Business analyticsBusiness analytics (BA) refers to the skills, technologies, and practices for iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods. In contrast, business intelligence traditionally focuses on using a consistent set of metrics to both measure past performance and guide business planning.
Modeling and simulationModeling and simulation (M&S) is the use of models (e.g., physical, mathematical, behavioral, or logical representation of a system, entity, phenomenon, or process) as a basis for simulations to develop data utilized for managerial or technical decision making. In the computer application of modeling and simulation a computer is used to build a mathematical model which contains key parameters of the physical model. The mathematical model represents the physical model in virtual form, and conditions are applied that set up the experiment of interest.
AnalyticsAnalytics 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.
Predictive analyticsPredictive analytics is a form of business analytics applying machine learning to generate a predictive model for certain business applications. As such, it encompasses a variety of statistical techniques from predictive modeling and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events. It represents a major subset of machine learning applications; in some contexts, it is synonymous with machine learning.
Indicative planningIndicative planning is a form of economic planning implemented by a state in an effort to solve the problem of imperfect information in market economies by coordination of private and public investment through forecasts and output targets. The resulting plans aim to supply economically valuable information as a public good that the market by itself cannot disseminate, or where forward markets are nonexistent. However, indicative planning takes only endogenous market uncertainty into account, plans the economy accordingly, and does not look into exogenous uncertainty like technology, foreign trade, etc.
Systems development life cycleIn systems engineering, information systems and software engineering, the systems development life cycle (SDLC), also referred to as the application development life cycle, is a process for planning, creating, testing, and deploying an information system. The SDLC concept applies to a range of hardware and software configurations, as a system can be composed of hardware only, software only, or a combination of both. There are usually six stages in this cycle: requirement analysis, design, development and testing, implementation, documentation, and evaluation.
Online analytical processingOnline analytical processing, or OLAP (ˈoʊlæp), is an approach to answer multi-dimensional analytical (MDA) queries swiftly in computing. OLAP is part of the broader category of business intelligence, which also encompasses relational databases, report writing and data mining. Typical applications of OLAP include business reporting for sales, marketing, management reporting, business process management (BPM), budgeting and forecasting, financial reporting and similar areas, with new applications emerging, such as agriculture.
Planned economyA planned economy is a type of economic system where the distribution of goods and services or the investment, production and the allocation of capital goods takes place according to economic plans that are either economy-wide or limited to a category of goods and services. A planned economy may use centralized, decentralized, participatory or Soviet-type forms of economic planning. The level of centralization or decentralization in decision-making and participation depends on the specific type of planning mechanism employed.
Analytical MarxismAnalytical Marxism is an academic school of Marxist theory which emerged in the late 1970s, largely prompted by G. A. Cohen's Karl Marx's Theory of History: A Defence (1978). In this book, Cohen drew on the Anglo–American tradition of analytic philosophy in an attempt to raise the standards of clarity and rigor within Marxist theory, which led to his distancing of Marxism from continental European philosophy. Analytical Marxism rejects much of the Hegelian and dialectical tradition associated with Marx's thought.
Deep learningDeep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective "deep" in deep learning refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.
Iterative and incremental developmentIterative and incremental development is any combination of both iterative design or iterative method and incremental build model for development. Usage of the term began in software development, with a long-standing combination of the two terms iterative and incremental having been widely suggested for large development efforts. For example, the 1985 DOD-STD-2167 mentions (in section 4.1.2): "During software development, more than one iteration of the software development cycle may be in progress at the same time.
Telescopic sightA telescopic sight, commonly called a scope informally, is an optical sighting device based on a refracting telescope. It is equipped with some form of a referencing pattern – known as a reticle – mounted in a focally appropriate position in its optical system to provide an accurate point of aim. Telescopic sights are used with all types of systems that require magnification in addition to reliable visual aiming, as opposed to non-magnifying iron sights, reflector (reflex) sights, holographic sights or laser sights, and are most commonly found on long-barrel firearms, particularly rifles, usually via a scope mount.
