How to Build Fact and Dimension Tables in dbt
Learn how to build business-ready fact and dimension tables in dbt using a simple Gold layer example with dim_course, dim_student, and fact_enrollment.
Deep Learning Nerds Academy
The ultimate Learning Platform for AI, Data Science, Data Analytics and Data Engineering.
Search posts, subjects and tutors
Popular subjects
Why Codex Is a Productivity Booster for Data Engineers
Learn why Codex can make Data Engineers more productive by helping with dbt YAML, column descriptions, SQL reviews, debugging, boilerplate, and project conventions.
LangChain Vector Stores Explained for Beginners: Store and Search Embeddings for RAG
Learn how LangChain vector stores keep embeddings searchable for RAG, semantic search, document retrieval, and beginner-friendly AI applications.
LangChain Embeddings Explained for Beginners: Turn Text into Vectors for RAG
Learn how LangChain embeddings turn text into vectors for RAG, semantic search, document retrieval, clustering, and similarity workflows.
How to Use Codex to Create dbt Models
Learn how to use Codex to create a dbt Gold model from existing Silver models with clear prompts, dbt ref(), YAML tests, and a practical review workflow.
How to Use Codex in Visual Studio Code: Step-by-Step Guide
Learn how to use Codex in Visual Studio Code, connect it to a local project, add AGENTS.md instructions, and start your first coding task.
Understanding _dlt_id and _dlt_parent_id in dlt
Learn what _dlt_id and _dlt_parent_id mean in dlt, why they appear in normalized tables, and how to use them in SQL joins.
LangChain Text Splitters Explained for Beginners: Split Documents for RAG
Learn how LangChain text splitters break long documents into useful chunks for RAG, semantic search, summarization, and retrieval workflows.
Codex vs ChatGPT: What Is the Difference for Coding?
Learn the difference between Codex and ChatGPT for coding, when to use each tool, and how beginners can combine them in a practical workflow.
You might also like
