Databand.ai

JULY 17, 2023

DataOps vs. MLOps: Similarities, Differences, and How to Choose Joseph Arnold July 17, 2023 What Is DataOps? By adopting a set of best practices inspired by Agile methodologies, DevOps principles, and statistical process control techniques, DataOps helps organizations deliver high-quality data insights more efficiently.

Data Pipeline 52

Data Pipeline Machine Learning High Quality Data BI 52

Advancing Analytics: Data Engineering

MARCH 5, 2019

Azure Databricks training live We arrived on the Thursday (SQLBits day 2) to deliver a sold out full day training session on Big Data processing with Azure Databricks titled "Data Engineering Vs Data Science". I am in the process of curating those questions in to a blog (there are 70 questions, so it might take a few days).

Deep Learning 52

Deep Learning Big Data Machine Learning Data Science 52

ProjectPro

FEBRUARY 25, 2022

The blog starts with an introduction to MLOps, skills required to become an MLOps engineer, and then lays out an MLOps learning path for beginners. Usually, data scientists do not have a strong background in engineering and cannot thus follow DevOps norms. Ability to understand DevOps practices and abide by them.

Deep Learning 52

Deep Learning Algorithm Machine Learning Data Science 52

phData: Data Engineering

JANUARY 3, 2022

When is it more profitable to use method A vs. method B? You also have to be concerned about merge strategies (merge commit vs squash) in order to be able to revert changes confidently. This was made more well known by Docker, however, they weren’t the first to provide containerization capabilities.

IT 52

IT AWS Software Engineer Software Engineering 52