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In-database Processing
In-database processing, sometimes referred to as in-database analytics, refers to the integration of data analytics into data warehousing functionality. Today, many large databases, such as those used for credit card fraud detection and investment bank risk management, use this technology because it provides significant performance improvements over traditional methods. History Traditional approaches to data analysis require data to be moved out of the database into a separate analytics environment for processing, and then back to the database. (SPSS from IBM are examples of tools that still do this today). Doing the analysis in the database, where the data resides, eliminates the costs, time and security issues associated with the old approach by doing the processing in the data warehouse itself. Though in-database capabilities were first commercially offered in the mid-1990s, as object-related database systems from vendors including IBM, Illustra/Informix (now IBM) and Oracle, t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Analytics
Analytics 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. Specifically, areas within analytics include descriptive analytics, diagnostic analytics, predictive analytics, prescriptive analytics, and cognitive analytics. Analytics may apply to a variety of fields such as marketing, management, finance, online systems, information security, and software services. Since analytics can require extensive computation (see big data), the algorithms and software used for analytics harness the most current methods ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Aster Data Systems
Aster Data Systems was a data management and analysis software company headquartered in San Carlos, California. It was founded in 2005 and acquired by Teradata in 2011. History Aster Data was co-founded in 2005 by Stanford University graduate students George Candea, Mayank Bawa and Tasso Argyros. It received funding from First Round Capital, Sequoia Capital, Institutional Venture Partners, Cambrian Ventures, Jafco Ventures as well as angel investors including Rajeev Motwani, Ron Conway and David Cheriton. It received its first round of funding of $5 million in 2005, then a second round of $17 million in February 2009, and third round of $30 million in September 2010. Aster was mentioned in 2010 by Intelligent Enterprise' editor. It was ranked seventh in 2011 of venture-funded companies by ''The Wall Street Journal''. Argyros (Chief Technical Officer at the time) was listed as a technology pioneer of information technologies and new media by the World Economic Forum in 2011. Tera ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Predictive Analytics
Predictive analytics encompasses a variety of statistical techniques from data mining, predictive modeling, and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events. In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding decision-making for candidate transactions. The defining functional effect of these technical approaches is that predictive analytics provides a predictive score (probability) for each individual (customer, employee, healthcare patient, product SKU, vehicle, component, machine, or other organizational unit) in order to determine, inform, or influence organizational processes that pertain across large numbers of individuals, such as in marketing, credit risk assessment, fraud detecti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Massive Parallel Processing
Massively parallel is the term for using a large number of computer processors (or separate computers) to simultaneously perform a set of coordinated computations in parallel. GPUs are massively parallel architecture with tens of thousands of threads. One approach is grid computing, where the processing power of many computers in distributed, diverse administrative domains is opportunistically used whenever a computer is available.''Grid computing: experiment management, tool integration, and scientific workflows'' by Radu Prodan, Thomas Fahringer 2007 pages 1–4 An example is BOINC, a volunteer-based, opportunistic grid system, whereby the grid provides power only on a best effort basis.''Parallel and Distributed Computational Intelligence'' by Francisco Fernández de Vega 2010 pages 65–68 Another approach is grouping many processors in close proximity to each other, as in a computer cluster. In such a centralized system the speed and flexibility of the interconnect b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Shared Nothing Architecture
Shared may refer to: * Sharing * Shared ancestry or Common descent * Shared care * Shared-cost service * Shared decision-making in medicine * Shared delusion, various meanings * Shared government * Shared intelligence or collective intelligence * Shared library * Shared morality * Shared ownership * Shared parenting or shared custody * Shared property * Shared reading * Shared secret * Shared services * Shared universe, in fiction * Shared vision planning, in irrigation * Shared workspace Science and technology * Shared medium, in telecommunication * Shared neutral, in electric circuitry * Shared pair, in chemistry *Shared vertex (or shared corner or common corner), point of contact between polygons, polyhedra, etc. *Shared edge, line of contact between polygons, polyhedra, etc. Computing * Shared agenda, in groupware * Shared computing * Shared desktop * Shared data structure * Shared IP address * Shared memory architecture * Shared memory (interprocess communication) * S ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Parallel Computing
Parallel computing is a type of computation in which many calculations or processes are carried out simultaneously. Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism. Parallelism has long been employed in high-performance computing, but has gained broader interest due to the physical constraints preventing frequency scaling.S.V. Adve ''et al.'' (November 2008)"Parallel Computing Research at Illinois: The UPCRC Agenda" (PDF). Parallel@Illinois, University of Illinois at Urbana-Champaign. "The main techniques for these performance benefits—increased clock frequency and smarter but increasingly complex architectures—are now hitting the so-called power wall. The computer industry has accepted that future performance increases must largely come from increasing the number of processors (or cores) on a die, rather than m ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fuzzy Logix
Introduction Fuzzy Logix develops high -performance analytics solutions for Big Data. Fuzzy Logix offers in-database and GPU-based analytics solutions built on comprehensive and growing libraries of over 600 mathematical, statistical, simulation, data mining, time series and financial models. History Fuzzy Logix was formed in 2007 by Partha Sen and Mike Upchurch who met while working at Bank of America and shared a goal of making analytics pervasive. In 2008 Fuzzy Logix released DB Lytix, the first complete and commercially available library of in-database analytics. FIN Lytix was released in 2010 and was the first comprehensive library of in-database financial models. In 2010, Aperity OEM’d Fuzzy Logix models to run in their analytics and CPG software SaaS solutions. In 2011, Quest{{Cite web , url=http://www.quest.com/news-release/quest-introduces-new-edition-of-toad-for-data-analysts-that-brings-po-092011-815428.aspx , title=Quest Teams with Fuzzy Logix to Deliver a Cos ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
MonetDB
MonetDB is an open-source column-oriented relational database management system (RDBMS) originally developed at the Centrum Wiskunde & Informatica (CWI) in the Netherlands. It is designed to provide high performance on complex queries against large databases, such as combining tables with hundreds of columns and millions of rows. MonetDB has been applied in high-performance applications for online analytical processing, data mining, geographic information system (GIS), Resource Description Framework (RDF), text retrieval and sequence alignment processing. History Data mining projects in the 1990s required improved analytical database support. This resulted in a CWI spin-off called Data Distilleries, which used early MonetDB implementations in its analytical suite. Data Distilleries eventually became a subsidiary of SPSS in 2003, which in turn was acquired by IBM in 2009. MonetDB in its current form was first created in 2002 by doctoral student Peter Boncz and professor Ma ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ParAccel
ParAccel, Inc. was a California-based software company. It provided a database management system designed to provide advanced analytics for business intelligence. ParAccel was acquired by Actian in April 2013. History ParAccel was a venture-backed company focused on developing software for data analysis. It acquired some intellectual property from the company XPrime, which ended operations in 2005. It was officially incorporated in February 2006, founded by Barry Zane who became chief technology officer, Tom Clancey as interim-CEO, and was first funded by angel investors. In August 2006 the first series of venture capital came from Mohr Davidow Ventures, Bay Partners and Tao Venture Partners. In 2007 the company was based in San Diego, California, with an office in Ann Arbor, Michigan. David J. Ehrlich was chief executive, and Bruce Scott, vice president of engineering. In November 2007, a second round of $20 million included previous investors and was led by Walden Ventures. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sybase
Sybase, Inc. was an enterprise software and services company. The company produced software to manage and analyze information in relational databases, with facilities located in California and Massachusetts. Sybase was acquired by SAP in 2010; SAP ceased using the Sybase name in 2014. History *1984: Robert Epstein, Mark Hoffman, Jane Doughty, and Tom Haggin founded Sybase (initially trading as ''Systemware'') in Epstein's home in Berkeley, California. Their first commercial location is half of an office suite at 2107 Dwight Way in Berkeley. They set out to create a relational database management system (RDBMS) that will organize information and make it available to computers within a network. *March 1986: Systemware enters into talks with Microsoft to license Data Server, a database product built to run on UNIX computers. Those talks led to a product called Ashton-Tate/Microsoft SQL Server 1.0, shipping in May 1989. *May 1991: Systemware changes its name to Sybase. *January 19 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Greenplum
Greenplum is a big data technology based on MPP architecture and the Postgres open source database technology. The technology was created by a company of the same name headquartered in San Mateo, California around 2005. Greenplum was acquired by EMC Corporation in July 2010. Starting in 2012, its database management system software became known as the Pivotal Greenplum Database sold through Pivotal Software. Pivotal open sourced the core engine and continued its development by the Greenplum Database open source community and Pivotal. Starting in 2020 Pivotal was acquired by VMware and VMware continued to sponsor the Greenplum Database open source community as well as commercialize the technology under the brand name VMware Tanzu Greenplum. Company Greenplum, the company, was founded in September 2003 by Scott Yara and Luke Lonergan. It was a merger of two smaller companies: Metapa (founded in August 2000 near Los Angeles) and Didera in Fairfax, Virginia. Investors in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
