ETL vs ELT: Understanding Data Pipelines
Learn the difference between ETL and ELT data pipelines. Understand extract, transform, load, when to use each approach, modern tools like dbt, and how to build simple pipelines in Python.
Introduction to Data Warehousing Concepts
Learn data warehousing fundamentals: OLTP vs OLAP, star schema, dimension and fact tables, slowly changing dimensions, data lakes, lakehouses, and modern cloud warehouses explained clearly.
Big Data Basics: What Changes When Data Gets Large
Learn what big data really means for data scientists. Understand when scale changes everything, the limitations of pandas, and practical tools like Dask, Polars, Spark, and cloud solutions.
Understanding Data Granularity
Learn what data granularity means in data science. Master grain definition, aggregation levels, rollup vs drill-down, mismatched granularity bugs, and choosing the right level of detail for analysis.
Working with Date and Time in Python
Master date and time in Python. Learn datetime, timedelta, timezone handling, pandas Timestamp, date arithmetic, parsing, formatting, and common pitfalls for data science work.
