My experience with Snowflake spans several different organizational contexts, it’s power in scaling to meet business data requirements is closely followed by how the costs can similarly scale. This post explores practical strategies to help you reduce your Snowflake costs without sacrificing performance. Starting with general guidance, then dipping into technical strategies including dbt specific packages and approaches.
While writing my previous post on Running Oracle SQL & PL/SQL: Free Online Execution environments compared I decided to do a comparison between using AI to generate content, and writing the article myself. I had previously as an experiment used AI to write much of my post on my Gmail Clean-up post.
I used both Gemini and ChatGPT (both outputs below for comparison).
If you only want to run something quickly, you probably want an online platform that provides a convenient environment for writing, executing, and sharing SQL queries. Here I compare some for use with Oracle SQL & PL/SQL
In today’s fast-paced development world, efficiency is paramount. AI can significantly accelerate the coding process, including the creation of scripts to interact with various data formats. This blog post will explore how to use AI assistance to generate Python code for loading a custom XML file.
Not so much Data & Database, but useful advice for managing a Gmail account once the storage gets a bit full (and Google suggests paying for storage).
Yes, the title is clickbait, but the savings are real! The approach can be applied to save money on any cloud data infrastructure. The saving in question applies to regular refreshes, not other data processes (more on that in the future).
An approach for creating a dbt demo project which can be shared and run easily by any developer. From an empty directory, to dbt run in under 5 minutes.
I’ve been using eclipse as an IDE of choice with dbt for a couple of years, here is how I configure it for working with dbt projects.
This is a side project of mine, something to keep me out of mischief at home. My aim for this project is to be an example/template/starting point for using flask for a quick (and dirty) approach to a Master Data Management (MDM) application AKA a Data Warehouse Management Application (DWMA).
Some time ago what started as one article on dates and their value, turned into a mini-series (nearly as engaging as The Queens Gambit). I kept finding more to say about dates and examples to give. I’m now pulling them together with a little narrative.