See also: Row space. Categorical variable: see Qualitative variable. The EWMA is usually used as a control charting technique in MSPC. Time series data: A sequence of measurements taken at different times, and often, but not necessarily at equally spaced intervals. A failover is when functions of a system are automatically transferred to a secondary system when the primary system encounters a failure. This is a term used to describe a particular profession pursued by humans that enable them to do administrative, technical or creative work from the comforts of their house or other remote locations. Here are some common terms used in data analytics. Bilinear modeling: Matrices modeled as a product of two low rank matrices, e.g. Mode: In a set of numbers, the value that occurs most often. Algorithm. Singular value decomposition: See: Principal component analysis. A variable refers to a numeric value, characteristic or quantity which increases or decreses based on the situation. They don't define how the solution will solve the problem technically or specifically; that happens later. Projection methods: A group of methods that can efficiently extract the information inherent in MVD. Regular Expressions are essntially defined as character sequences that help in pattern matching with strings in order to define a search pattern. Phase iterations: The modelling and monitoring of complex phases that can happen more than once or be split and then merged again. Solution requirements in a business analysis specify the conditions and capabilities a solution has to have in order to meet the need or solve the problem and provide clarity around delivery needs. The observations are sometimes called objects, samples, case or items. A fiscal year, or financial year, is a specific period used for accounting and tax purposes. Dimensions is used in terms of measurements, to measure the overall extent or quantity of a particular object. Each observation vector is represented as a point in that space. This is a machine learning method which uses sophisticated mathematical modeling to process data in complex ways. This is equivalent to the length of a principal diameter of the data. Phase: A part of the process that has a specific chemical or physical interpretation. Intelligence refers to the ability to understand concepts, make judgements and apply knowledge gained. Virtual Personal Assistants (VPA) - Enabled Wireless Speakers are wireless devices or applications that use artificial intelligence and simulates commands and conversations prompted by a human being. It is one of the big data terms that define a big data career. Data transformation is the process to convert data from one form to the other. Inflation is when the price of commodities increases while the purchasing value of money decreases. The degree of elongation or diminution is expressed by the eigenvalue. Score vector: Observation coordinates along a PC or PLS component axis. Outliers: Extreme values that might be errors in measurement and recording, or might be accurate reports of rare events. Even the term “data science” can be somewhat nebulous, and as the field gains popularity it seems to lose definition. In such an analysis, each variable is a data set is carefully explored and summarised. 0 (zero) is both a number and the numerical digit used to represent that number in numerals. It bears various aesthetic factors in mind including layout, content and graphics. A value of a variable which unspecified, mysterious or arbitrary is an Unknown Variable. This term is used to bearing artificial intelligence in mind and using it as a service. Cognitive Computing are computerised models that simulate the thought processes of humans in order to find solutions to complex problems. Also sub-divided into Initial conditions & Final conditions. The variables can be independant (not influencing each other) or dependant (having an impact on each other). Knowledge Graph is a knowledge base used by Google for the enhancement of its search engine's results with information gathered from a variety of sources. Bi variant is a mathematical system that contains two independent variables. It refers to a value where a certain percentage of scores fall below that number. Ad Hoc Query. Image recognition is the ability of computer technology to identify people, places, animals, objects and written figures. Event stream processing or ESP, is a kind of technology designed to assist the construction of event-driven information systems. It is an open source processing engine built around speed, ease of use, and analytics. In analysis of data, an anomaly is also known as an outlier. This AI technology is mostly used by enterprises and organisations mostly related to better engagement with customers. MMM uses multiple regression on sales and marketing time series data which helps in identifying its impact and future. In other words, it is a software for artificial intelligence workers. ANOVA stands for Analysis of Variance. Big Data includes so many specialized terms that it’s hard to know where to begin. Demystifying Big Data Analytics: Glossary of Terms Part 1. An algorithm is a set of specified rules, a defined procedure or formula, that is used to solve problems. It functions on the principle of find an alternative despite contraints all done at minimal cost and time. Consumer analytics includes processes that gather large volumes of customer data. In other words, the machine learns from the training data set just like how a teacher would supervise the learning process of a student. The term ‘data analytics’ (or ‘DA’) is part of our analytics consulting service and it is generally used to define the process of using an algorithmic or mechanical process to derive insights that can then be leveraged from a business-like perspective; it represents one of the first steps within our Performance Management service, … Spectral filters: Pretreatment of data per observation specifically aimed at spectral type of data. Open CV (Open Computer Vision) is one of the most popular open source library for real-time computer vision and machine learning. … Analogous to MSPC (multivariate statistical process control) and its control charting techniques applied to a continuous process. Unit: A production vessel, or reactor, where raw material are processed. MOCA, Multiblock Orthogonal Component Analysis: Generalization of OPLS to cover multiple blocks of data and search for their joint and unique variablities. Using data analytics, companies can be better equipped to make strategic decisions and increase their turnover. This is used to track the movement and progress of each of the data points. For example, blood pressure could be deemed to respond to changes in age. Local centering: A way to realign variables that are drifting. It appears as multiple overlapping closed curves which is used to organise information visually. Unlike Amazon’s Web Services, it is free for small … This term is refered to as finding the best course of action bearing a situation in mind. Lead for Data Analytics. See: Predictor. Come on guys, give me a break, Dirty data is data that is not clean or in other words inaccurate, duplicated and inconsistent data. Think of it as the top-level folder that you access using your login details. Heterogenous refers to items or substances that are different from each other. 11. A Robotic Process Automation Software is a type of technology that enables anybody to configure computer software, or a “robot” to emulate and integrate the actions of a human interacting within digital systems to execute a business process. Phase iteration conditions: Phase iteration conditions pertain to the whole phase iteration and are therefore used in the batch level model. It is used in terms of an unadjusted rate or the change in value. Jack-knifing: A method for finding the confidence interval of an estimated model parameter, by iteratively keeping out parts of the underlying data, making estimates from the subsets and comparing these estimates. Partial least squares (PLS) regression: A statistical technique that combines features from principal component analysis and multiple regression, but instead of finding hyperplanes of maximum variance between the dependent and independent variables, it finds a linear regression model by projecting the predicted variables and the observable variables to a new lower-dimensioned space. Expresses the row-wise residual standard deviation as a distance measure to the model for that particular observation (row). COST (change-one-separate-factor-at-a-time) approach: Also called OVAT (one-variable-at-a-time) or OFAT (one-factor-at-a-time), this is an intuitive method of  “eye-balling” data to determine which factors may be influencing each other by calculating their average and standard deviation one at a time (an inefficient and error-prone method). It's a business-driven approach that helps in capitalizing at the right time based on current trends. Outer vector product: Product of two vectors that produces a matrix: M = t * p' where mij = ti * pj. Big data describes a large set of data that is continuously growing. Marketing Mix Modeling MMM uses multiple regression on sales and marketing time series data which helps in … Virtual Reality refers to a simulated environment created using computer technology, where the user is simply immersed inside the experience. Discriminant analysis: A statistical analysis technique used to predict class membership from labeled data. A control charting technique used in multivariate statistical process control (MSPC) applications. Discrete data Big Data is one of those emerging concepts. Least squares estimate: A method to estimate model parameters by minimizing the sum of squares of the differences between the actual response value and the value predicted by the model. 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