Big dataBig data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe big data is the one associated with a large body of information that we could not comprehend when used only in smaller amounts.
Economic analysis of climate changeThe economic analysis of climate change explains how economic thinking, tools and techniques are applied to calculate the magnitude and distribution of damage caused by climate change. It also informs the policies and approaches for mitigation and adaptation to climate change from global to household scales. This topic is also inclusive of alternative economic approaches, including ecological economics and degrowth. Economic analysis of climate change is considered challenging as it is a long-term problem and has substantial distributional issues within and across countries.
SnowmeltIn hydrology, snowmelt is surface runoff produced from melting snow. It can also be used to describe the period or season during which such runoff is produced. Water produced by snowmelt is an important part of the annual water cycle in many parts of the world, in some cases contributing high fractions of the annual runoff in a watershed. Predicting snowmelt runoff from a drainage basin may be a part of designing water control projects. Rapid snowmelt can cause flooding.
Climate sensitivityClimate sensitivity is a measure of how much Earth's surface will cool or warm after a specified factor causes a change in its climate system, such as how much it will warm for a doubling in the atmospheric carbon dioxide () concentration. In technical terms, climate sensitivity is the average change in global mean surface temperature in response to a radiative forcing, which drives a difference between Earth's incoming and outgoing energy.
Data scienceData science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured, and unstructured data. Data science also integrates domain knowledge from the underlying application domain (e.g., natural sciences, information technology, and medicine). Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession.
Data warehouseIn computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is considered a core component of business intelligence. Data warehouses are central repositories of integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating analytical reports for workers throughout the enterprise. This is beneficial for companies as it enables them to interrogate and draw insights from their data and make decisions.
Cross-validation (statistics)Cross-validation, sometimes called rotation estimation or out-of-sample testing, is any of various similar model validation techniques for assessing how the results of a statistical analysis will generalize to an independent data set. Cross-validation is a resampling method that uses different portions of the data to test and train a model on different iterations. It is mainly used in settings where the goal is prediction, and one wants to estimate how accurately a predictive model will perform in practice.
Data managementData management comprises all disciplines related to handling data as a valuable resource. The concept of data management arose in the 1980s as technology moved from sequential processing (first punched cards, then magnetic tape) to random access storage. Since it was now possible to store a discrete fact and quickly access it using random access disk technology, those suggesting that data management was more important than business process management used arguments such as "a customer's home address is stored in 75 (or some other large number) places in our computer systems.
Human impact on the environmentHuman impact on the environment (or anthropogenic environmental impact) refers to changes to biophysical environments and to ecosystems, biodiversity, and natural resources caused directly or indirectly by humans. Modifying the environment to fit the needs of society (as in the built environment) is causing severe effects including global warming, environmental degradation (such as ocean acidification), mass extinction and biodiversity loss, ecological crisis, and ecological collapse.
Data modelA data model is an abstract model that organizes elements of data and standardizes how they relate to one another and to the properties of real-world entities. For instance, a data model may specify that the data element representing a car be composed of a number of other elements which, in turn, represent the color and size of the car and define its owner. The corresponding professional activity is called generally data modeling or, more specifically, database design.
