Argues against using LLMs to generate SQL queries for novel business questions, highlighting the importance of human analysts for precision.
Part 1 of a series on data warehouse transformation flows, building intuition for analytics engineers and data professionals.
Explains the fundamentals of data modeling in Microsoft Power BI, covering tables, relationships, and calculated columns/measures for business intelligence.
A guide on how to model and calculate DynamoDB costs during the design phase to make informed architectural decisions.
A developer compares sleep API schemas from Oura, Whoop, and others, analyzing design choices and real-world discrepancies.
A statistical analysis of estimating a normal distribution using binary (yes/no) predictions from multiple scientists, applied to a temperature forecasting problem.
Analyzing the compatibility of GraphQL with DynamoDB's single-table design, discussing trade-offs and when each approach is preferable.
A technical guide to modeling one-to-one, one-to-many, and many-to-many relationships in MongoDB using the Mongoose ODM in Node.js.
Explores the mathematical and data science challenges of analyzing ordinal data, including tradeoffs in interpreting ordered scales and model limitations.
An introductory guide to database fundamentals, covering data design, relationships, and types of databases for application development.
A deep dive into DynamoDB partitions, explaining their role in data modeling and performance for the NoSQL database.
Explores the difference between inference and prediction in data modeling, using a Click Through Rate (CTR) example to contrast Machine Learning and Statistics.
A guide to advanced data modeling in Amazon DynamoDB, covering access patterns, single-table design, and filtering strategies.
Key takeaways from a talk on Amazon DynamoDB data modeling, covering primary keys, access patterns, and single-table design strategies.
A guide to quickly exploring and understanding a new PostgreSQL database using psql, covering initial setup and table inspection.
Explains DynamoDB single-table design patterns for scalable, high-performance NoSQL data modeling in serverless applications.
Explains how to model variable fields in ksqlDB using MAP instead of STRUCT for nested data, with practical examples.
A guide to designing a data model for a Django survey application, covering models for Survey, Question, Option, and Submission.
A deep dive into single-table design for DynamoDB, covering its concepts, benefits, and trade-offs for scalable applications.
Explains DynamoDB filter expressions, their limitations, and when to use them versus proper table design for efficient queries.
