Iguazio

JANUARY 16, 2024

Since AI is a central pillar of their value offering, Sense has invested heavily in a robust engineering organization, including a large number of data and data science professionals. This includes a data team, an analytics team, DevOps, AI/ML, and a data science team. Enabling quick experimentation.

ML 52

ML ML DataOps Data Scientist 52

Iguazio

JANUARY 16, 2024

Since AI is a central pillar of their value offering, Sense has invested heavily in a robust engineering organization including a large number of data and AI professionals. This includes a data team, an analytics team, DevOps, AI/ML, and a data science team. The Solution Sense chose Iguazio as their MLOps solution.

ML 52

ML ML DataOps Data Scientist 52

ODSC - Open Data Science

JULY 20, 2023

Video of the Week: Beyond Monitoring: The Rise of Data Observability Watch as Monte Carlo’s Shane Murray introduces “Data Observability” as the game-changing solution to the costly reality of broken data in advanced data teams.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

Snorkel AI

AUGUST 29, 2023

GPT-3’s generative AI helped unlock additional capacity for me as the Data Science Content Lead here at Snorkel AI. Sometimes it would return a list of tweets with the specified tone followed by the text, such as “Funny: With Snowflake and Snorkel AI, you can label your data faster than you can say ‘DataOps’!

DataOps 52

DataOps Python AI AI 52

Snorkel AI

AUGUST 29, 2023

GPT-3’s generative AI helped unlock additional capacity for me as the Data Science Content Lead here at Snorkel AI. Sometimes it would return a list of tweets with the specified tone followed by the text, such as “Funny: With Snowflake and Snorkel AI, you can label your data faster than you can say ‘DataOps’!

DataOps 52

DataOps Python Artificial Intelligence Artificial Intelligence 52

Snorkel AI

AUGUST 29, 2023

GPT-3’s generative AI helped unlock additional capacity for me as the Data Science Content Lead here at Snorkel AI. Sometimes it would return a list of tweets with the specified tone followed by the text, such as “Funny: With Snowflake and Snorkel AI, you can label your data faster than you can say ‘DataOps’!

DataOps 52

DataOps Python Artificial Intelligence Artificial Intelligence 52

DataRobot Blog

SEPTEMBER 13, 2022

At this level, the data science team will be small or nonexistent. Businesses will then require more information-literate staff, but they’ll need to contend with an ongoing shortage of data scientists. These features reduce the need for a large workforce of data professionals. BARC ANALYST REPORT. Download Now.

Data Scientist 52

Data Scientist ML ML AI 52

Alation

OCTOBER 12, 2021

Enterprise data analytics integrates data, business, and analytics disciplines, including: Data management. Data engineering. DataOps. … In the past, businesses would collect data, run analytics, and extract insights, which would inform strategy and decision-making. Business strategy. Analytics forecasting.

Analytics 52

Analytics Analytics Data Governance DataOps 52

AWS Machine Learning Blog

JULY 31, 2023

Conclusion SageMaker Canvas provides powerful tools that enable you to build and assess the accuracy of models, enhancing their performance without the need for coding or specialized data science and ML expertise. He designs modern application architectures based on microservices, serverless, APIs, and event-driven patterns.

ML 93

ML ML Data Preparation Machine Learning 93

Pickl AI

DECEMBER 11, 2024

Governance and Compliance Adhering to governance and compliance standards is non-negotiable in lean data management. To protect sensitive information, establish clear policies for data access, usage, and retention. Regular audits and automated compliance checks can ensure your systems stay up-to-date with evolving regulations.

Data Silos 52

Data Silos Data Pipeline Artificial Intelligence Artificial Intelligence 52

The Data Administration Newsletter

FEBRUARY 15, 2022

The future of data democratization lies in the hands of your end-users. They are already generating data, they know what problems they need to solve with it, and they know how to use that information for business value. It is time you let the end-users pull their own weight without having to rely on IT […].

DataOps 52

DataOps Big Data Big Data Business Intelligence 52