Here is a humorous recent example of what one can achieve with basic data exploration, without even going into any advanced ML techniques. In this recent project I was asked to study response time log of an online service running
4 reasons for building Data Lakes… or not
Data Lakes are repositories where data is ingested and stored in its original form, without much (or any) preprocessing. This is in contrast to traditional data warehouses, where much effort is in the ETL processing, data cleansing and aggregation, to
Lecture notes: Introduction to Apache Spark
In Lecture 7 of Big Data in 30 hours lecture series, we introduce Apache Spark. The purpose of this memo is to serve to the students as a reference of some of the concepts learned. About Spark Spark, managed by
Product Owner vs Product Manager vs Architect
This short memo is to clarify the proper usage of these roles in the context of software development projects: Product Owner, Product Manager / Manager, and (Software/Product) Architect. Product Owner The term Product Owner is mainly used in Scrum context.
Collected thoughts on implementing Kafka data pipelines
Below are my recent notes and thoughts collected during the recent work with Kafka, to build data streaming pipelines between data warehouses and data lakes. Maybe someone will benefit. The rationale Some points on picking (or not picking) Kafka as