Computerized maintenance management systemA computerized maintenance management system (CMMS) is any software package that maintains a computer database of information about an organization's maintenance operations. This information is intended to help maintenance workers do their jobs more effectively (for example, determining which machines require maintenance and which storerooms contain the spare parts they need) and to help management make informed decisions (for example, calculating the cost of machine breakdown repair versus preventive maintenance for each machine, possibly leading to better allocation of resources).
Open dataOpen data is data that is openly accessible, exploitable, editable and shared by anyone for any purpose. Open data is licensed under an open license. The goals of the open data movement are similar to those of other "open(-source)" movements such as open-source software, open-source hardware, open content, open specifications, open education, open educational resources, open government, open knowledge, open access, open science, and the open web. The growth of the open data movement is paralleled by a rise in intellectual property rights.
Data qualityData quality refers to the state of qualitative or quantitative pieces of information. There are many definitions of data quality, but data is generally considered high quality if it is "fit for [its] intended uses in operations, decision making and planning". Moreover, data is deemed of high quality if it correctly represents the real-world construct to which it refers. Furthermore, apart from these definitions, as the number of data sources increases, the question of internal data consistency becomes significant, regardless of fitness for use for any particular external purpose.
Stream processingIn computer science, stream processing (also known as event stream processing, data stream processing, or distributed stream processing) is a programming paradigm which views streams, or sequences of events in time, as the central input and output objects of computation. Stream processing encompasses dataflow programming, reactive programming, and distributed data processing. Stream processing systems aim to expose parallel processing for data streams and rely on streaming algorithms for efficient implementation.
Publish–subscribe patternIn software architecture, publish–subscribe is a messaging pattern where publishers categorize messages into classes that are received by subscribers. This is contrasted to the typical messaging pattern model where publishers sends messages directly to a subscribers. Similarly, subscribers express interest in one or more classes and only receive messages that are of interest, without knowledge of which publishers, if any, there are. Publish–subscribe is a sibling of the message queue paradigm, and is typically one part of a larger message-oriented middleware system.
Message queueIn computer science, message queues and mailboxes are software-engineering components typically used for inter-process communication (IPC), or for inter-thread communication within the same process. They use a queue for messaging – the passing of control or of content. Group communication systems provide similar kinds of functionality. The message queue paradigm is a sibling of the publisher/subscriber pattern, and is typically one part of a larger message-oriented middleware system.
Media consumptionMedia consumption or media diet is the sum of information and entertainment media taken in by an individual or group. It includes activities such as interacting with new media, reading books and magazines, watching television and film, and listening to radio. An active media consumer must have the capacity for skepticism, judgement, free thinking, questioning, and understanding.Media consumption is to maximize the interests of consumers. For as long as there have been words and pictures, the people of the world have been consuming media.
Apache SparkApache Spark is an open-source unified analytics engine for large-scale data processing. Spark provides an interface for programming clusters with implicit data parallelism and fault tolerance. Originally developed at the University of California, Berkeley's AMPLab, the Spark codebase was later donated to the Apache Software Foundation, which has maintained it since. Apache Spark has its architectural foundation in the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way.
