption of food in years 1961 and 2013.

Top ten items for the year 1961;

The top ten food products in year 2013 are provided in the following dashboard;

From the dashboards provided above, it could be said that the items that are in the list for year 1961 to 2013, the cereals have been mostly produced as well as consumed all over the world (Tamea, Laio & Ridolfi, 2016). Whereas potatoes and similar food items are nowhere in the top ten foods produced in year 2013.

Some other food products that were present in the analysis were various milk products (not including butter), potatoes and many more vegetables, organic products (Tamea, Laio & Ridolfi, 2016). Elevated generation would be found, in case there is an occurrence of milk products considered after grains and beer is excluded.   

 Along with that, the exclusion of potatoes and products obtained from the top 10 food items, meat has been added recently in year 2013 (Dwivedi, van Bueren & Ceccarelli, 2017). Usually there are 7 categories of meat that is consumed all over the world. The categories are Meat of Aquatic animals, Bovine Meat, poultry meat, pig meat, Mutton and goat meat.

Recommendations for CEO

The dashboard that would depict the various types of meats consumed by people is given below.

From the dashboard provided above, it can be said that, the meat of aquatic animals have been consumed less by people compared to the meat of goat (Dwivedi, van Bueren & Ceccarelli, 2017). Poultry meat and pig meat.

 It is very important to improve the meat production because it has been considered among the food items that are consumed the most. In the year 1961, meat as well as meat based items was not among the 10 rundowns of delivery (Gasparri, Kuemmerle & Meyfroidt, 2016). In the time span between 1961 and 2013, in year 2013 they had discovered a particular place. Increasing the production of meat is a way to meet the demand of the population. Along with this, the meat based items have a very esteem of wholesome as well as has the ability to assume a tough job in the competition with the crisis of food (Gasparri, Kuemmerle & Meyfroidt, 2016). The rapid increase in population has resulted in decrease in the amount of place available for production of food. As a result, the food products are difficult to produce in a limited space. The amount of food produced is not enough to meet the demands of the entire population. This results in feed production. Feed production does not actually need huge amount of farms or fields. The feed production has been introduced recently in the list of food product that is consumed the most (Gasparri, Kuemmerle & Meyfroidt, 2016). Among the countries India and China, China consumed more feed products compared to India.

Production of Food and Feed in y2013

The dashboard given above represents the food as well as feed production in Y2013 for various countries in the world. The portions that have been portrayed with a green line in the pie graph of Y2013 represent China (Schierhorn, Meyfroidt & Kastner, 2016). From the dashboard given above, it could be sated that, India produces more food compared to its feed production according to the pie graph.

Consumption of food items by the population in year 2013

When a comparison has been carried out of the consumption of various food items by population of different countries, a dashboard has been found. The dashboard is given below.

From the dashboard given above, it could be said that, the most amount of food consumed per capita in the countries of Italy, France, Norway and Russian federation, Canada, Spain, Kazakhstan, Indonesia, USA, Brazil, Australia, Japan, Mexico, India and Mali.

  From the above analysis following are the recommendations that can be used    in order to improve the scenario and meet the both ends i.e. supply and demand of the foods by different areas in the given dataset.

 Diversified food production:   In our analysis, we found that throughout the time period of 1961 to 2013, the most general food item which is produced as well as consumed is the cereal. Thus it is important to diversify the production food items in different regions of the world.

Numerous research program indicated that diversity in the food production can help in fighting with the food crisis in the present scenario. As it is observed that for the long time period of 42 years there is similarity in food productions throughout the world therefore it is now a vita point to consider for producing diverse range of food items.

Improving the production of meat based food items:  In the above analysis, it is found that meat based products is in the list if top 10 products that are consumed in the year 2013. Increase in the production of meat based food items can  be helpful in the  improving the scenario of  food crisis throughout the world due to the increase in population. Furthermore, it can be said that meat based food items have a high nutritional value and can play vital.

Food security is one of the burning issues in the present scenario along with the increasing population. Different researchers have found that with the present rate of growth in the population the food production must be doubled by the next 30 years order to meet the demand against the supply of the food.

 In order to analyse the scenario, the food production/consumption data is collected from Food and agricultural Organization. This collected data is the analysed using the BI data analysis tool IBM Watson Analytics. Through the analysis different important insights from the data is collected depending on the food items, countries and regions was visualised.

From the above analysis it is found that there is significant increase in the production levels from 1961 to 2013. However, this change in the production is not too much helpful for this scenario.  It is also investigated and found that there is not too much change in the food consumption patterns (except the entry of meat based foods in the list of top 10 food items) which depicts the lack of food diversity. Therefore, it is suggested to bring in the diversification in the production of the food items in order meet the demands.

 In addition to that it is also important to improve the production of foods which are listed as top ten food producing countries as there is no new entrants in the top food producing countries.


Alexander, P., Brown, C., Arneth, A., Finnigan, J., & Rounsevell, M. D. (2016). Human appropriation of land for food: the role of diet. Global Environmental Change, 41, 88-98.

Dwivedi, S. L., van Bueren, E. T. L., Ceccarelli, S., Grando, S., Upadhyaya, H. D., & Ortiz, R. (2017). Diversifying food systems in the pursuit of sustainable food production and healthy diets. Trends in plant science, 22(10), 842-856.

Fetzel, T., Niedertscheider, M., Haberl, H., Krausmann, F., & Erb, K. H. (2016). Patterns and changes of land use and land-use efficiency in Africa 1980–2005: an analysis based on the human appropriation of net primary production framework. Regional environmental change, 16(5), 1507-1520.

Gao, T., Dontcheva, M., Adar, E., Liu, Z., & Karahalios, K. G. (2015, November). Datatone: Managing ambiguity in natural language interfaces for data visualization. In Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology (pp. 489-500). ACM.

Gasparri, N. I., Kuemmerle, T., Meyfroidt, P., le Polain de Waroux, Y., & Kreft, H. (2016). The emerging soybean production frontier in Southern Africa: conservation challenges and the role of south?south telecouplings. Conservation Letters, 9(1), 21-31.

Hoyt, R. E., Snider, D., Thompson, C., & Mantravadi, S. (2016). IBM Watson analytics: automating visualization, descriptive, and predictive statistics. JMIR public health and surveillance, 2(2).

Khoury, C. K., Achicanoy, H. A., Bjorkman, A. D., Navarro-Racines, C., Guarino, L., Flores-Palacios, X., ... & Ramírez-Villegas, J. (2016). Origins of food crops connect countries worldwide. Proc. R. Soc. B, 283(1832), 20160792.

Ranganathan, J., Vennard, D., Waite, R. I. C. H. A. R. D., Dumas, P., Lipinski, B., & Searchinger, T. (2016). Shifting diets for a sustainable food future. World Resources Institute.

Schierhorn, F., Meyfroidt, P., Kastner, T., Kuemmerle, T., Prishchepov, A. V., & Müller, D. (2016). The dynamics of beef trade between Brazil and Russia and their environmental implications. Global Food Security, 11, 84-92.

Tamea, S., Laio, F., & Ridolfi, L. (2016). Global effects of local food-production crises: a virtual water perspective. Scientific reports, 6, 18803.

Tsoi, K. K., Chan, F. C., Hirai, H. W., Keung, G. K., Kuo, Y. H., Tai, S., & Meng, H. M. (2018). Data Visualization with IBM Watson Analytics for Global Cancer Trends Comparison from World Health Organization. International Journal of Healthcare Information Systems and Informatics (IJHISI), 13(1), 45-54.

Tsoi, K. K., Chan, F. C., Hirai, H. W., Leung, G. K., Kuo, Y. H., Tai, S., & Meng, H. M. (2017). Data visualization on global trends on cancer incidence an application of IBM Watson Analytics.

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