data engineering – Page 7 – Andrew Fairless, Ph.D.

What I Read: Dataset-Centric Visualization

By Andrew Fairless on May 23, 2022April 25, 2022

https://preset.io/blog/dataset-centric-visualization/ DATA ENGINEERINGThe Case for Dataset-Centric VisualizationMaxime BeaucheminMarch 30, 2022 “Different BI tools offer different approaches to building dashboards. On one end of the spectrum, you have tools that prescribeContinue readingWhat I Read: Dataset-Centric Visualization

What I Read: Data Observability vs. Data Testing

By Andrew Fairless on April 25, 2022March 12, 2022

https://towardsdatascience.com/data-observability-vs-data-testing-everything-you-need-to-know-6f3d7193b388?gi=6618bd7121fd Data Observability vs. Data Testing: Everything You Need to KnowYou already test your data. Do you need data observability, too?Lior GavishFeb 12 “In any data system, there are twoContinue readingWhat I Read: Data Observability vs. Data Testing

What I Read: Scale Real-time Data Infrastructure

By Andrew Fairless on April 4, 2022February 3, 2022

https://zhenzhongxu.com/the-four-innovation-phases-of-netflixs-trillions-scale-real-time-data-infrastructure-2370938d7f01 The Four Innovation Phases of Netflix’s Trillions Scale Real-time Data InfrastructureZhenzhong Xu2/1/2022“I think it’s a perfect time to summarize my learnings building the real-time data infrastructure at Netflix. IContinue readingWhat I Read: Scale Real-time Data Infrastructure

What I Watch: Engineering For Data

By Andrew Fairless on March 16, 2022January 20, 2022

https://youtu.be/jeMQld-6BtQ What Is Engineering For Data?Jan 5, 2022Continuous Delivery “What are the big mistakes that data scientists and big organisations often make when dealing with big data? What does engineeringContinue readingWhat I Watch: Engineering For Data

What I Read: Real-time machine learning

By Andrew Fairless on March 9, 2022January 20, 2022

https://huyenchip.com//2022/01/02/real-time-machine-learning-challenges-and-solutions.html Real-time machine learning: challenges and solutionsJan 2, 2022 • Chip Huyen “Starting with a batch prediction system, we’ll discuss what’s needed for a simple online prediction system using batchContinue readingWhat I Read: Real-time machine learning

What I Read: How Should Organizations Structure their Data?

By Andrew Fairless on February 23, 2022January 20, 2022

https://towardsdatascience.com/how-should-organizations-structure-their-data-c19b66d629e How Should Organizations Structure their Data?A review of three popular data warehousing techniquesMichael Berk “Efficient data infrastructure leads to efficient data scientists. How you structure your data as anContinue readingWhat I Read: How Should Organizations Structure their Data?

What I Read: MLOps Documentation

By Andrew Fairless on February 2, 2022January 20, 2022

https://www.kdnuggets.com/2021/12/best-practices-mlops-docs.html Best Practices for MLOps DocumentationBy Nifesimi Ademoye “Why does technical documentation matter in MLOps?…. MLOps levels are defined by the extent of automation of processes in an ML pipeline,Continue readingWhat I Read: MLOps Documentation

What I Read: Maps of Model Space, Stan

By Andrew Fairless on January 5, 2022December 11, 2021

https://statmodeling.stat.columbia.edu/2021/11/19/drawing-maps-of-model-space-with-modular-stan/ Drawing Maps of Model Space with Modular StanPosted on November 19, 2021 9:50 AM by AndrewThis post is by Ryan Bernstein. “What if instead of describing one model atContinue readingWhat I Read: Maps of Model Space, Stan

What I Read: AntiPatterns, MLOps

By Andrew Fairless on January 4, 2022December 11, 2021

https://arxiv.org/abs/2107.00079 Using AntiPatterns to avoid MLOps MistakesNikhil Muralidhar, Sathappah Muthiah, Patrick Butler, Manish Jain, Yu Yu, Katy Burne, Weipeng Li, David Jones, Prakash Arunachalam, Hays ‘Skip’ McCormick, Naren Ramakrishnan “HereContinue readingWhat I Read: AntiPatterns, MLOps

Tag: data engineering