What is industrial field data management?
Update:2019-03-28 Page View:2025

[Industrial Field Data Management] refers to a general term for a list of requirements, services, and applications formed around industrial field data/information.

Industrial field data management, with "data" as the core concern, in addition to focusing on solving data initialization problems such as acquisition, cleaning, and preprocessing of various industrial field data, including security management of industrial field data, ownership management, Full-scale management content such as storage management, call management, edge computing, and application pre-application (microservices), as well as data reverse flow management (such as command information delivery, application parameter download, etc.) that occurs in individual application scenarios.

Industrial field data management, with the transmission layer/cloud as the boundary, encapsulates all industrial sites such as workshops, factories, and control stations on the south side into an orderly “black box” and provides standard communication and data to the outside. And service interface, which facilitates data interaction between various platforms, applications or cloud systems and industrial sites, turning the original complex industrial field data management problem into a standardized application service support system, helping various platforms and application providers to solve the industry. The problem of on-site data management provides data-driven "ignition capability" for the entire industrial Internet industry system, and completes the "first gear" of various industrial Internet projects.

Is a service, not a technology

Industrial field data management is not a specific technology. This is very different from the existing industrial Internet related concepts such as platform, big data analysis, visual recognition, cloud computing, and edge computing. For industrial field data management, it cannot be interpreted by a single technology, or even understood by a purely technical level.

From the perspective of Gezhi Dongzhi, an industrial Internet solution provider and smart industrial service provider, industrial field data management is a service, a one-stop Turn Key service.

In the system and ecology of industrial site data management, the main line of consulting is to use the customer's explicit/invisible demand as the starting point of the project/system. According to the customer's actual situation and other various boundary conditions, the most customized for the customer. A solution that meets the needs of its industrial field data management needs.

This type of solution is often a combination of multiple technologies, complemented by specially tailored software, on-site and engineering services, and even with different business models to provide customers with the most cost-effective industrial field data management. method.

Derived from DaaS higher than DaaS

DaaS is Data-as-a-service, which is a new service concept after IaaS, PaaS and SaaS. Data-as-a-Service (DaaS) provides a direction for improving IT efficiency and system performance through centralized management of resources. The main technologies included in DaaS are data virtualization, data integration, SOA, BPM, and PaaS.

A platform of the DaaS standard, the elements involved mainly include:

1, Dataacquisition: from any data source, such as data warehouse, email, portal, third-party data sources.

2, data governance and standardization: manually or automatically organize data standards.

3, data aggregation: must have a strong service and technology-driven quality control mechanism, not simply write 100 ETL programs.

4, data services: through web services, extraction and reports, so that end users can more easily consume data.

Industrial field data management can be seen as a special case of DaaS in the industrial field. The core concept of industrial field data management is similar to DaaS, but it has its own unique features:

The data source is mainly based on equipment, production lines and systems in the industrial field, and the data source of some scenarios may be an application system or database of IT;

A large amount of real-time data and historical data coexist;

The final external interface is generally not an application interface, but a database or data management interface;

Not a traditional IT service, but an IOT hybrid service.