Newsletter Issue 20: What really matters is the quality of the data, the data literacy at the organization, and the motives behind using data analytics.
Newsletter Issue 17: SQL is dead. Long live SQL. Why SQL is thriving even after 48 years. Resources to learn and master SQL.
Newsletter Issue 16: With diverse data sources, multi-cloud, and data mesh scenarios becoming increasingly common, a misfit data pipeline orchestration tool can multiply your woes.
Various types of SQL Joins: inner, left, right, full, and cross. Understanding SQL joins will help you in making them fast.
Newsletter Issue 6: Cheatsheets and decision trees to find the best visualization for your data and purpose
Newsletter Issue 5: Examines the effort-cost spectrum for data collection approaches from do-it-yourself to fully-outsource-it w.r.t. team's ability/budget.
Difference between SQL and NoSQL database. When to choose NoSQL over SQL. Decision tree to pick from RDBMS, key-value, wide column, document, graph dbs.
How to efficiently iterate over rows in a Pandas DataFrame and apply a function to each row. 5 simple yet faster alternatives to Pandas apply and iterrow methods.
Scalable and efficient data pipelines are as important for the success of data science and machine learning as reliable supply lines are for winning a war.