Hi! Thanks for sharing your thoughts about the semantic layer. I am working on the same topic, and I think a semantic business glossary could be one of the digital commons. I've started a registry of semantic data types registry.apicrafter.io and looking for cooperation to make it worthwhile for the community.
In "Down the Semantic Rabbit Hole [1], JP Monteiro wrote:
#data #analytics #business #sql #language
'The purpose of a semantic layer is to close the gap between the “business language” and the “data language” and offer a unified and consistent view of the business domain as represented in the data.'
Arguably, Executable English, live online at [2], covers JP's detailed points.
Executable English is a platform for acquiring knowledge in the form of English syllogisms, for using the knowledge to answer questions, and for explaining the answers.
It's an outcome of many person-years of R&D.
It works with everyday English and jargons. The vocabulary is *open*, and so is most of the syntax, yet it needs no external grammar or dictionary maintenance, it supports non-programmer authors, and avoids ambiguities by means of context.
When needed, it automatically generates and runs complex networked SQL queries.
The platform is live online at [2], with many examples. You are invited to write and run your own examples too. If you are reading this, you already know most of the language!
So, what do you think? Have we here the Holy Grail of semantics for analytics? Mind the gap!
Hi and great article. How does the "semantic layer" equate to meta content integration (https://www.metaintegration.com) along with usage of a metadata framework (including the Metadata Repository now called Data Catalog) to manage all this semantic content from years ago. Data Modeling tools (ErWin, ER/Studio Data Architect, plus) plus other integrated toolsets (Business Glossary) can capture and manage quite a bit of semantics (business context) to the business data. I am very curious what would be replacing these capabilities to now manage "semantics".
Hi! Thanks for sharing your thoughts about the semantic layer. I am working on the same topic, and I think a semantic business glossary could be one of the digital commons. I've started a registry of semantic data types registry.apicrafter.io and looking for cooperation to make it worthwhile for the community.
In "Down the Semantic Rabbit Hole [1], JP Monteiro wrote:
#data #analytics #business #sql #language
'The purpose of a semantic layer is to close the gap between the “business language” and the “data language” and offer a unified and consistent view of the business domain as represented in the data.'
Arguably, Executable English, live online at [2], covers JP's detailed points.
Executable English is a platform for acquiring knowledge in the form of English syllogisms, for using the knowledge to answer questions, and for explaining the answers.
It's an outcome of many person-years of R&D.
It works with everyday English and jargons. The vocabulary is *open*, and so is most of the syntax, yet it needs no external grammar or dictionary maintenance, it supports non-programmer authors, and avoids ambiguities by means of context.
When needed, it automatically generates and runs complex networked SQL queries.
The platform is live online at [2], with many examples. You are invited to write and run your own examples too. If you are reading this, you already know most of the language!
So, what do you think? Have we here the Holy Grail of semantics for analytics? Mind the gap!
Adrian Walker
Executable English LLC
San Jose, CA, USA
USA 860-830-2085 (California time)
www.executable-english.com
[1] https://lnkd.in/gbhpk9vw
[2] www.executable-english.com
Hi and great article. How does the "semantic layer" equate to meta content integration (https://www.metaintegration.com) along with usage of a metadata framework (including the Metadata Repository now called Data Catalog) to manage all this semantic content from years ago. Data Modeling tools (ErWin, ER/Studio Data Architect, plus) plus other integrated toolsets (Business Glossary) can capture and manage quite a bit of semantics (business context) to the business data. I am very curious what would be replacing these capabilities to now manage "semantics".
Tools Needed for Power Mismatches
on the World Wide Web and Social Media
https://tomg2021.substack.com/p/tools-needed-for-power-mismatches
The World Wide Web's course correction
https://tomg2021.substack.com/p/the-world-wide-webs-course-correction