- How Bad Data is Affecting Your Organization’s Operational Efficiency - Mar 5, 2020.
Despite recognizing the importance of data quality, many companies still fail to implement a data quality framework that could protect them from making costly mistakes. Poor data does not just cause revenue loss – it’s the reason your company could lose employees, customers and reputation!
Business, Data Management, Data Operations, Data Quality, Efficiency
- Managing Machine Learning Cycles: Five Learnings from comparing Data Science Experimentation/ Collaboration Tools - Jan 29, 2020.
Machine learning projects require handling different versions of data, source code, hyperparameters, and environment configuration. Numerous tools are on the market for managing this variety, and this review features important lessons learned from an ongoing evaluation of the current landscape.
Collaboration, Comet.ml, Data Operations, Data Workflow, DataOps, MLflow, MLOps, Pipeline, Reproducibility
- Data Science with Optimus Part 2: Setting your DataOps Environment - Apr 16, 2019.
Breaking down data science with Python, Spark and Optimus. Today: Data Operations for Data Science. Here we’ll learn to set-up Git, Travis CI and DVC for our project.
Apache Spark, Data Operations, Data Science, Python, Workflow
- Merkle: Data Operations Lead - Jul 2, 2015.
The ideal candidate has some Ad Ops experience and is familiar with the ad:tech ecosystem, including DMP, DSP, Facebook, ad servers, mobile platforms, portals, and exchanges as well as traditional offline processes.
Columbia, Data Operations, MD, Merkle, Online advertising