Remove Data Governance Remove Data Warehouse Remove Deep Learning Remove Metadata
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Of Muffins and Machine Learning Models

Cloudera

Weak model lineage can result in reduced model performance, a lack of confidence in model predictions and potentially violation of company, industry or legal regulations on how data is used. . Within the CML data service, model lineage is managed and tracked at a project level by the SDX. Machine Learning Model Visibility .

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.

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Data Science, Past & Future

Domino Data Lab

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

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The Cloud Connection: How Governance Supports Security

Alation

Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. This is why, when data moves, it’s imperative for organizations to prioritize data discovery. Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth.

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Themes and Conferences per Pacoid, Episode 11

Domino Data Lab

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Scale the problem to handle complex data structures. BTW, videos for Rev2 are up: [link].

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