Alation

MARCH 22, 2022

Data people face a challenge. They must put high-quality data into the hands of users as efficiently as possible. DataOps has emerged as an exciting solution. As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. Accenture’s DataOps Leap Ahead.

DataOps 52

DataOps Data Pipeline Data Engineer Data Engineering 52

Alation

JUNE 21, 2022

The audience grew to include data scientists (who were even more scarce and expensive) and their supporting resources (e.g., ML and DataOps teams). After that came data governance , privacy, and compliance staff. Power business users and other non-purely-analytic data citizens came after that. data pipelines) to support.

DataOps 52

DataOps Data Scientist Data Quality Data Pipeline 52

Iguazio

JANUARY 16, 2024

Iguazio is an essential component in Sense’s MLOps and DataOps architecture, acting as the ML training and serving component of the pipeline. With Iguazio, Sense’s ML team members can pull data, analyze it, train and run experiments, making the process automated, scalable and cost-effective. Enabling quick experimentation.

ML 52

ML ML DataOps Data Scientist 52

Iguazio

JANUARY 16, 2024

Iguazio is an essential component in Sense’s MLOps and DataOps architecture, acting as the ML training and serving component of the pipeline. With Iguazio, Sense’s data professionals can pull data, analyze it, train and run experiments. With Iguazio, data scientists and ML engineers start having superpowers.”

ML 52

ML ML DataOps Data Scientist 52

Pickl AI

DECEMBER 11, 2024

Focusing only on what truly matters reduces data clutter, enhances decision-making, and improves the speed at which actionable insights are generated. Streamlined Data Pipelines Efficient data pipelines form the backbone of lean data management.

Data Silos 52

Data Silos Data Pipeline Artificial Intelligence Artificial Intelligence 52

Alation

APRIL 18, 2023

This, in turn, helps them to build new data pipelines, solutions, and products, or clean up the data that’s there. It bears mentioning data profiling has evolved tremendously. Data migration Digital transformation is ongoing. To achieve this, these developers need to build data pipelines that migrate data.

Data Profiling 52

Data Profiling Data Quality Data Governance Data Pipeline 52