Completely agree! A semantic layer is essential for scaling analytics to enterprise complexity.
Another alternative here is Veezoo [0], which combines the semantic layer (a Knowledge Graph) and self-service analytics into one integrated solution.
We built it specifically for the analytics use-case for both the "data persona" to manage the semantic layer, as well as for the "business persona" to analyze the data.
If you’re looking for a semantic-layer + (embedded) BI solution right out of the box. This could be a fit.
Having an LLM be in charge of business logic is madness.
There cannot be any AI involved when processing the definition of a KPI. Otherwise you'll never be able to roll it out to thousands of users when there's always a 90% (or even 99%) chance that the business logic might not get applied correctly.
Check out what we do at Veezoo (https://www.veezoo.com) with the Knowledge Graph / Semantic Layer to mitigate that.
Agree that an approach that more semantically models the data is better,
especially when you want to eventually let the non-technical users ask questions.
When you're on a higher abstraction level, it also allows you to make clear definitions (e.g. for certain KPIs) and define business logic that always needs to be applied to get the correct results.
There you don't want to leave it up to chance that a filter gets hallucinated in or out when you ask e.g. about your company's revenue.
At Veezoo (https://www.veezoo.com) we have taken the approach that instead of going directly to SQL. So when a user asks a question, Veezoo translates it first into a query against the Knowledge Graph (which represents the business objects, their relationship etc.). From there we compile it into a SQL query depending on the target database (they all have slight differences) without any AI involvement. In this compilation step we also make sure that the business logic is properly applied.
I dislike about your pricing that it tells me reasonable 29$ and then in the fineprint it says minimum 5 users. I get the reasoning behind your pricing logic, but I really dislike it. Now as solo business owner I'm gone.
When Veezoo connects to a database / dwh for the first time, an initial Semantic Layer / Knowledge Graph gets built automatically based on the data itself. We try to recognize how the columns link to other tables, try to identify units, and other semantic information e.g. if something is a "Location" or a "Country" and so on.
The whole conversational "plain english" querying then operates on top of the semantic layer, ensuring business logic (and other governance topics) are always respected.
"So is enterprise conversational BI impossible in 2023? Will there be a few more years of academic papers and company AI hackathon projects before a solution can be deployed in production? We don’t think so." -- from the medium article.
Want to put your attention to https://www.veezoo.com as well. A conversational self-service analytics solution that's been around since 2016 and productively deployed in fortune 500 companies and used by thousands of users daily :)
Congrats on the launch - and also reaching the top of the Spider dataset. We're very familiar with that dataset and its difficulties :)!
Another alternative here is Veezoo [0], which combines the semantic layer (a Knowledge Graph) and self-service analytics into one integrated solution.
We built it specifically for the analytics use-case for both the "data persona" to manage the semantic layer, as well as for the "business persona" to analyze the data.
If you’re looking for a semantic-layer + (embedded) BI solution right out of the box. This could be a fit.
0 - https://www.veezoo.com