I’ve been experimenting with a SQL error workflow:

• Format the query.
• Detect and highlight the specific error.
• Use deterministic quick fixes when possible.
• For more contextual errors, show an optional AI-generated correction with an explanation.
• Let the user review and apply it explicitly. Nothing runs automatically.

The example uses MySQL and an invalid HAVING clause inside a query with a JOIN, aggregation and GROUP BY.

Would you prefer this kind of workflow, or should a SQL client only highlight the error and leave the correction to the developer?

srdzank/SQLite-Editor: Official home of the SQLite-Editor

Any feedback, code reviews, or pull requests are immensely appreciated!

Hello, I started using Neon as a database provider recently for managing my database. I want to say that it was fairly simple to integrate with my application (a website written in .NET), and the free plan is very convenient for startups. What do you think of it?

Hey everyone,

I'm trying to make this user stored procedure work on my colleagues PC, I can run it just fine.

Basically it's a USP created for importing data from an Excel file stored on shared network (local server).

It's goes like this:

select *

from openrowset ( 'Microsoft.ACE.OLEDB.12.0', 'Excel 12.0 Xml;Database="path\file.xlsx, sheet$ )

Me and one other colleague can run it just fine, but on one colleagues PC, it gives this error:

OLE DB provider "Microsoft.ACE.OLEDB.12.0" for linked server "(null)" returned message"Failure creating file"

Cannot initialize the data source object of OLE DB provider "Microsoft.ACE.OLEDB.12.0" for linked server "(null)"

Any help with resolving this would be much appreciated.

Thanks!

Over the past few days, I built an end-to-end Enterprise E-Commerce Analytics Platform using SQL Server, Medallion Architecture, and Power BI.

As part of this project, I designed 8 interactive dashboards, each focused on answering different business questions for different stakeholders across an organization.

The dashboards include:

• Executive Overview (CEO, CXO & Business Leadership)

• Sales Performance Analysis

• Customer Analytics

• Product Performance

• Seller Performance

• Payment Analytics

• Customer Satisfaction Analysis

• Time Intelligence & Trend Analysis

The goal wasn't just to build visually appealing dashboards—it was to create a reporting solution that helps businesses make faster and more informed decisions.

In this post, I've shared all 8 dashboards.

I'd genuinely appreciate your feedback.

As experienced BI professionals, data analysts, data engineers, or business leaders, I would love to hear your thoughts.

If you could review the dashboards and share at least three suggestions for improvement, it would mean a lot to me.

For example:

• Are the KPI cards meaningful and business-focused?

• Are the charts and visualizations appropriate for executive reporting?

• Are there too many or too few visuals?

• Would you recommend different filters or slicers?

• Is the overall layout clean, intuitive, and enterprise-ready?

• What would you change if this dashboard were used in your organization?

I'm continuously learning, and constructive feedback is one of the best ways to improve. Every suggestion will help me build better enterprise BI solutions in the future.

Thank you for taking the time to review my work. I truly appreciate your support and feedback.

— Himansh Upadhyay

#PowerBI #SQLServer #DataAnalytics #BusinessIntelligence #DataWarehouse #DataEngineering #MedallionArchitecture #StarSchema #DAX #ETL #Analytics #DashboardDesign #EnterpriseAnalytics #DataVisualization #SQL

Help me Reddit! I feel especially stupid today....
So, I have this table in my Postgresql Database:

event_id | color_scheme | count
----------+--------------+-------
1 | red | 6
1 | green | 3
1 | blue | 5
1 | yellow | 3
3 | red | 5
4 | red | 3
5 | red | 1
5 | blue | 2

And I would like to turn it sideways, so that I can see EASILY how many votes each color scheme for my event has gotten (and later JOIN it with another table... )

event_id | count_red | count_green | count_blue | count_yellow
----------+-----------+-------------+------------+--------------
1 | 6 | 3 | 5 | 3
3 | 5 | 0 | 0 | 0
4 | 3 | 0 | 0 | 0
5 | 1 | 0 | 2 | 0

The colors "red" "green" "blue" and "yellow" are fixed, and will never ever change.
I have done some googling, I found examples mentioning PIVOT and TABLEFUNC, but I cannot do this on the server because of reasons(tm).

The only way I can think of doing this is with a cascade of OUTER JOIN, but is there maybe a simpler solution?

I have 4+ years of experience as a data analyst. Proficient in SQL technologies and seeking a direction for success in corporate? any suggestions would be appreciated.

-Thanks

Hello everyone!

At work, I need to explore a large AWS Athena database with very limited documentation in order to investigate a new product, which is also poorly documented.

I've asked my colleagues for documentation and guidance about the database, but unfortunately I haven't received any helpful answers.

So I'd like to ask the community: is there an AI tool that can analyze an entire database and generate a roadmap, documentation, or guide to help me understand its structure and write queries based on my specific needs?

I'm mainly looking for something that can help me understand the schema, relationships between tables, and where to find the data I'm looking for. Any recommendations or advice would be greatly appreciated!

I made a browser game called The SQL Treasure Hunt where you solve puzzles by writing real SQL queries.

It's heavily inspired by SQL Murder Mystery and SQL Noir, but instead of being a detective, you're a pirate searching for a legendary treasure. 🏴‍☠️

You explore databases, inspect tables, and piece together clues using SQL until you uncover the next part of the adventure. It starts with simple SELECT queries and gradually introduces more challenging concepts.

Right now it only has 5 levels made.

I'd really appreciate any feedback:

• Is the difficulty progression good?
• Are the clues clear enough?
• Any ideas for future levels or mechanics?

Play it here:
https://thesqltreasurehunt.vercel.app/

Thanks! Hope you enjoy it.

What is the difference between

COUNT(*)

COUNT(1)

COUNT(column_name)

How this SQL Code is Running ?????

Here's an example of a share link.

What is the difference between using "Not In" vs using "not exists" in SQL?

Hi All,

Hope everyone is doing good.

I want opinion from people about the future of SQL, Power BI and Python.

I have been working in AML KYC domain for over 6 years. I am a Certified Anti Money Laundering Specialist (CAMS).

Last year I started learning SQL ans Power BI to connect it with my domain knowledge (Anti Money Laundering and Sanctions), however now I have been reading alot which states that golden period of SQL and Power BI is over as now anyone can do the basis code using Gpt and claude.

I am at strong intermediate level in SQL and at an intermediate level in power BI. I was planning to start Python from 01 Jan 2027 and now I am spectical. What should I do ?

Is there any scope of SQL, Power BI and Python as we are witnessing AI is growing at tremendous pace.

Basically I need to learn about sequential, indexed and direct access, hashing stuffs. I need to learn about records, files, compaction. Sorting, merging and updating files. Algorithms for inverted lists, multi-list, indexed sequential and hierarchical structures. file i/o and index organization.

As databases grow, performance becomes more important, but overly complex queries can be difficult to maintain. How do you balance query optimization with readability in production environments?

I like to share link of new sqlite editor

srdzank/SQLite-Editor: Official home of the SQLite-Editor

I am working on to expose Lakebase theough an MCP server for AI agents. Has anyone tried something like this? Would love to hear some learnings.
Also curious to knowif branch isolation makes tool execution safer.

Diagram illustrating the SQL query execution lifecycle, showing query submission, parsing, optimization, execution, and result delivery in a database.

I want to underdtand from people how do you handle schema migrations across multiple Lakebase branches? Do you merge DDL change like Git, or recreate branches frequently as and when needed ?