A software architect's humorous account of a client derailing a professional Power BI dashboard project with a chaotic, self-built data model.
An introduction to data modeling concepts, covering OLTP vs OLAP systems, normalization, and common schema designs for data engineering.
A technical exploration of using C# records and collections for immutable data models, covering benefits and practical implementation details.
Explains the CQRS pattern, its benefits for scaling read/write operations independently, and when to use it in software architecture.
A recap of AWS re:Invent 2024 Day 3, covering sessions on advanced DynamoDB data modeling and key AI/Data announcements from Amazon Bedrock.
A critique of modern bug trackers, proposing a 'separation of concerns' principle to better distinguish factual bug records from planning data.
Explores the differences between event and entity data modeling, when to use each approach, and practical design considerations for structuring data effectively.
Explores Data-Oriented Programming principles in Java, focusing on modeling data with records and sealed types.
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.
