Remove Data Discovery Remove Data Quality Remove ML
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Five benefits of a data catalog

IBM Journey to AI blog

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

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Why data governance is essential for enterprise AI

IBM Journey to AI blog

If you add in IBM data governance solutions, the top left will look a bit more like this: The data governance solution powered by IBM Knowledge Catalog offers several capabilities to help facilitate advanced data discovery, automated data quality and data protection.

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AI that’s ready for business starts with data that’s ready for AI

IBM Journey to AI blog

With an open data lakehouse architecture, you can now optimize your data warehouse workloads for price performance and modernize traditional data lakes with better performance and governance for AI. Effective data quality management is crucial to mitigating these risks.

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How to Build ETL Data Pipeline in ML

The MLOps Blog

From data processing to quick insights, robust pipelines are a must for any ML system. Often the Data Team, comprising Data and ML Engineers , needs to build this infrastructure, and this experience can be painful. However, efficient use of ETL pipelines in ML can help make their life much easier.

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12 AI Insight Talks to Help Improve Your Company’s AI Game at ODSC West

ODSC - Open Data Science

Delphina Demo: AI-powered Data Scientist Jeremy Hermann | Co-founder at Delphina | Delphina.Ai In this demo, you’ll see how Delphina’s AI-powered “junior” data scientist can transform the data science workflow, automating labor-intensive tasks like data discovery, transformation, and model building.

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3 Takeaways from Gartner’s 2018 Data and Analytics Summit

DataRobot Blog

In Rita Sallam’s July 27 research, Augmented Analytics , she writes that “the rise of self-service visual-bases data discovery stimulated the first wave of transition from centrally provisioned traditional BI to decentralized data discovery.” 2) Line of business is taking a more active role in data projects.

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Google experts on practical paths to data-centricity in applied AI

Snorkel AI

Abhishek Ratna, in AI ML marketing, and TensorFlow developer engineer Robert Crowe, both from Google, spoke as part of a panel entitled “Practical Paths to Data-Centricity in Applied AI” at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Is more data always better?