Remove Data Observability Remove Data Quality Remove Download
article thumbnail

Alation 2022.2: Open Data Quality Initiative and Enhanced Data Governance

Alation

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

article thumbnail

What Is Data Observability and Why You Need It?

Precisely

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.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

16 Companies Leading the Way in AI and Data Science

ODSC - Open Data Science

Making Data Observable Bigeye The quality of the data powering your machine learning algorithms should not be a mystery. Bigeye’s data observability platform helps data science teams “measure, improve, and communicate data quality at any scale.”

article thumbnail

Data Trends for 2023

Precisely

Read our Report Improving Data Integrity and Trust through Transparency and Enrichment Data trends for 2023 point to the need for enterprises to govern and manage data at scale, using automation and AI/ML technology. To learn more about these and other data trends, download your free copy of the IDC spotlight report.

DataOps 52
article thumbnail

MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

Data quality control: Robust dataset labeling and annotation tools incorporate quality control mechanisms such as inter-annotator agreement analysis, review workflows, and data validation checks to ensure the accuracy and reliability of annotations. Data monitoring tools help monitor the quality of the data.

article thumbnail

Claims Processing with Generative AI: Making Sense of the Data

Precisely

Yet experts warn that without proactive attention to data quality and data governance, AI projects could face considerable roadblocks. Data Quality and Data Governance Insurance carriers cannot effectively leverage artificial intelligence without first having a clear data strategy in place.

AI 72
article thumbnail

Mainframe Data: Empowering Democratized Cloud Analytics

Precisely

That means that for data to be trustworthy and ready to power the enterprise it should be accurate, timely, and contextually relevant. Consistency, accuracy, and completeness are aspects of data integrity, of course, but true data integrity extends much further than just data quality.