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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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Amazon AI Introduces DataLore: A Machine Learning Framework that Explains Data Changes between an Initial Dataset and Its Augmented Version to Improve Traceability

Marktechpost

Data scientists and engineers frequently collaborate on machine learning ML tasks, making incremental improvements, iteratively refining ML pipelines, and checking the model’s generalizability and robustness. This facilitates a series of data transformations and enhances the effectiveness of the proposed LLM-based system.

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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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Attivio Accelerates Business Intelligence and Big Data Projects with New Data Source Discovery Software

Attivio

June 8, 2015: Attivio ( www.attivio.com ), the Data Dexterity Company, today announced Attivio 5, the next generation of its software platform. And anecdotal evidence supports a similar 80% effort within data integration just to identify and profile data sources.” [1] Newton, Mass.,

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How to Build ETL Data Pipeline in ML

The MLOps Blog

ETL pipeline | Source: Author These activities involve extracting data from one system, transforming it, and then processing it into another target system where it can be stored and managed. ML heavily relies on ETL pipelines as the accuracy and effectiveness of a model are directly impacted by the quality of the training data.

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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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Augmented Analytics?—?Where Do You Fit in at the Intersection of Analytics and Business…

ODSC - Open Data Science

Data visualization is a critical way for anyone to turn endless rows of data into easy-to-understand results through dynamic and understandable visuals. And with augmented analytics (and embedded insights), anyone can become a citizen data scientist, regardless of their advanced analytics expertise.