#semanticlayer — Public Fediverse posts

Why S/4HANA Migration Alone Won’t Make You AI-Ready

Completing an SAP S/4HANA migration is a major milestone. It is not the same thing as becoming AI-ready.…
#Germany #DE #Europe #EU #Europa #SAP #AIagentsERP #AIgovernance #AIreadiness #cleancoreSAP #datafoundation #datalakehouse #EnterpriseAI #ERPAI #ERPToday #S/4HANAmigration #sap #SAPAI #SAPS/4HANA #SAPinsider #SemanticLayer
https://www.europesays.com/germany/47599/

Ontopic Suite 2026.1 is here. What's new?

- Kubernetes
- arm64 and amd64 fully supported
- lot of UI polishing
- Azure Blob Storage
- updated Ontop engine

Visit https://ontopic.ai/en/activities/ontopic-suite-2026.1-released/ for more information

#knowledgeGraphs
#rdf
#rdb2RDF
#semanticlayer

Ontopic Suite 2026.1 is here. What's new?

- Kubernetes
- arm64 and amd64 fully supported
- lot of UI polishing
- Azure Blob Storage
- updated Ontop engine

Visit https://ontopic.ai/en/activities/ontopic-suite-2026.1-released/ for more information

#knowledgeGraphs
#rdf
#rdb2RDF
#semanticlayer

Ontopic Suite 2026.1 is here. What's new?

- Kubernetes
- arm64 and amd64 fully supported
- lot of UI polishing
- Azure Blob Storage
- updated Ontop engine

Visit https://ontopic.ai/en/activities/ontopic-suite-2026.1-released/ for more information

#knowledgeGraphs
#rdf
#rdb2RDF
#semanticlayer

Ontopic Suite 2026.1 is here. What's new?

- Kubernetes
- arm64 and amd64 fully supported
- lot of UI polishing
- Azure Blob Storage
- updated Ontop engine

Visit https://ontopic.ai/en/activities/ontopic-suite-2026.1-released/ for more information

#knowledgeGraphs
#rdf
#rdb2RDF
#semanticlayer

https://www.europesays.com/uk/720516/ What Other Industries Can Learn from Healthcare’s Knowledge Graphs #ArtificialIntelligence #DataGovernance #EnterpriseData #Health #Healthcare #KnowledgeGraphs #SemanticLayer #UK #UnitedKingdom

What Other Industries Can Learn from Healthcare’s Knowledge Graphs

Note 1: This post is part 3 of a three-part series on healthcare, knowledge graphs, and lessons for…
#NewsBeep #News #Healthcare #ArtificialIntelligence #DataGovernance #EnterpriseData #Health #healthcare #KnowledgeGraphs #SemanticLayer #UK #UnitedKingdom
https://www.newsbeep.com/uk/390184/

What Other Industries Can Learn from Healthcare’s Knowledge Graphs

Note 1: This post is part 3 of a three-part series on healthcare, knowledge graphs, and lessons for…
#NewsBeep #News #Healthcare #ArtificialIntelligence #DataGovernance #EnterpriseData #Health #healthcare #KnowledgeGraphs #SemanticLayer #UK #UnitedKingdom
https://www.newsbeep.com/uk/390184/

What Other Industries Can Learn from Healthcare’s Knowledge Graphs

Note 1: This post is part 3 of a three-part series on healthcare, knowledge graphs, and lessons for…
#NewsBeep #News #Healthcare #ArtificialIntelligence #DataGovernance #EnterpriseData #Health #healthcare #KnowledgeGraphs #SemanticLayer #UK #UnitedKingdom
https://www.newsbeep.com/uk/390184/

What Other Industries Can Learn from Healthcare’s Knowledge Graphs

Note 1: This post is part 3 of a three-part series on healthcare, knowledge graphs, and lessons for…
#NewsBeep #News #Healthcare #ArtificialIntelligence #DataGovernance #EnterpriseData #Health #healthcare #KnowledgeGraphs #SemanticLayer #UK #UnitedKingdom
https://www.newsbeep.com/uk/390184/

https://www.europesays.com/ie/299731/ What Other Industries Can Learn from Healthcare’s Knowledge Graphs #ArtificialIntelligence #DataGovernance #Éire #EnterpriseData #Health #HealthCare #Healthcare #IE #Ireland #KnowledgeGraphs #SemanticLayer

https://www.europesays.com/ie/295119/ Why Healthcare Leads in Knowledge Graphs #ArtificialIntelligence #DataGovernance #Éire #Health #HealthCare #Healthcare #IE #Ireland #KnowledgeGraphs #SemanticLayer

🧩 Sciogli i nodi dei tuoi incubi di data engineering con il potere del semantic layer! Rinventando la gestione dei dati. #DataEvolution #SemanticLayer ✨📈

🔗 https://www.tomshw.it/business/come-costruire-chatbot-affidabili-sui-tuoi-dati-aziendali-2025-12-16

🧩 Sciogli i nodi dei tuoi incubi di data engineering con il potere del semantic layer! Rinventando la gestione dei dati. #DataEvolution #SemanticLayer ✨📈

🔗 https://www.tomshw.it/business/come-costruire-chatbot-affidabili-sui-tuoi-dati-aziendali-2025-12-16

🧩 Sciogli i nodi dei tuoi incubi di data engineering con il potere del semantic layer! Rinventando la gestione dei dati. #DataEvolution #SemanticLayer ✨📈

🔗 https://www.tomshw.it/business/come-costruire-chatbot-affidabili-sui-tuoi-dati-aziendali-2025-12-16

Does your company struggle with messy, inconsistent data? A semantic layer transforms complex data into a single, business-friendly view, enabling reliable self-service analytics and trusted AI. Find out why you need one now. #DataAnalytics #SemanticLayer #BusinessIntelligence #DataGovernance
https://inpathways.net/is-companys-data-frustratingly-useless-why-you-absolutely-need-an-essential-semantic-layer/

Does your company struggle with messy, inconsistent data? A semantic layer transforms complex data into a single, business-friendly view, enabling reliable self-service analytics and trusted AI. Find out why you need one now. #DataAnalytics #SemanticLayer #BusinessIntelligence #DataGovernance
https://inpathways.net/is-companys-data-frustratingly-useless-why-you-absolutely-need-an-essential-semantic-layer/

Does your company struggle with messy, inconsistent data? A semantic layer transforms complex data into a single, business-friendly view, enabling reliable self-service analytics and trusted AI. Find out why you need one now. #DataAnalytics #SemanticLayer #BusinessIntelligence #DataGovernance
https://inpathways.net/is-companys-data-frustratingly-useless-why-you-absolutely-need-an-essential-semantic-layer/

Does your company struggle with messy, inconsistent data? A semantic layer transforms complex data into a single, business-friendly view, enabling reliable self-service analytics and trusted AI. Find out why you need one now. #DataAnalytics #SemanticLayer #BusinessIntelligence #DataGovernance
https://inpathways.net/is-companys-data-frustratingly-useless-why-you-absolutely-need-an-essential-semantic-layer/

Does your company struggle with messy, inconsistent data? A semantic layer transforms complex data into a single, business-friendly view, enabling reliable self-service analytics and trusted AI. Find out why you need one now. #DataAnalytics #SemanticLayer #BusinessIntelligence #DataGovernance
https://inpathways.net/is-companys-data-frustratingly-useless-why-you-absolutely-need-an-essential-semantic-layer/

🤡 A riveting 21-minute #guide for those desperate to build a "semantic layer" with DuckDB—because who wouldn't want to spend their precious time wrestling with #YAML files? 🐤📚 The authors promise you’ll emerge enlightened, or at least mildly confused, about why this even matters. 🙃
https://motherduck.com/blog/semantic-layer-duckdb-tutorial/ #DuckDB #SemanticLayer #DataEngineering #TechHumor #HackerNews #ngated

🤡 A riveting 21-minute #guide for those desperate to build a "semantic layer" with DuckDB—because who wouldn't want to spend their precious time wrestling with #YAML files? 🐤📚 The authors promise you’ll emerge enlightened, or at least mildly confused, about why this even matters. 🙃
https://motherduck.com/blog/semantic-layer-duckdb-tutorial/ #DuckDB #SemanticLayer #DataEngineering #TechHumor #HackerNews #ngated

🤡 A riveting 21-minute #guide for those desperate to build a "semantic layer" with DuckDB—because who wouldn't want to spend their precious time wrestling with #YAML files? 🐤📚 The authors promise you’ll emerge enlightened, or at least mildly confused, about why this even matters. 🙃
https://motherduck.com/blog/semantic-layer-duckdb-tutorial/ #DuckDB #SemanticLayer #DataEngineering #TechHumor #HackerNews #ngated

🤡 A riveting 21-minute #guide for those desperate to build a "semantic layer" with DuckDB—because who wouldn't want to spend their precious time wrestling with #YAML files? 🐤📚 The authors promise you’ll emerge enlightened, or at least mildly confused, about why this even matters. 🙃
https://motherduck.com/blog/semantic-layer-duckdb-tutorial/ #DuckDB #SemanticLayer #DataEngineering #TechHumor #HackerNews #ngated

#KnowledgeGraphs work best when they're accompanied by a #domainKnowledgeModel. This creates a #semanticLayer where everyone in your enterprise can see and connect the data, content, and knowledge they need. Andreas Blumauer has been developing this powerful idea for 20 years.

https://knowledgegraphinsights.com/andreas-blumauer/

#KnowledgeGraphs work best when they're accompanied by a #domainKnowledgeModel. This creates a #semanticLayer where everyone in your enterprise can see and connect the data, content, and knowledge they need. Andreas Blumauer has been developing this powerful idea for 20 years.

https://knowledgegraphinsights.com/andreas-blumauer/

#KnowledgeGraphs work best when they're accompanied by a #domainKnowledgeModel. This creates a #semanticLayer where everyone in your enterprise can see and connect the data, content, and knowledge they need. Andreas Blumauer has been developing this powerful idea for 20 years.

https://knowledgegraphinsights.com/andreas-blumauer/

Question for #data people -- I'm trying to understand headless BI. In particular, what it solves that SQL doesn't. In other words, why dbt (pre-analytics layer) isn't enough.

From what I can tell, it solves the problem that SQL can't easily be parameterized. You can make views that slice and dice your transactional data, but those views would hardcode a bunch of decisions better left up to the consumer. You can also denormalize the heck out of your data to make all conceivable queries easy, but then you end up with an analytical table that's way too tall and wide.

It seems like what these semantic layer / headless BI tools do is apply the metadata to your transactional data that allow for BI tools to offer slick query builder interfaces, which ultimately are generating SQL. Furthermore, the logic for different types of analysis can be standardized and controlled, compared to people handwriting their queries.

Do I have this right?

#semanticlayer #analyticslayer #headlessbi #businessintelligence #analytics #dataanlytics #datamastodon

Question for #data people -- I'm trying to understand headless BI. In particular, what it solves that SQL doesn't. In other words, why dbt (pre-analytics layer) isn't enough.

From what I can tell, it solves the problem that SQL can't easily be parameterized. You can make views that slice and dice your transactional data, but those views would hardcode a bunch of decisions better left up to the consumer. You can also denormalize the heck out of your data to make all conceivable queries easy, but then you end up with an analytical table that's way too tall and wide.

It seems like what these semantic layer / headless BI tools do is apply the metadata to your transactional data that allow for BI tools to offer slick query builder interfaces, which ultimately are generating SQL. Furthermore, the logic for different types of analysis can be standardized and controlled, compared to people handwriting their queries.

Do I have this right?

#semanticlayer #analyticslayer #headlessbi #businessintelligence #analytics #dataanlytics #datamastodon

Question for #data people -- I'm trying to understand headless BI. In particular, what it solves that SQL doesn't. In other words, why dbt (pre-analytics layer) isn't enough.

From what I can tell, it solves the problem that SQL can't easily be parameterized. You can make views that slice and dice your transactional data, but those views would hardcode a bunch of decisions better left up to the consumer. You can also denormalize the heck out of your data to make all conceivable queries easy, but then you end up with an analytical table that's way too tall and wide.

It seems like what these semantic layer / headless BI tools do is apply the metadata to your transactional data that allow for BI tools to offer slick query builder interfaces, which ultimately are generating SQL. Furthermore, the logic for different types of analysis can be standardized and controlled, compared to people handwriting their queries.

Do I have this right?

#semanticlayer #analyticslayer #headlessbi #businessintelligence #analytics #dataanlytics #datamastodon

Question for #data people -- I'm trying to understand headless BI. In particular, what it solves that SQL doesn't. In other words, why dbt (pre-analytics layer) isn't enough.

From what I can tell, it solves the problem that SQL can't easily be parameterized. You can make views that slice and dice your transactional data, but those views would hardcode a bunch of decisions better left up to the consumer. You can also denormalize the heck out of your data to make all conceivable queries easy, but then you end up with an analytical table that's way too tall and wide.

It seems like what these semantic layer / headless BI tools do is apply the metadata to your transactional data that allow for BI tools to offer slick query builder interfaces, which ultimately are generating SQL. Furthermore, the logic for different types of analysis can be standardized and controlled, compared to people handwriting their queries.

Do I have this right?

#semanticlayer #analyticslayer #headlessbi #businessintelligence #analytics #dataanlytics #datamastodon

Enterprise sponsored #opensource:
ADP, a global leader in cloud based solutions for Human Capital Management, sponsored the development of “rules”, (https://github.com/ontop/ontop/pull/576), another great feature of @ontop4obda
.

#semanticlayer
#knowledgegraphs

Enterprise sponsored #opensource:
ADP, a global leader in cloud based solutions for Human Capital Management, sponsored the development of “rules”, (https://github.com/ontop/ontop/pull/576), another great feature of @ontop4obda
.

#semanticlayer
#knowledgegraphs

Enterprise sponsored #opensource:
ADP, a global leader in cloud based solutions for Human Capital Management, sponsored the development of “rules”, (https://github.com/ontop/ontop/pull/576), another great feature of @ontop4obda
.

#semanticlayer
#knowledgegraphs

Isn't the dbt semantic layer introducing the "N + 1 standard problem"? How is the data team preventing folks from defining in LookerML and other BI tools? Doesn't it create one more vendor lock? #dbt #semanticlayer? Curious to see some real-world experience. #datadon

Isn't the dbt semantic layer introducing the "N + 1 standard problem"? How is the data team preventing folks from defining in LookerML and other BI tools? Doesn't it create one more vendor lock? #dbt #semanticlayer? Curious to see some real-world experience. #datadon

Isn't the dbt semantic layer introducing the "N + 1 standard problem"? How is the data team preventing folks from defining in LookerML and other BI tools? Doesn't it create one more vendor lock? #dbt #semanticlayer? Curious to see some real-world experience. #datadon

Isn't the dbt semantic layer introducing the "N + 1 standard problem"? How is the data team preventing folks from defining in LookerML and other BI tools? Doesn't it create one more vendor lock? #dbt #semanticlayer? Curious to see some real-world experience. #datadon

Isn't the dbt semantic layer introducing the "N + 1 standard problem"? How is the data team preventing folks from defining in LookerML and other BI tools? Doesn't it create one more vendor lock? #dbt #semanticlayer? Curious to see some real-world experience. #datadon