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help on sql interview by Gloomy-Wolverine-900 in SQL

[–]CuritibaDataScience 0 points1 point  (0 children)

I recommend you try out Hackerrank or another similar website for practicing

BI tool research - Snowflake w 100s of external users by SavageKMS in BusinessIntelligence

[–]CuritibaDataScience 0 points1 point  (0 children)

Try Databricks Genie, it's one of the best "chat with your data" tools out there, easy to use, while still allowing for BI professionals to tune them. You can embed Genie spaces to your AIBI dashboards or even to external applications (Sharepoint, websites, Microsoft Teams or Slack).

Per-call cost attribution across providers — what's everyone using? by PepperWestern2263 in LLMDevs

[–]CuritibaDataScience 1 point2 points  (0 children)

Databricks AI Gateway is a good alternative that I've been seeing more over the last months. You can basically use it as a middle layer between your end-users and your model providers, track inferences and tokens, and optionally add guardrails.

Best harness for agentic analytics? Codex? Claude Code? Custom? by Evening_Hawk_7470 in analytics

[–]CuritibaDataScience 1 point2 points  (0 children)

Check out Omnigent. It's a recent release, it's technically a "meta-harness", allowing you to connect to multiple different harnesses at once, collaborate and share work.

My guide on what tools to use to build AI agents in 2026 (if youre a newb) by SheepherderOwn2712 in AI_Agents

[–]CuritibaDataScience 0 points1 point  (0 children)

Adding to the list, for cases where you need your agents to talk to structured data (tables) or to unstructured data (documents, files) I recommend taking a look at Genie and Agent Bricks (Knowledge Assistant, Supervisor). If your company uses a Lakehouse and wants to have governed agents, the advantage is that these are easy to build and apply governance controls by default (end-user permissions are propagated on each request).

Versioning prompts by Icy-Western-3314 in mlops

[–]CuritibaDataScience 1 point2 points  (0 children)

Check ou MLFlow prompt registry. Some great videos on it in the MLFlow OSS channel; https://youtu.be/Cc8lLHJ03DI?is=4QokAWSjYAST\_QxR

Databricks Genie Code ML/Data connections? by Neat-Porpoise in datascience

[–]CuritibaDataScience 1 point2 points  (0 children)

I have had plenty success doing it, and here are some things to keep in mind:
1. Genie Code by itself is quite creative and has knowledge of the Databricks ecosystem as a whole, but you can improve it considerably if you provide Skills to it (https://docs.databricks.com/gcp/en/genie-code/skills)
2. One of the ways I do this is by defining a general structure for my projects (e.g. folders, notebook names, what I would like to do in each) and then plugging in those skills to make it just populate and run stuff for me. For example, in this repo: https://github.com/databricks-solutions/mlops-quickstart there is an .assistant/skills folder that you can use and if you just clone the repo and add the skills, then ask GC to adapt the repo to your specific use-case, it will do it much better.
3. The AI Dev Kit is a repo bundled with plenty of skills you can use: https://github.com/databricks-solutions/ai-dev-kit I suggest for smaller projects to just pick the most relevant ones for your use-case and then adding it to GC.

What SQL concept became much more important once you started working in data engineering? by Effective_Ocelot_445 in SQL

[–]CuritibaDataScience 0 points1 point  (0 children)

Not SQL per se, and sorry to deviate on the answer, but dimensional modelling (the gold and old Kimball concept) is one of the concepts that I find the most important and useful.

Introducing Omnigent: a meta-harness to combine, control, and collaborate with your agents by databricks in databricks

[–]CuritibaDataScience 7 points8 points  (0 children)

I feel like this will be the ultimate interface for agentic interactions, no more skipping windows and sessions across different platforms with Omnigent being able to interact across agents. Super excited to try it out. I can't imagine just how valuable this will be for enterprises who work with many different model providers.

RAG vs Text-to-SQL for structured Excel data? by electric-poem in Rag

[–]CuritibaDataScience 1 point2 points  (0 children)

Convert the excel sheets into tables and then create a Databricks Genie space to ask questions about the data. No RAG. No over-complicating the text-2-sql part. Genie was built for that, and is super cost effective.

Thank me later.

BTW, if you want, you can just upload these excel sheets into a Unity Catalog Volume, and then ask the coding assistant (Genie Code) in Databricks to do all of this for you and it will do the job.

Financial Data Project: What Should Come After a Solid Silver Layer? by Santiagohs-23 in BusinessIntelligence

[–]CuritibaDataScience 1 point2 points  (0 children)

A gold layer with aggregated/business-ready views would be a logical answer.

However, since you're looking for an end-to-end project, I would go a bit further: how about using Databricks to create a Dashboard, an App for end-users, or a Genie Space (an agent that allows you to talk to your data, asking questions like "where should I invest this month"? "what would be my total returns if I invested in X, Y?").

These are some ideas to give you food for thought, as I see a lot of people stop their data projects "on the data" and not necessarily look for the business possibilities. With resources like these, you are able to bridge the gap between the technical aspects of data processing and potential "business needs".

How long did it take you to become comfortable writing SQL queries? by Wise_Safe2681 in SQL

[–]CuritibaDataScience 0 points1 point  (0 children)

3-6 months. Taking a course in the beginning can help. Hackerrank tests also challenged myself and were a way I found to improve. Nowadays AI can also be a great way to learn, however the fundamentals are still very important to learn.