Predictive analyticsPredictive analytics is a form of business analytics applying machine learning to generate a predictive model for certain business applications. As such, it encompasses a variety of statistical techniques from predictive modeling and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events. It represents a major subset of machine learning applications; in some contexts, it is synonymous with machine learning.
AnalyticsAnalytics is the systematic computational analysis of data or statistics. It is used for the discovery, interpretation, and communication of meaningful patterns in data. It also entails applying data patterns toward effective decision-making. It can be valuable in areas rich with recorded information; analytics relies on the simultaneous application of statistics, computer programming, and operations research to quantify performance. Organizations may apply analytics to business data to describe, predict, and improve business performance.
Business analyticsBusiness analytics (BA) refers to the skills, technologies, and practices for iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods. In contrast, business intelligence traditionally focuses on using a consistent set of metrics to both measure past performance and guide business planning.
Prescriptive analyticsPrescriptive analytics is a form of business analytics which suggests decision options for how to take advantage of a future opportunity or mitigate a future risk, and shows the implication of each decision option. It enables an enterprise to consider "the best course of action to take" in the light of information derived from descriptive and predictive analytics. Prescriptive analytics is the third and final phase of business analytics, which also includes descriptive and predictive analytics.
Predictive modellingPredictive modelling uses statistics to predict outcomes. Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crime has taken place. In many cases, the model is chosen on the basis of detection theory to try to guess the probability of an outcome given a set amount of input data, for example given an email determining how likely that it is spam.
Machine learningMachine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.
Food distributionFood distribution is the process where a general population is supplied with food. The Food and Agriculture Organization (FAO) considers food distribution as a subset of the food system. The process and methodology behind food distribution varies by location. Food distribution has been a defining characteristic of human behavior in all societies, and recordings of food distribution date back for thousands of years. Most governments and societies are highly shaped by the systems created to support food distribution.
Food industryThe food industry is a complex, global network of diverse businesses that supplies most of the food consumed by the world's population. The food industry today has become highly diversified, with manufacturing ranging from small, traditional, family-run activities that are highly labour-intensive, to large, capital-intensive and highly mechanized industrial processes. Many food industries depend almost entirely on local agriculture, animal farms, produce, and/or fishing.
Food engineeringFood engineering is a scientific, academic, and professional field that interprets and applies principles of engineering, science, and mathematics to food manufacturing and operations, including the processing, production, handling, storage, conservation, control, packaging and distribution of food products. Given its reliance on food science and broader engineering disciplines such as electrical, mechanical, civil, chemical, industrial and agricultural engineering, food engineering is considered a multidisciplinary and narrow field.
Food systemThe term food system describes the interconnected systems and processes that influence nutrition, food, health, community development, and agriculture. A food system includes all processes and infrastructure involved in feeding a population: growing, harvesting, processing, packaging, transporting, marketing, consumption, distribution, and disposal of food and food-related items. It also includes the inputs needed and outputs generated at each of these steps.
Sustainable food systemA sustainable food system is a type of food system that provides healthy food to people and creates sustainable environmental, economic, and social systems that surround food. Sustainable food systems start with the development of sustainable agricultural practices, development of more sustainable food distribution systems, creation of sustainable diets, and reduction of food waste throughout the system. Sustainable food systems have been argued to be central to many or all 17 Sustainable Development Goals.
