DataIn common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.
Data analysisData analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively.
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.
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.
Scientific methodThe scientific method is an empirical method for acquiring knowledge that has characterized the development of science since at least the 17th century (with notable practitioners in previous centuries; see the article history of scientific method for additional detail.) It involves careful observation, applying rigorous skepticism about what is observed, given that cognitive assumptions can distort how one interprets the observation.
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.
WorkflowA workflow consists of an orchestrated and repeatable pattern of activity, enabled by the systematic organization of resources into processes that transform materials, provide services, or process information. It can be depicted as a sequence of operations, the work of a person or group, the work of an organization of staff, or one or more simple or complex mechanisms. From a more abstract or higher-level perspective, workflow may be considered a view or representation of real work.
Computational scienceComputational science, also known as scientific computing, technical computing or scientific computation (SC), is a division of science that uses advanced computing capabilities to understand and solve complex physical problems. This includes Algorithms (numerical and non-numerical): mathematical models, computational models, and computer simulations developed to solve sciences (e.
Concurrent computingConcurrent computing is a form of computing in which several computations are executed concurrently—during overlapping time periods—instead of sequentially—with one completing before the next starts. This is a property of a system—whether a program, computer, or a network—where there is a separate execution point or "thread of control" for each process. A concurrent system is one where a computation can advance without waiting for all other computations to complete. Concurrent computing is a form of modular programming.
LaptopA laptop computer or notebook computer, also known as a laptop or notebook for short, is a small, portable personal computer (PC). Laptops typically have a clamshell form factor with a flat panel screen (usually in diagonal size) on the inside of the upper lid and an alphanumeric keyboard and pointing device (such as a trackpad and/or trackpoint) on the inside of the lower lid, although 2-in-1 PCs with a detachable keyboard are often marketed as laptops or as having a "laptop mode".
Workflow management systemA workflow management system (WfMS or WFMS) provides an infrastructure for the set-up, performance and monitoring of a defined sequence of tasks, arranged as a workflow application. There are several international standards-setting bodies in the field of workflow management: Workflow Management Coalition World Wide Web Consortium Organization for the Advancement of Structured Information Standards WS-BPEL 2.0 (integration-centric) and WS-BPEL4People (human task-centric) published by OASIS Standards Body.
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.
Scientific workflow systemA scientific workflow system is a specialized form of a workflow management system designed specifically to compose and execute a series of computational or data manipulation steps, or workflow, in a scientific application. Distributed scientists can collaborate on conducting large scale scientific experiments and knowledge discovery applications using distributed systems of computing resources, data sets, and devices. Scientific workflow systems play an important role in enabling this vision.
Workflow engineA workflow engine is a software application that manages business processes. It is a key component in workflow technology and typically makes use of a database server. A workflow engine manages and monitors the state of activities in a workflow, such as the processing and approval of a loan application form, and determines which new activity to transition to according to defined processes (workflows). The actions may be anything from saving an application form in a document management system to sending a reminder e-mail to users or escalating overdue items to management.
Job Control LanguageJob Control Language (JCL) is a name for scripting languages used on IBM mainframe operating systems to instruct the system on how to run a batch job or start a subsystem. The purpose of JCL is to say which programs to run, using which files or devices for input or output, and at times to also indicate under what conditions to skip a step. Parameters in the JCL can also provide accounting information for tracking the resources used by a job as well as which machine the job should run on.
ScienceScience is a rigorous, systematic endeavor that builds and organizes knowledge in the form of testable explanations and predictions about the universe. Modern science is typically divided into three major branches: natural sciences (e.g., biology, chemistry, and physics), which study the physical world; the social sciences (e.g., economics, psychology, and sociology), which study individuals and societies; and the formal sciences (e.g., logic, mathematics, and theoretical computer science), which study formal systems, governed by axioms and rules.
SupercomputerA supercomputer is a computer with a high level of performance as compared to a general-purpose computer. The performance of a supercomputer is commonly measured in floating-point operations per second (FLOPS) instead of million instructions per second (MIPS). Since 2017, there have existed supercomputers which can perform over 1017 FLOPS (a hundred quadrillion FLOPS, 100 petaFLOPS or 100 PFLOPS). For comparison, a desktop computer has performance in the range of hundreds of gigaFLOPS (1011) to tens of teraFLOPS (1013).
One Laptop per ChildOne Laptop per Child (OLPC) was a non-profit initiative established with the goal of transforming education for children around the world; this goal was to be achieved by creating and distributing educational devices for the developing world, and by creating software and content for those devices. When the program launched in 2005, the typical retail price for a laptop was considerably in excess of $1,000 (US), so achieving this objective required bringing a low-cost machine to production.
Paradigm shiftA paradigm shift is a fundamental change in the basic concepts and experimental practices of a . It is a concept in the philosophy of science that was introduced and brought into the common lexicon by the American physicist and philosopher Thomas Kuhn. Even though Kuhn restricted the use of the term to the natural sciences, the concept of a paradigm shift has also been used in numerous non-scientific contexts to describe a profound change in a fundamental model or perception of events.
ReproducibilityReproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method. For the findings of a study to be reproducible means that results obtained by an experiment or an observational study or in a statistical analysis of a data set should be achieved again with a high degree of reliability when the study is replicated. There are different kinds of replication but typically replication studies involve different researchers using the same methodology.
