"Data governance" has become a hot topic in the enterprise IT community in the past two years. Even IT strategic planning for enterprises must include a "data governance system". This term has also caused a lot of conceptual confusion in the industry. I have written several articles on this topic:
Enterprise IT Planning | Which department should be responsible for data governance? How useful is a data governance platform?
Talking about data governance from the perspective of GHS index
Most enterprise data governance solutions fail to deliver results
Ancient prose and labels | Seek benevolence and gain benevolence, go to the middle stage
Misunderstandings in Digital Transformation | Limitations of the “Data Middle Platform” Concept
I am in "Enterprise IT Planning | Which department should be responsible for data governance? How useful is a data governance platform?" 》The article mentioned that different industries have different concerns about data governance. Internet companies/e-commerce, financial institutions, manufacturing industries, etc. all have different starting points for data governance. Therefore, the IT solutions and system architectures of data governance vary greatly.
Taking the comparison between Internet companies and the manufacturing industry as an example, to put it simply: the data application characteristics of Internet companies are that the standardization of their business transaction systems is very low, and the data is "fixed first and then treated", which is mainly oriented towards analysis; while the data application characteristic of the manufacturing industry is that the business information system is highly standardized, the data is "fixed first and then used", mainly oriented towards processes. Therefore,The concepts, architecture and processes of the so-called "data center" originated from Internet companies cannot be simply applied to the manufacturing industry to a large extent.。
As far as manufacturing and similar industries are concerned, the core business system is ERP, as well as peripheral business systems related to ERP - CRM, SCM, SRM, PLM, etc. The purpose of data governance is to support the application of information systems:
I think in manufacturing informatization, data quality is determined by master data and business quality. The buzzword "data governance" should be preceded by the word "master", that is, "Master data governance", this term is basically equivalent to "master data management". In fact, the master data management system in the manufacturing industry has a long history. When there was ERP, there was a "coding system". Today's "master data governance" is the upgrade of the coding system, which should roughly cover the following areas:
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Business classification of master data (Taxonomy and Hierarchy)
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Concept standardization of master data
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Cleaning and correction of erroneous data
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Data quality monitoring
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Deduplication, matching and key-value uniqueness
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Master data management workflow, including operations such as generation, approval, release, and manual classification
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Integrate with ERP, CRM and other business systems
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Integrate with ETL tools and data analysis systems
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Visual analysis of data relationships
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Data rights management
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Data compliance and privacy management
I think that master data management solutions in the manufacturing industry should no longer invent the wheel. For related business processes and system architecture, please refer toThe King of Manufacturing Information SystemsJust like SAP, SAP’s master data governance solution is called MDG:
SAP's master data management solution is mainly aimed at serving ERP, including major data objects such as finance, materials, customers, and suppliers:
"Master data governance" is originally a very mature software market, with many MDM/MDG packages
Software provider:
In a market with such mature suppliers, when I see many Chinese manufacturing companies developing their own "data middle platform" and "data governance tools", I can't understand what they are going to do? What value does it bring to the business? What business problem was solved? Why keep inventing the wheel? ——Perhaps this is a bad habit brought out by Internet companies advocating "data center":
The above pictures are quoted from
Machine-translated from the Chinese original 数据治理究竟解决了制造业企业什么问题？ (published 2022-03-29). WeChat original ↗