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Month: January 2023

Hanukah of Data: Solving a Data Challenge with AI and SQL

Hanukah of Data: Solving a Data Challenge with AI and SQL

Published January 23, 2023

A colleague of mine recently gave me a data challenge called the Hanukkah of Data (https://hanukkah.bluebird.sh/about/) which has 8 challenges. I decided to try them out in DataDistillr. The challenges use a fictional data set which consists of four tables: a customer table, a product table, an order table and a table linking orders to products. The data was very representative of what a customer database might look like. I did, however make some modifications to the data to facilitate querying. The address line was not split up into city, state, zip. So I imported this data into a database, and then split these fields up into separate columns.

Overall, this was a really well done challenge and my compliments to the authors.

SPOILER ALERT

If you choose to read beyond this point, it will have my answers so if you want to try it yourself, stop right here. I warned you… Really … go no further.

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ChatGPT, Meet DataDistillr! You’ll have lots to discuss!

ChatGPT, Meet DataDistillr! You’ll have lots to discuss!

Published January 5, 2023

Happy New Year everyone! I’m pretty excited about this. Like every other tech geek out there, I was experimenting with ChatGPT when it was announced in December of 2022.

Initially I was amazed at how well the AI appeared to work, and somewhat terrified with what people could actually do with it. I teach a database class at the University of Maryland Baltimore County (UMBC) and I was really worried that students could use ChatGPT to generate answers to essay questions on my exams. I wanted to see if there were ways of phrasing questions that would make it obvious that a person did not write them. After using ChatGPT for a while, I do think it would be possible to detect if a student was using AI to write their papers, as the quality and style are fairly distinct.

But I digress…

What really intrigued me was that these models can write SQL queries using natural language. Of course the fact that you can write a SQL query isn’t necessarily useful unless you understand the schema of the underlying data and you have a query engine or database capable of executing that query.

Well… guess what…

My team and I have been hard at work at incorporating this powerful feature into our DataDistillr. Today, I am happy to announce that we’ve added natural language AI capability to DataDistillr!

Continue readingChatGPT, Meet DataDistillr! You’ll have lots to discuss!
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