Precisely

DECEMBER 12, 2023

It includes streaming data from smart devices and IoT sensors, mobile trace data, and more. Data is the fuel that feeds digital transformation. But with all that data, there are new challenges that may prompt you to rethink your data observability strategy. Learn more here.

Data Observability 52

Data Observability Data Quality Data Pipeline Machine Learning 52

The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. and Pandas or Apache Spark DataFrames.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

IBM Journey to AI blog

JUNE 5, 2024

That’s why today’s application analytics platforms rely on artificial intelligence (AI) and machine learning (ML) technology to sift through big data, provide valuable business insights and deliver superior data observability. AI- and ML-generated SaaS analytics enhance: 1.

Analytics 94

Analytics Analytics AI AI 94

ODSC - Open Data Science

FEBRUARY 28, 2023

To deliver on their commitment to enhancing human ingenuity, SAS’s ML toolkit focuses on automation and more to provide smarter decision-making. Making Data Observable Bigeye The quality of the data powering your machine learning algorithms should not be a mystery.

Data Science 96

Data Science Machine Learning Machine Learning AI 96

Precisely

FEBRUARY 10, 2023

Advanced analytics and AI/ML continue to be hot data trends in 2023. According to a recent IDC study, “executives openly articulate the need for their organizations to be more data-driven, to be ‘data companies,’ and to increase their enterprise intelligence.”

DataOps 52

DataOps Data Observability ML ML 52

AWS Machine Learning Blog

FEBRUARY 15, 2024

With the use of cloud computing, big data and machine learning (ML) tools like Amazon Athena or Amazon SageMaker have become available and useable by anyone without much effort in creation and maintenance. It also allows you to deploy and share these models with ML and MLOps specialists after creation.

ML 121

ML ML Data Science AWS 121

AWS Machine Learning Blog

AUGUST 21, 2024

Inside this folder, you’ll find the processed data files, which you can browse or download as needed. Access the output data using the AWS SDK Alternatively, you can access the processed data programmatically using the AWS SDK. Navigate to the bucket you specified as the output destination for your batch inference job.

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AWS Data Preparation ML ML 113