Customer relationship management (CRM) is a process in which a business or other organization administers its interactions with customers, typically using data analysis to study large amounts of information.
Enterprise resource planning (ERP) is the integrated management of main business processes, often in real time and mediated by software and technology. ERP is usually referred to as a category of business management software—typically a suite of integrated applications—that an organization can use to collect, store, manage and interpret data from many business activities. ERP systems can be local based or cloud-based. Cloud-based applications have grown in recent years due to information being readily available from any location with Internet access. Traditional on-premises ERP systems are now considered legacy technology.
Business intelligence (BI) comprises the strategies and technologies used by enterprises for the data analysis and management of business information. Common functions of business intelligence technologies include reporting, online analytical processing, analytics, dashboard development, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics, and prescriptive analytics.
A management information system (MIS) is an information system used for decision-making, and for the coordination, control, analysis, and visualization of information in an organization. The study of the management information systems involves people, processes and technology in an organizational context.
An information system (IS) is a formal, sociotechnical, organizational system designed to collect, process, store, and distribute information. From a sociotechnical perspective, information systems are composed by four components: task, people, structure, and technology. Information systems can be defined as an integration of components for collection, storage and processing of data of which the data is used to provide information, contribute to knowledge as well as digital products that facilitate decision making.
A decision support system (DSS) is an information system that supports business or organizational decision-making activities. DSSs serve the management, operations and planning levels of an organization and help people make decisions about problems that may be rapidly changing and not easily specified in advance—i.e. unstructured and semi-structured decision problems. Decision support systems can be either fully computerized or human-powered, or a combination of both.
Information technology management or IT management is the discipline whereby all of the information technology resources of a firm are managed in accordance with its needs and priorities. Managing the responsibility within a company entails many of the basic management functions, like budgeting, staffing, change management, and organizing and controlling, along with other aspects that are unique to technology, like software design, network planning, tech support etc.
Business rules are abstractions of the policies and practices of a business organization. In computer software development, the business rules approach is a development methodology where rules are in a form that is used by, but does not have to be embedded in, business process management systems.
Lean software development is a translation of lean manufacturing principles and practices to the software development domain. Adapted from the Toyota Production System, it is emerging with the support of a pro-lean subculture within the agile community. Lean offers a solid conceptual framework, values and principles, as well as good practices, derived from experience, that support agile organizations.
StatSoft is the original developer of Statistica. Dell acquired it in March 2014. Statistica is an analytics software portfolio that provides enterprise and desktop software for statistics, data analysis, data management, data visualization, data mining, which is also called predictive analytics, and quality control.
Decision management, also known as enterprise decision management (EDM) or business decision management (BDM) entails all aspects of designing, building and managing the automated decision-making systems that an organization uses to manage its interactions with customers, employees and suppliers. Computerization has changed the way organizations are approaching their decision-making because it requires that they automate more decisions, to handle response times and unattended operation required by computerization, and because it has enabled "information-based decisions" – decisions based on analysis of historical behavioral data, prior decisions, and their outcomes.
Operational intelligence (OI) is a category of real-time dynamic, business analytics that delivers visibility and insight into data, streaming events and business operations. OI solutions run queries against streaming data feeds and event data to deliver analytic results as operational instructions. OI provides organizations the ability to make decisions and immediately act on these analytic insights, through manual or automated actions.
Business analytics (BA) refers to the skills, technologies, and practices for continuous 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. In other words, business intelligence focusses on description, while business analytics focusses on prediction and prescription.
A network-centric organization is a network governance pattern which empowers knowledge workers to create and leverage information to increase competitive advantage through the collaboration of small and agile self-directed teams. It is emerging in many progressive 21st century enterprises. This implies new ways of working, with consequences for the enterprise’s infrastructure, processes, people and culture.
An intelligent decision support system (IDSS) is a decision support system that makes extensive use of artificial intelligence (AI) techniques. Use of AI techniques in management information systems has a long history – indeed terms such as "Knowledge-based systems" (KBS) and "intelligent systems" have been used since the early 1980s to describe components of management systems, but the term "Intelligent decision support system" is thought to originate with Clyde Holsapple and Andrew Whinston in the late 1970s. Examples of specialized intelligent decision support systems include Flexible manufacturing systems (FMS), intelligent marketing decision support systems and medical diagnosis systems.
Business process management (BPM) is the discipline in which people use various methods to discover, model, analyze, measure, improve, optimize, and automate business processes. Any combination of methods used to manage a company's business processes is BPM. Processes can be structured and repeatable or unstructured and variable. Though not required, enabling technologies are often used with BPM.
Forest informatics is the combined science of Forestry and informatics, with a special emphasis on collection, management, and processing of data, information and knowledge, and the incorporation of informatic concepts and theories specific to enrich forest management and forest science; it has a similar relationship to library science and information science.
Collaborative decision-making (CDM) software is a software application or module that helps to coordinate and disseminate data and reach consensus among work groups.
Ephraim R. McLean is an American organizational theorist, and Professor of Information Systems at the J. Mack Robinson College of Business, known as one of the founders of the MIS discipline in the 1960s and for his work with William H. DeLone on the information systems success model.
ModelOps, as defined by Gartner, "is focused primarily on the governance and life cycle management of a wide range of operationalized artificial intelligence (AI) and decision models, including machine learning, knowledge graphs, rules, optimization, linguistic and agent-based models". “ModelOps lies at the heart of any enterprise AI strategy”. It orchestrates the model life cycles of all models in production across the entire enterprise, from putting a model into production, then evaluating and updating the resulting application according to a set of governance rules, including both technical and business KPI's. It grants business domain experts the capability to evaluate AI models in production, independent of data scientists.
