Gartner defines the market for cloud database management systems (DBMSs) as the market for software products that store and manipulate data and that are primarily delivered as software as a service (SaaS) in the cloud. Cloud DBMSs may optionally be capable of running on-premises, or in hybrid, multicloud or intercloud configurations. They can be used for transactional work and/or analytical work. They may have features that enable them to participate in a wider data ecosystem. Must-have capabilities for this market include: Availability as SaaS on provider-managed public or private cloud systems; Management of data within cloud storage — that is, cloud DBMSs are not hosted in infrastructure as a service (IaaS), such as in a virtual machine or a container managed by the customer.
Gartner defines cloud enterprise resource planning (ERP) for product-centric enterprises as a market for application technology that supports the automation of operational and financial activities for the manufacturing, distribution, delivery and servicing of goods. Cloud ERP for Product-Centric Enterprises is delivered under a SaaS license model with frequent updates and where application support and infrastructure is the responsibility of the vendor.
Competitive and market intelligence tools allow organizations to track, collect, store, analyze, and disseminate information and insights about competitors, markets, and customers collected from internal and external sources, including but not limited to social media, websites, product information, and financial filings. Such tools provide a centralized platform for all market and competitive intelligence, which can be utilized by a range of stakeholders within the organization for their specific needs.
Computer-Aided Design software is used by designers, engineers, architects, and drafters across several industries to create two-dimensional and three-dimensional models. These 2D and 3D models can be used to explore design ideas, visualize concepts and simulate the physical behavior of a design in the real world. The software provides in-built templates such as flowcharts, mind maps, wireframes, network diagrams, and org charts to create quality as well as detailed design models. The software also allows for instant changes to models enabling collaborative work between team members.
Gartner defines a data science and machine learning platform as an integrated set of code-based libraries and low-code tooling that support the independent use by, and collaboration between, data scientists and their business and IT counterparts through all stages of the data science life cycle. These stages include business understanding, data access and preparation, experimentation and model creation, and sharing of insights. They also support machine learning engineering workflows including creation of data, feature, deployment and testing pipelines. The platforms are provided via desktop client or browser with supporting compute instances and/or as a fully managed cloud offering. Data science and machine learning (DSML) platforms are designed to allow a broad range of users to develop and apply a comprehensive set of predictive and prescriptive analytical techniques. Leveraging data from distributed sources, cutting-edge user experience, and native machine learning and generative AI (GenAI) capabilities, these platforms help to augment and automate decision making across an enterprise. They provide a range of proprietary and open-source tools to enable data scientists and domain experts to find patterns in data that can be used to forecast financial metrics, understand customer behavior, predict supply and demand, and many other use cases. Models can be built on all types of data, including tabular, images, video and text for applications that require computer vision or natural language processing.
Enterprise asset management (EAM) is a business application used most comprehensively by asset-intensive industries to execute, track and optimize inspections, maintenance and repair of industrial plants and equipment. Examples of these industries are heavy discrete and process manufacturing industries, oil and gas, rail, and power and utilities. An alternative term used for EAM is “computerized maintenance management system” (CMMS), which is generally considered to be small-scale, single-site applications with less functionality around parts management and resource scheduling.
Labeling and artwork management is both a discipline and a network of applications that governs product packaging and product content data. It creates compliant artwork and labeling that can be viewed on traditional product packaging, online or in the supply chain. Gartner defines the market for LAM software applications as “pure-play, on-premises or cloud applications that digitally link individuals, functions and organizations involved in product packaging, artwork and labeling processes with existing business processes across the entire supply chain. The digital applications support the functional roles involved in the processes, automating traditionally manual activities, and digitizing the content for visibility, speed, accuracy and quality.” LAM consists of three distinct categories that may have overlaps, but all integrate with the product content data: * Enterprise labeling * E-labeling * Artwork management
Manufacturing process management (MPM) and model-based manufacturing (MbM) bridge the gap between the virtual design realm and the physical product/process manufacturing realm as part of an organized software architecture. These technologies are not only applied within the four walls of a plant or a corporation's multiple manufacturing sites. They can be applied holistically, with workflow to manage multiple recipe variants and labeling change/requirements, and/or handle certificates of compliance (CoCs) and certificates of analysis (CoAs) from suppliers.
Gartner defines manufacturing execution systems (MES) as a specialist class of production-oriented software that manages, monitors and synchronizes the execution of real-time physical processes involved in transforming raw materials into intermediate and/or finished goods. These systems coordinate this execution of work orders with production scheduling and enterprise-level systems like ERP and product life cycle management (PLM). MES applications also provide feedback on process performance, and support component and material-level traceability, genealogy and integration with process history, where required.
Product life cycle management (PLM) is a philosophy, process and discipline supported by software for managing the life cycle of products through the stages from concept through recycling/retirement. As a discipline, it has grown from a mechanical design and engineering focus to being applied to many different vertical-industry product development challenges. The market for PLM software includes vendors that: - Provide product data management (PDM) software to capture, cultivate and manage technical product-related content. That content defines the products’ specifications and designs and their allowable product configurations. It includes technical descriptions of the parts, materials and allowable product configurations expressed as 3D models, drawings and other related content. All PLM vendors deliver PDM functionality. - If software providers support only PDM functionality, Gartner does not consider them PLM vendors. PLM vendors support complementary applications that enable the PLM discipline to various degrees. Gartner considers a vendor a PLM provider if it supports at least three complementary software categories that enable the PLM discipline. Table 1 provides insight into the complementary categories of software that support the PLM discipline. Those additional software categories help manufacturers create, deliver, maintain, service and discontinue products.
Gartner defines the market for quality management system (QMS) software as the business information management system that manages quality policies and standard operating procedures (SOPs). This may include, but is not limited to, customer requirements, quality documents, International Organization for Standardization (ISO) requirements, manufacturing capabilities, robust design, auditing procedures and protocols, nonconformance/risk management activities, testing criteria, and industry-specific regulations (for example, U.S. Food and Drug Administration [FDA] or Federal Acquisition Regulation [FAR] requirements).
Gartner defines supply chain planning (SCP) solutions as platforms that provide technological support to enable a company to manage, link, align, collaborate and share its planning data across an extended supply chain. An SCP solution supports planning, ranging from demand planning through detailed supply-side response planning and from strategic planning through execution-level planning. It is the planning decision repository for a defined end-to-end supply chain. It is also the environment in which end-to-end-integrated supply chain decisions are managed. It establishes a single version of the truth for planning data and decisions, regardless of the underlying execution technology environment. Organizations use SCP solutions to improve their supply chain planning decisions and reach higher levels of maturity.
Reviews for 'Vertical Industries - Others'