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Vertica
Vertica Systems is an analytic database management software company. Vertica was founded in 2005 by the database researcher Michael Stonebraker, with Andrew Palmer as the founding CEO. Ralph Breslauer and Christopher P. Lynch served as later CEOs. Lynch joined as chairman and CEO in 2010 and was responsible for Vertica's acquisition by Hewlett Packard in March 2011. The acquisition expanded the HP Software portfolio for enterprise companies and the public sector group. As part of the merger of Micro Focus and the Software division of Hewlett Packard Enterprise, Vertica joined Micro Focus in September, 2017. Products The column-oriented Vertica Analytics Platform was designed to manage large, fast-growing volumes of data and with fast query performance for data warehouses and other query-intensive applications. The product claims to greatly improve query performance over traditional relational database systems, and to provide high availability and exabyte scalability on com ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Michael Stonebraker
Michael Ralph Stonebraker (born October 11, 1943) is a computer scientist specializing in database systems. Through a series of academic prototypes and commercial startups, Stonebraker's research and products are central to many relational databases. He is also the founder of many database companies, including Ingres Corporation, Illustra, Paradigm4, StreamBase SystemsTamr Vertica and VoltDB, and served as chief technical officer of Informix. For his contributions to database research, Stonebraker received the 2014 Turing Award, often described as "the Nobel Prize for computing." Stonebraker's career can be broadly divided into two phases: his time at University of California, Berkeley when he focused on relational database management systems such as Ingres and Postgres, and at Massachusetts Institute of Technology (MIT) where he developed more novel data management techniques such as C-Store, H-Store and SciDB. Stonebraker is currently a professor emeritus at UC Berkeley ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Column-oriented Database
A column-oriented DBMS or columnar DBMS is a database management system (DBMS) that stores data tables by column rather than by row. Benefits include more efficient access to data when only querying a subset of columns (by eliminating the need to read columns that are not relevant), and more options for data compression. However, they are typically less efficient for inserting new data. Practical use of a column store versus a row store differs little in the relational DBMS world. Both columnar and row databases can use traditional database query languages like SQL to load data and perform queries. Both row and columnar databases can become the backbone in a system to serve data for common extract, transform, load (ETL) and tools. Description Background A relational database management system provides data that represents a two-dimensional table of columns and rows. For example, a database might have this table: This simple table includes an employee identifier (EmpId), name ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cambridge, MA
Cambridge ( ) is a city in Middlesex County, Massachusetts, United States. As part of the Boston metropolitan area, the cities population of the 2020 U.S. census was 118,403, making it the fourth most populous city in the state, behind Boston, Worcester, and Springfield. It is one of two de jure county seats of Middlesex County, although the county's executive government was abolished in 1997. Situated directly north of Boston, across the Charles River, it was named in honor of the University of Cambridge in England, once also an important center of the Puritan theology embraced by the town's founders. Harvard University, the Massachusetts Institute of Technology (MIT), Lesley University, and Hult International Business School are in Cambridge, as was Radcliffe College before it merged with Harvard. Kendall Square in Cambridge has been called "the most innovative square mile on the planet" owing to the high concentration of successful startups that have emerged in the vici ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Genus
Genus ( plural genera ) is a taxonomic rank used in the biological classification of living and fossil organisms as well as viruses. In the hierarchy of biological classification, genus comes above species and below family. In binomial nomenclature, the genus name forms the first part of the binomial species name for each species within the genus. :E.g. '' Panthera leo'' (lion) and '' Panthera onca'' (jaguar) are two species within the genus '' Panthera''. ''Panthera'' is a genus within the family Felidae. The composition of a genus is determined by taxonomists. The standards for genus classification are not strictly codified, so different authorities often produce different classifications for genera. There are some general practices used, however, including the idea that a newly defined genus should fulfill these three criteria to be descriptively useful: # monophyly – all descendants of an ancestral taxon are grouped together (i.e. phylogenetic analysis should cl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Commodity Computing
Commodity computing (also known as commodity cluster computing) involves the use of large numbers of already-available computing components for parallel computing, to get the greatest amount of useful computation at low cost. It is computing done in commodity computers as opposed to in high-cost superminicomputers or in boutique computers. Commodity computers are computer systems - manufactured by multiple vendors - incorporating components based on open standards. Characteristics Such systems are said to be based on standardized computer components, since the standardization process promotes lower costs and less differentiation among vendors' products. Standardization and decreased differentiation lower the switching or exit cost from any given vendor, increasing purchasers' leverage and preventing lock-in. A governing principle of commodity computing is that it is preferable to have more low-performance, low-cost hardware working in parallel ( scalar computing) (e.g. AMD x8 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Logistic Regression
In statistics, the logistic model (or logit model) is a statistical model that models the probability of an event taking place by having the log-odds for the event be a linear combination of one or more independent variables. In regression analysis, logistic regression (or logit regression) is estimating the parameters of a logistic model (the coefficients in the linear combination). Formally, in binary logistic regression there is a single binary dependent variable, coded by an indicator variable, where the two values are labeled "0" and "1", while the independent variables can each be a binary variable (two classes, coded by an indicator variable) or a continuous variable (any real value). The corresponding probability of the value labeled "1" can vary between 0 (certainly the value "0") and 1 (certainly the value "1"), hence the labeling; the function that converts log-odds to probability is the logistic function, hence the name. The unit of measurement for the log-odds ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Linear Regression
In statistics, linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables). The case of one explanatory variable is called '' simple linear regression''; for more than one, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable. In linear regression, the relationships are modeled using linear predictor functions whose unknown model parameters are estimated from the data. Such models are called linear models. Most commonly, the conditional mean of the response given the values of the explanatory variables (or predictors) is assumed to be an affine function of those values; less commonly, the conditional median or some other quantile is used. Like all forms of regression analysis, linear regression focuse ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Outline Of Machine Learning
The following outline is provided as an overview of and topical guide to machine learning. Machine learning is a subfield of soft computing within computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence.http://www.britannica.com/EBchecked/topic/1116194/machine-learning In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. Such algorithms operate by building a model from an example training set of input observations in order to make data-driven predictions or decisions expressed as outputs, rather than following strictly static program instructions. What ''type'' of thing is machine learning? * An academic discipline * A branch of science ** An applied science *** A subfield of computer science ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Geospatial Analysis
Spatial analysis or spatial statistics includes any of the formal techniques which studies entities using their topological, geometric, or geographic properties. Spatial analysis includes a variety of techniques, many still in their early development, using different analytic approaches and applied in fields as diverse as astronomy, with its studies of the placement of galaxies in the cosmos, to chip fabrication engineering, with its use of "place and route" algorithms to build complex wiring structures. In a more restricted sense, spatial analysis is the technique applied to structures at the human scale, most notably in the analysis of geographic data or transcriptomics data. Complex issues arise in spatial analysis, many of which are neither clearly defined nor completely resolved, but form the basis for current research. The most fundamental of these is the problem of defining the spatial location of the entities being studied. Classification of the techniques of spatial ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Regression Analysis
In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the 'outcome' or 'response' variable, or a 'label' in machine learning parlance) and one or more independent variables (often called 'predictors', 'covariates', 'explanatory variables' or 'features'). The most common form of regression analysis is linear regression, in which one finds the line (or a more complex linear combination) that most closely fits the data according to a specific mathematical criterion. For example, the method of ordinary least squares computes the unique line (or hyperplane) that minimizes the sum of squared differences between the true data and that line (or hyperplane). For specific mathematical reasons (see linear regression), this allows the researcher to estimate the conditional expectation (or population average value) of the dependent variable when the independent variables take on a give ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Pattern Matching
In computer science, pattern matching is the act of checking a given sequence of tokens for the presence of the constituents of some pattern. In contrast to pattern recognition, the match usually has to be exact: "either it will or will not be a match." The patterns generally have the form of either sequences or tree structures. Uses of pattern matching include outputting the locations (if any) of a pattern within a token sequence, to output some component of the matched pattern, and to substitute the matching pattern with some other token sequence (i.e., search and replace). Sequence patterns (e.g., a text string) are often described using regular expressions and matched using techniques such as backtracking. Tree patterns are used in some programming languages as a general tool to process data based on its structure, e.g. C#, F#, Haskell, ML, Python, Ruby, Rust, Scala, Swift and the symbolic mathematics language Mathematica have special syntax for expressing tree p ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Interpolation
In the mathematical field of numerical analysis, interpolation is a type of estimation, a method of constructing (finding) new data points based on the range of a discrete set of known data points. In engineering and science, one often has a number of data points, obtained by sampling or experimentation, which represent the values of a function for a limited number of values of the independent variable. It is often required to interpolate; that is, estimate the value of that function for an intermediate value of the independent variable. A closely related problem is the approximation of a complicated function by a simple function. Suppose the formula for some given function is known, but too complicated to evaluate efficiently. A few data points from the original function can be interpolated to produce a simpler function which is still fairly close to the original. The resulting gain in simplicity may outweigh the loss from interpolation error and give better performance ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
