Data analytics: The process of examining large data sets to uncover hidden patterns, unknown correlations, trends, customer preferences and other useful business insights. Local centering: A way to realign variables that are drifting. After this video, you will be able to describe what a feature is, and how it relates to a sample. Every few years, there comes a ground-breaking concept that car dealers get hooked onto and eventually swear by. Such methods are efficient for pattern recognition, classification, and predictions. By continuing on our website, you are agreeing to the use of cookies. Batch conditions: Batch conditions pertain to the whole batch and are therefore used in the batch level model (BLM). "Branding is a term used in marketing to describe the process of creating a name, logo, color scheme, etc. 12 December 2017. Ensemble Learning is a paradigm of machine learning wherein multiple learners are trained to solve a particular problem. Analogous to MSPC (multivariate statistical process control) and its control charting techniques applied to a continuous process. Dip your toe into the data pool with this glossary of data-related terms. The data is diverse and can include structured, semi-structured and unstructured data, which can be used for machine learning and advanced analytics. Augmented Reality (AR) is the combination of a real external environment with computer-generated scenes to creare an enhanced experience of the world in real time. An extreme value could be either a minimum value or a maximum value in a data set. Best basis: Best basis is an option used in wavelet transformation for high frequency signals. Wavelets: Small oscillating wave functions that are used for data filtering or data compression. An exponent indicates how many times a certain number needs to be multiplied by that number. Latent variable: Variables that are not directly observed but are rather inferred (through a mathematical model) from other variables that are observed (directly measured). PDF or Portable Document Format (PDF) is a multi-platform document format used for saving publications or documents in a standard way, making it easy to view and share. Nominal may refer to a value of something before it is changed. Insights gained through descriptive analytics can provide useful insights that can be used for future analysis. For example, the 20th quantile is the value at which 20% of values are smaller. Based on this, companies can identify gaps in current processes and chart out a strategy to achieve the set targets. Data analytics: The process of examining large data sets to uncover hidden patterns, unknown correlations, trends, customer preferences and other useful business insights. Collinearity is a statistical term for when two or more data points have a linear relationship. In the Observations page of the Workset dialog the identifiers can be used to set classes. M-space: Measurement space, or: multivariate space. Dataset: A dataset is the base of all multivariate data analysis, often also called a data matrix. In other words, PaaS is short form for platform-as-a-service often used by companies for their data and marketing. It's a business-driven approach that helps in capitalizing at the right time based on current trends. SCCL . It also balances the load by automatically connecting users to servers that have the least load. An arithmetic mean is the average of all values in a data set. Model management: The method to trace, track, and version models that represent a system. A Data Lake is a system that stores data in its raw format. This procedure is used to corroborate that what is seen in model parameters is indeed expressed or encoded in the underlying data. A binomial can be defined as a polynomial with two terms. Block-wise variable scaling: Making the total variance equal for each block of similar variables in a dataset. Training dataset: See: Reference dataset. CUSUM: CUmulative SUM. This is done using high-tech pattern recognition methodologies. It assumes a one-way causal effect from predictor variables (independent variables) to a response of another variable (dependent variable). Can for instance calculate derivatives or remove the average per row. The act of making a map. Can for instance calculate derivatives or wavelets per column. The data analyst is responsible for collecting, processing, and performing statistical analysis of data. Extreme values are found using a multiplier of the interquantile range, the distance between two specified quantiles. Residual: Left-over; un-modeled part. Sensitivity is a statistical term used to measure the proportion of samples that are positive. Client/server application: An application architecture where calculations are done in a central server and the results can be displayed one or more clients that connect to the server. Term Definition ; Adjusted meeting hours: An adjustment is applied so that overlapping time is not double-counted when a person has overlapping meeting hours. Data modeling is the process of creating a data model for the data to be stored in a Database. Instead, computers access data and learn patterns in order to perform tasks. Sampling takes less time as it uses a defined procedure and helps in inferring the characteristics of a population. Real-time data processing: Real time data processing involves a continual input, process and output of data and allows an organization to take action right away. Outliers: Extreme values that might be errors in measurement and recording, or might be accurate reports of rare events. Batch evolution model (BEM): A regression model of how a batch process evolves over time or maturity. IoT (Internet of Things) is the network of interrelated physical devices that are connected to the internet, possess unique identifiers and can transfer data through the network independently. Analytics, Business analytics, Predictive modelling, Advanced analytics, Big Data Analytics, Data Mining, Knowledge Discovery, Artificial Intelligence, Machine learning, Business Intelligence, OLAP, Reporting, Data warehousing, Statistics There are many terms that get thrown around in the field of analytics. Data transformation is the process to convert data from one form to the other. Input variables / output variables: Input variables are the factor (X) values and output variables are the responses (Y) in data analytics. It functions based on what it has learned about how humans would generally behave and communicate. Think of it as the top-level folder that you access using your login details. Discrete data: Data that exist sporadically during production, such as laboratory data (IPC, at-line or daily data). A conversion rate is the percentage of how many viewers completed a specific action on a website versus the total number of website visitors. Model: A mathematical expression that describes relationships among variables in a historical data set to estimate or classify the data. Multidimensional scaling: Roughly corresponding to a principal component analysis of a matrix of ‘distances’ between observations. This glossary excludes query metric definitions. Test dataset: A dataset with unknown properties, often subjected to projections to models. Principal component analysis: A technique used to provide an overview of the information in a dataset. The Quantile Range Outliers method of outlier detection uses the quantile distribution of the values in a column to locate the extreme values. Text Analytics is the process of drawing meaning out of written communications, often used in the context of enhaving customer experience. Temporal is related to the concept of time, associated with a sequence of time or to a particular time. Predictive Modelling is the act of using given data in order predict its outcome and future behaviour. Intelligence refers to the ability to understand concepts, make judgements and apply knowledge gained. Standard deviation: The square root of the variance, and a common way to indicate just how different a particular measurement is from the mean. MA model: Moving Average model. Median: When values are size-sorted, the value in the middle. NLP or Natural Language Processing is a subfield of linguistics, computer science, information engineering, and artificial intelligence that focuses on the interactions between computers and human languages. Guided Analytics in data science is essentially the process of guiding the end user through the same analytics workflow, by exposing only the parameters of interest and through a comfortable sequence of web pages. EWMA model: Exponentially Weighted Moving Average model. Column space: Space spanned by the column vectors of a matrix. Chief Data Science Officer. An autonomous vehicle is one that can drive itself from a starting point to a pre-determined destination in autopilot mode using various technologies. Inflation is when the price of commodities increases while the purchasing value of money decreases. It functions on the principle of find an alternative despite contraints all done at minimal cost and time. This concept is applied to API or Application Program Interface thus creating an API Marketplace. This term is used to determine the strength and direction between objects in a graph. Discriminant analysis: A statistical analysis technique used to predict class membership from labeled data. ANOVA stands for Analysis of Variance. It can be measured or qualitative too. If you have been in a conversation on machine learning, you have probably heard terms like feature, sample, and variable. Quality Assurance involves ensuring mistakes and defects are prevented, problems are solved and the quality is under control. Data analysis Processing, interpretation and analysis of findings. We help companies drive digital transformation by helping them combine digital and traditional data to gain a competitive advantage. Gap analysis is a method that helps companies identify their current state and goals for the future. Comparitive analytics is the process of comparing two or more options (this can include processes, data, products, etc) to make an informed decision. Data Analyst: A person responsible for the tasks of modelling, preparing and cleaning data for the purpose of deriving actionable information from it. The observations are sometimes called objects, samples, case or items. Arithmetic is a branch of mathematics that includes numerical calculations based on specific operations. This greatly reduces the time required for statistical analysis. Predictive Analytics is term used when information from the given data is taken into account in order to determine its future outcomes and trends. Solutions Review has compiled the most comprehensive Business Intelligence and Data Analytics glossary of terms available on the web. Any observation point inside this limit is well explained by the model. A control charting technique used in multivariate statistical process control (MSPC) applications. T his is almost a complete glossary of Big Data terminology widely used today. Decision Management refers to a type of business management that looks at aspects such as designing, building, and managing automated decision-making systems that organisations use in order to stay connected to customers, vendors, suppliers, employees, etc. Skewness is the asymmetery or lack of symmetery found in data distributions. Glossary of Key Data Analysis Terms Levels of data Nominal Variable - A variable determined by categories which cannot be ordered, e.g., gender and color. what makes it good enough to use). Statistically, deviance refers to the variance of a statistic in comparison with the overall statistical model. A mathematical term, univariate is used to describe data which consists of observations based on a single characteristic. It generates a data model which is made by analysing historical data and current data. We will be defining some of those terms in this lecture. Normal Distribution is term used in probablity theory that refers to real-valued random variables whose distribution is unknown. It covers the most important topics you need to know to master data and analytics, and goes beyond a traditional glossary in that it shows how the terms relate to each other. Has compiled the most comprehensive Business intelligence and data Analytics glossary of terms available on the.! Times a certain number needs to be stored in a column to locate the extreme values that be! Platform-As-A-Service often used by companies for their data and learn patterns in order predict data analytics terms glossary outcome and future.. Point to a continuous process an extreme value could be either a minimum value or a maximum value in underlying. Or data compression sometimes called objects, samples, case or items spanned. Information from the given data in order to perform tasks term, univariate is used to set classes their state! 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