u/AviusAnima

Any data that gets heavy with numbers whether business related, or otherwise, gets difficult to digest real quick. I find that if you have to work with a lot of such data, it gets mentally fatiguing.

There are a lot of tools that visualize such data for you, but I'm curious to know which ones most of you prefer (is it a layer above your database provider, or something more modular like metabase?), and what your workflow is around such tools. I'd also love to know what your favorite feature in your preferred visualization tool is.

Any data that gets heavy with numbers whether business related, or otherwise, gets difficult to digest real quick. I find that if you have to work with a lot of such data, it gets mentally fatiguing.

There are a lot of tools that visualize such data for you, but I'm curious to know which ones most of you prefer, and what your workflow is around such tools. I'd also love to know what your favorite feature in your preferred visualization tool is.

Any data that gets heavy with numbers whether business related, or otherwise, gets difficult to digest real quick. I find that if you have to work with a lot of such data, it gets mentally fatiguing. There are a lot of tools that visualize data for you, but I'm curious to know which ones most of you prefer, and what your workflow is around such tools.

I personally feel like it's become much more convenient, especially for people with lesser experience in technical data analytics skills to solve their analytics problems with LLMs with access to MCP servers.

Ex: Tools like MongoDB Compass (and others) have started integrating "Query in natural language" and similar features which generate complex queries for you. For me, this has helped with not having to remember query syntaxes for different query langs and still being able to query across DB providers.

But I'd like to know how most of you feel about conversational analytics and the way people query databases is changing.

I personally feel like it's become much more convenient, especially for people with lesser experience in technical data analytics skills to solve their analytics problems with LLMs with access to MCP servers.

Ex: Tools like MongoDB Compass (and others) have started integrating "Query in natural language" and similar features which generate complex queries for you. For me, this has helped with not having to remember query syntaxes for different query langs and still being able to query across DB providers.

But I'd like to know how most of you feel about conversational analytics and the way people query databases is changing.

Hi everyone!

I'm working on a no-code agent builder project that helps you build and quickly deploy conversational analytics agents that respond with interactive charts and UI.

I've implemented dedicated support for multiple databases (NeonDB, Snowflake, DuckDB/Motherduck, Railway, Clickhouse and more) to make it easier to hook up databases for agents to query.

Here's an example agent I've built using the project: https://console.thesys.dev/app/-2PqdNdGjSQb6WrdYI9pR

Any feedback regarding agent output quality, UI, etc would be highly appreciated!

Hi everyone!

I'm working on a no-code agent builder that builds conversational analytics agents that respond with interactive charts and UI. I've implemented dedicated support for Snowflake to make it easier to hook up databases for agents to query.

Here's an example agent I've built using the project: https://console.thesys.dev/app/-2PqdNdGjSQb6WrdYI9pR

Any feedback regarding agent output quality, UI, etc would be highly appreciated!

Hi everyone!

I'm working on a no-code agent builder that builds conversational analytics agents that respond with interactive charts and UI. I've implemented dedicated support for DuckDB to make it easier to hook up databases for agents to query.

Here's an example agent I've built using the project: https://console.thesys.dev/app/-2PqdNdGjSQb6WrdYI9pR

Feedback would be highly appreciated!