Active metadata management is a set of capabilities that enables continuous access and processing of metadata that support ongoing analysis over a different spectrum of maturity, use cases and vendor solutions. Active metadata outputs range from design recommendations based upon execution results and reports of runtime steps through, and indicators of, business outcomes achieved. The resulting recommendations from those analytics are issued as design inputs to humans or system-level instructions that are expected to have a response.
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 non modeled 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 'Cloud Computing - Others'
Content collaboration tools provide an easy way for employees to use and share content both inside and outside the organizations. Since these tools can be used to collaborate with customers, partners and suppliers, they often provide rich security and privacy controls. Today, much of this functionality also can be found in other tools such as cloud office platforms, workstream collaboration platforms, content services platforms and content services applications. Functional differentiators in dedicated CCTs are difficult to identify.
Reviews for 'Data Center - Others'
Data preparation is an iterative and agile process for finding, combining, cleaning, transforming and sharing curated datasets for various data and analytics use cases including analytics/business intelligence (BI), data science/machine learning (ML) and self-service data integration. Data preparation tools promise faster time to delivery of integrated and curated data by allowing business users including analysts, citizen integrators, data engineers and citizen data scientists to integrate internal and external datasets for their use cases. Furthermore, they allow users to identify anomalies and patterns and improve and review the data quality of their findings in a repeatable fashion. Some tools embed ML algorithms that augment and, in some cases, completely automate certain repeatable and mundane data preparation tasks. Reduced time to delivery of data and insight is at the heart of this market.
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.
Reviews for 'Data and Analytics - Others'
Gartner defines the market for data and analytics (D&A) services as consulting and system integration (C&SI) and managed services. These services manage data for all uses (operational and analytical), and analyze data to drive business processes and improve business outcomes through more effective decision making. The core capabilities for vendor solutions in the D&A services market include: D&A strategy and operating model design Data management Analytics and business intelligence (ABI) Data science and machine learning D&A governance Program management Enterprise metadata
Gartner defines distributed file systems and object storage as software and hardware appliance products that offer object and distributed file system technologies for unstructured data. Their purpose is to store, secure, protect and scale unstructured data with access over the network using file and object protocols, such as Amazon Simple Storage Service (S3), Network File System (NFS) and Server Message Block (SMB).
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.
Integrated systems combine server, shared storage and network devices, along with management software and support in a preintegrated stack. The integrated system market has four segments: integrated infrastructure system, integrated reference architecture, integrated stack system and hyperconverged infrastructure (HCI) segment. The overall HCI segment is further subdivided into Hyperconverged Integrated Systems (HCIS), which provides both software and hardware in an appliance model and the software only segment in which vendors provide the Hyperconverged software. This is then integrated with HW by a reseller or the end customer.
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.
Gartner defines Oracle Cloud Application (OCA) services as only those services associated with the products under Oracle Cloud Applications, also known as SaaS. This means consultancy, migration, implementation, ongoing services, postimplementation evolution and optimization services. To qualify, each vendor project must have an “anchoring” OCA product from at least one of the following Oracle “Fusion” solutions: - Advertising and customer experience (ACX) - Industry applications (IA) - Enterprise resource planning (ERP; includes the previous EPM applications) - Human capital management (HCM) - Supply chain management (SCM)
The services for Oracle Cloud Infrastructure (OCI) market includes consulting, implementation and ongoing management services for Oracle and non-Oracle workloads hosted on OCI. Service providers in this market combine expertise in Oracle solutions and OCI with skills in managing private infrastructure, hybrid IT, multicloud, sovereign and distributed cloud to provide strategic and operational assistance as clients define and realize their cloud goals and business outcomes with OCI.
Gartner defines primary storage with platform services as dedicated products and platform-native services for solid-state arrays or hybrid storage arrays, structured block data consumption-based offerings and software-defined storage (SDS) software. API-centric control and vendor-managed data services planes are used for primary storage onboarding, provisioning and AIOps-enabled SLA-based life cycle management and support outcomes. Platform-native services include the syndication and integration of complementary third-party storage products and data services as part of their managed services offerings. Products and services are available in traditional capex, subscription and consumption pay-for-use licensing.