ODSC - Open Data Science

JANUARY 9, 2024

Now that we’re in 2024, it’s important to remember that data engineering is a critical discipline for any organization that wants to make the most of its data. These data professionals are responsible for building and maintaining the infrastructure that allows organizations to collect, store, process, and analyze data.

Data Engineer 97

Data Engineer Data Engineering Data Engineering Data Engineering 97

Data Science Dojo

OCTOBER 10, 2023

The speaker is Andrew Madson, a data analytics leader and educator. The event is for anyone interested in learning about generative AI and data storytelling, including business leaders, data scientists, and enthusiasts. The event will be conducted online, making it accessible to a global audience.

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AI AI Data Observability Artificial Intelligence 243

Pickl AI

OCTOBER 11, 2023

Data Observability and Data Quality are two key aspects of data management. The focus of this blog is going to be on Data Observability tools and their key framework. The growing landscape of technology has motivated organizations to adopt newer ways to harness the power of data.

Data Observability 52

Data Observability Data Quality Data Pipeline Data Governance 52

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

IBM Journey to AI blog

FEBRUARY 26, 2024

That’s why data pipeline observability is so important. Data lineage expands the scope of your data observability to include data processing infrastructure or data pipelines, in addition to the data itself. The Basel Committee released BCBS 239 as far back as 2013.

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Data Pipeline Data Engineer Data Engineering Data Engineering 112

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. For example, neptune.ai Check out the Kubeflow documentation.

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Machine Learning Machine Learning ML ML 134

Alation

DECEMBER 7, 2021

Alation and Bigeye have partnered to bring data observability and data quality monitoring into the data catalog. Read to learn how our newly combined capabilities put more trustworthy, quality data into the hands of those who are best equipped to leverage it.

Data Quality 52

Data Quality Data Pipeline Data Observability Data Profiling 52