Application platforms provide runtime environments for application logic. They manage the life cycle of an application or application component, and ensure the availability, reliability, scalability, security and monitoring of application logic. They typically support distributed application deployments across multiple nodes. Some also support cloud-style operations (elasticity, multitenancy and self-service).
The application portfolio management (APM) discipline monitors the business, technical and cost fitness of the application portfolio. It uses factual information and analysis, allowing objective and transparent decisions. Its main objective is to identify, prioritize and propose opportunities to improve the portfolio. Opportunities include replacements, migration, modernization, consolidation and decommissioning. APM tools support the people, processes and information of the APM IT discipline to discover, monitor, analyze and visualize the fitness of the application portfolio and provide recommendations for improvement.
Gartner defines business process automation (BPA) tools as software that automates business processes by enabling orchestration and choreography of diverse sets of actors (humans, systems and bots) involved in the execution of the process. BPA tools provide an environment for developing and running applications that incorporate process models (and optionally other business, decision and data models) enabling digitization of business operations
Gartner defines business processes as the coordination of the behavior of people, systems and things to produce specific business outcomes. 'Things' in this context refers to devices that are part of the Internet of Things (IoT). A BPM platform minimally includes: a graphical business process and/or rule modeling capability, a process registry/repository to handle the modeling metadata, a process execution engine and a state management engine or rule engine (or both). The three types of BPM platforms — basic BPM platforms, business process management suites (BPMSs), and intelligent business process management suites (iBPMSs) — can help solution architects and business outcome owners accelerate application development, transform business processes, and digitalize business processes to exploit business moments by providing capabilities that manage different aspects of the business process life cycle.
Gartner defines the market for Enterprise Architecture Tools as tools that allow organizations to examine both the need for, and the impact of, change. They allow users to capture the interrelationships and interdependencies within and between an ecosystem of partners, operating models, capabilities, people, processes, information, and applications and technologies. They provide a central repository to capture data and metadata about the artifacts that an enterprise cares about, and their related life cycles. Models represent the relationships between these artifacts and are themselves treated as assets that help describe and shape the future of the enterprise. EA tools provide a means to model the business and IT aspects of the enterprise in support of business outcome delivery. Doing so requires the collaboration of multiple stakeholders across the organization — each playing a different role at a different time. The models and methods used by the stakeholders will vary depending on their role and must be integrated and connected to other models to be useful. To support these needs, EA tools have two aspects. The first provides a modeling environment, along with a supporting repository. The second facilitates collaboration between a diverse group of stakeholders across the organization, right from business strategy to IT. A broad array of architectural and IT disciplines, such as business, information, solution, security, applications and infrastructure use EA tools. EA tools operate at many levels and across a wide spectrum to enable insights and support informed decision making. With such a broad array of stakeholders, EA tools must also facilitate their consumption of, and contribution to, the information contained within the repository. As they undertake their work, these users switch between an ever-expanding set of views and visual representations of the datasets contained in the repository.
EBPA is a comprehensive approach toward business and process modeling aimed at transforming and improving business performance with an emphasis on cross-viewpoint (strategy, analysis, architecture, automation), cross-functional analysis to support strategic and operational decisions.
The market for ESP platforms consists of software subsystems that perform real-time computation on streaming event data. They execute calculations on unbounded input data continuously as it arrives, enabling immediate responses to current situations and/or storing results in files, object stores or other databases for later use. Examples of input data include clickstreams; copies of business transactions or database updates; social media posts; market data feeds; images; and sensor data from physical assets, such as mobile devices, machines and vehicles.
The global industrial IoT platform delivers multiple integrations to industrial OT assets and other asset-intensive enterprises’ industrial data sources to aggregate, curate and deliver contextualized insights that enable intelligent applications and dashboards through an edge-to-cloud architecture. The global industrial Internet of Things (IIoT) platform market exists because of the core capabilities of integrated middleware software that support a multivendor marketplace of intelligent applications to facilitate and automate asset management decision making. IIoT platforms also provide operational visibility and control for plants, infrastructure and equipment. Common use cases are augmentation of industrial automation, remote operations, sustainability and energy management, global scalability, IT/operational technology (OT) convergence, and product servitization of industrial products. The IIoT platform monitors IoT endpoints and event streams, supports and/or translates a variety of manufacturer and industry proprietary protocols, analyzes data in the platform, at the edge and in the cloud, integrates and engages IT and OT systems in data sharing and consumption, enables application development and deployment and can enrich and supplement OT functions for improved asset management life cycle strategies and processes. In some emerging use cases, the IIoT platform may obviate some OT functions.
IMDGs provide a lightweight, distributed, scale-out in-memory object store — the data grid. Multiple applications can concurrently perform transactional and/or analytical operations in the low-latency data grid, thus minimizing access to high-latency, hard-disk-drive-based or solid-state-drive-based data storage. IMDGs maintain data grid durability across physical or virtual servers via replication, partitioning and on-disk persistence. Objects in the data grid are uniquely identified through a primary key, but can also be retrieved via other attributes. The most typical use of IMDGs is for web-scale transaction processing applications. However, adoption for analytics, often in combination with Apache Spark and Hadoop or stream analytics platforms, is growing fast — for example, for fraud detection, risk management, operation monitoring, dynamic pricing and real-time recommendation management.
Reviews for 'Internet of Things - Others'
Integration means making independently designed applications and data work well together. IoT integration means making the mix of new IoT devices, IoT data, IoT platforms and IoT applications — combined with IT assets (business applications, legacy data, mobile, and SaaS) — work well together in the context of implementing end-to-end IoT business solutions. The IoT integration market is defined as the set of IoT integration capabilities that IoT project implementers need to successfully integrate end-to-end IoT business solutions.
Process mining platforms are designed to discover, monitor and improve processes by extracting knowledge from events captured in information systems to continuously deliver visibility and insights. Process mining includes automated process discovery (extracting process models from an event log), conformance checking (monitoring deviations by comparing model and log), social network/organizational mining, automated construction of simulation models, model extension, model repair, case prediction and history-based recommendations. Process mining platforms extend process mining capabilities by advanced process analytics, process improvement detection and process improvement recommendations, partly driven by AI and generative AI (GenAI).
Gartner defines strategic portfolio management (SPM) as a set of business capabilities, processes and supporting portfolio management technology. Business leaders, enterprise portfolio management office (EPMO) leaders and IT leaders require SPM to support enterprisewide strategy-to-execution alignment and adaptation. The SPM market addresses the integrated portfolio management technology needs of business leaders, EPMO leaders and IT leaders. SPM technology supports clear definition of key business strategies and desired business outcomes, and the formulation and mapping of these with key portfolio elements, such as business capabilities, investments, programs, digital and physical products, applications and projects. SPM technology allows users to create multiple portfolio and subportfolio types with focused themes, such as programs, digital products, physical products, business or IT services, projects and applications. It allows users to link and cross-reference elements in the different portfolios and subportfolios to support integrated portfolio analysis and tracking.
A digital twin of an organization (DTO) is a dynamic software model of any organization that relies on operational and contextual data to understand how an organization operationalizes its business model, connects with its current state, responds to changes, deploys resources and delivers customer value.