Analytics and business intelligence platforms — enabled by IT and augmented by AI — empower users to model, analyze and share data. Analytics and business intelligence (ABI) platforms enable organizations to understand their data. For example, what are the dimensions of their data — such as product, customer, time, and geography? People need to be able to ask questions about their data (e.g., which customers are likely to churn? Which salespeople are not reaching their quotas?). They need to be able to create measures from their data, such as on-time delivery, accidents in the workplace and customer or employee satisfaction. Organizations need to blend modeled and nonmodeled data to create new data pipelines that can be explored to find anomalies and other insights. ABI platforms make all of this possible.
Reviews for 'Application Development, Integration and Management - Others'
Gartner defines cloud AI developer services (CAIDS) as cloud-hosted or containerized services and products that enable software developers who are not data science experts to use artificial intelligence (AI) models via APIs, software development kits (SDKs) or applications. Core capabilities include automated machine learning (autoML) including automated data preparation, automated feature engineering and automated model building, and model management and operationalization for language, vision and tabular use cases. Optional and important complementary capabilities include AI code models and assistants. Cloud AI developer services help organizations embed intelligence, such as AI and ML insights, into their applications. While that is what cloud AI developer services offer, it is more important to note how they accomplish this. These services democratize and increase the availability of AI and ML to software engineers through the automation and features offered. Traditional activities regarding data acquisition, data quality, feature engineering, algorithm selection and model training are augmented by the technology. Cloud AI developer services open up a world of possibilities for software engineers to build AI and ML production capabilities and features for enterprise-built applications.
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 WAAP as a category of security solutions designed to protect web applications irrespective of their hosted locations. Typically delivered as a service, cloud WAAP is offered as a series of security modules that provide protection from a broad range of runtime attacks. It offers protection from the Top 10 web application security risks defined by the Open Web Application Security Project (OWASP) and automated threats, provides API security, and can detect and protect against multiple sophisticated Layer 7 attacks targeted at web applications. Cloud WAAP’s core features include web application firewall (WAF), bot management, distributed denial of service (DDoS) mitigation and API protection.
Gartner defines container management as offerings that enable the deployment and operation of containerized workloads. Delivery methods include stand-alone software or as a service. Delivery methods include cloud, managed service and software for containers running on-premises, in the public cloud and/or at the edge. Container management automates the provisioning, operation and life cycle management of containerized workloads at scale. Centralized governance and security policies are used to manage container workloads and associated resources. Container management supports the requirements of modern applications (also refactoring legacy applications), including platform engineering, cloud management and continuous integration/continuous deployment (CI/CD) pipelines. Benefits include improved agility, elasticity and access to innovation.
The market for distributed denial of service (DDoS) mitigation includes vendors that detect and mitigate DDoS attacks and offer it as a dedicated offering. It includes specialty vendors, whose primary focus is DDoS mitigation, as well as providers that offer DDoS mitigation as a feature of other services. These include dedicated appliance-based vendors, communication service providers (CSPs), content delivery network (CDN) vendors, hosting providers and cloud infrastructure and platform services (CIPS) vendors.
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.
Reviews for 'Data and Analytics - Others'
Gartner defines desktop as a service (DaaS) as the provision of virtual desktops by public cloud or other service providers. DaaS provides desktop or application end-user experiences from virtual machines (VMs) accessed using a remote display protocol. DaaS vendors incorporate a fully managed control plane service into their offerings, which facilitates user connections and provides a management interface. DaaS can be delivered preconfigured as a service. Alternatively, it can be delivered as a platform, in which case the client is responsible for assembly, configuration and management. DaaS is charged for using subscription- or usage-based payment structures. DaaS solutions allow remote workers, offshore workers, third-party employees, contractors, home workers and office workers to access virtual desktops hosted in the cloud. DaaS solutions include technology that enables centralized management of all VMs. DaaS virtual desktops can be configured for a variety of use cases associated with contact center workers, process workers, information workers, and workers who require high-performance computing or rich graphics.
Gartner defines enterprise low-code application platforms (LCAPs) as platforms for accelerated development and maintenance of applications, using model-driven tools for the entire application’s technology stack, generative AI and prebuilt component catalogs. Enterprise LCAPs target software engineering teams responsible for custom application development and maintenance. Enterprise LCAP features include support for the collaborative development of all application components; runtime environments for high performance, availability and scalability of applications; application deployment and monitoring with detailed usage insights. Enterprise LCAP platforms feature governance controls and success management through self-service capabilities and APIs, developer documentation and training, and service-level agreements for platform operations. Enterprise LCAPs provide the foundation for developing a wide range of application types and application components, including complex front ends, business process automation and distributed data sources.
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.
Reviews for 'IT Infrastructure and Operations Management - Others'
Meeting solutions are real-time communication services with their associated devices that support live interactions between participants for internal and external collaboration, presentations, learning, training sessions and webinars. Meeting solutions power diverse use cases, such as one-on-one meetings, remote sales engagements, board meetings, telehealth sessions, remote banking and consulting services, to name just a few. Meeting solutions enable rich information sharing and interaction by combining audio and video, in-meeting chat, content and screen sharing, and visual collaboration and whiteboarding.
Gartner defines the network firewall market as the market for firewalls that use bidirectional stateful traffic inspection (for both egress and ingress) to secure networks. Network firewalls are enforced through hardware, virtual appliances and cloud-native controls. Network firewalls are used to secure networks. These can be on-premises, hybrid (on-premises and cloud), public cloud or private cloud networks. Network firewall products support different deployment use cases, such as for perimeters, midsize enterprises, data centers, clouds, cloud-native and distributed offices.
Gartner defines observability platforms as products that ingest telemetry (operational data) from a variety of sources including, but not limited to, logs, metrics, events and traces. They are used to understand the health, performance and behavior of applications, services and infrastructure. Observability platforms enable an analysis of the telemetry, either via human operator or machine intelligence, to determine changes in system behavior that impact end-user experience such as outages or performance degradation. This allows for early, and even preemptive, problem remediation. Observability solutions are used by IT operations, site reliability engineers, cloud and platform teams, application developers, and product owners. Observability platforms are used by organizations to understand and improve the availability, performance and resilience of these critical applications and services. Investment in and successful deployment of observability platforms leads to revenue loss avoidance and enables faster product development cycles and improvements in brand perception.
Public cloud storage is infrastructure as a service (IaaS) that provides block, file, object and hybrid cloud storage services delivered through various protocols. The services are stand-alone, but often used in conjunction with compute and other IaaS products. The services are priced based on capacity, data transfer and/or number of requests. The services provide on-demand storage capacity and self-provisioning capabilities. Stored data exists in a multitenant environment, and users access that data through the block, network and REST protocols provided by the services.
Gartner defines strategic cloud platform services (SCPS) as standardized, automated, public cloud offerings integrating infrastructure services (e.g., computing, network and storage), platform services (e.g., application, data and value-added services such as AI/ML) and transformation services (resources to help customers adopt cloud-oriented IT delivery models). Although owned by the service provider, infrastructure and platform services may be hosted in providers’ infrastructures or customers’ data centers. Services should be elastically scalable, metered by use, and consumable via web-based interfaces and programmable APIs. Transformation programs may be delivered by automated, self-service interfaces, and managed interactions facilitated by account teams/partners.