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Orchestrate an end-to-end ETL pipeline using Amazon S3, AWS Glue, and Amazon Redshift Serverless with Amazon MWAA

AWS Big Data

This approach allows the team to process the raw data extracted from Account A to Account B, which is dedicated for data handling tasks. This makes sure the raw and processed data can be maintained securely separated across multiple accounts, if required, for enhanced data governance and security.

Metadata 100
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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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Why We Started the Data Intelligence Project

Alation

In 2013 I joined American Family Insurance as a metadata analyst. I had always been fascinated by how people find, organize, and access information, so a metadata management role after school was a natural choice. The use cases for metadata are boundless, offering opportunities for innovation in every sector. The data scientist.

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Themes and Conferences per Pacoid, Episode 12

Domino Data Lab

In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. First and foremost: there’s substantial overlap between what the scientific community is working toward for scholarly infrastructure and some of the current needs of data governance in industry. We did it again.”.

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Becoming a machine learning company means investing in foundational technologies

O'Reilly on Data

Use ML to unlock new data types—e.g., Consider deep learning, a specific form of machine learning that resurfaced in 2011/2012 due to record-setting models in speech and computer vision. You also need solutions that let you understand what data you have and who can access it. Metadata and artifacts needed for audits.