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Analyst View: DataGalaxy Data Catalog 360

BI-Survey

The company DataGalaxy was founded in 2015 in Lyon, France, by Lazhar Sellami and Sébastien Thomas. It is mainly used for data cataloging, data governance, compliance & regulatory use cases or as a metadata hub. Metadata can be extracted from any source and made available. Openness and extensibility are fundamental to this.

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10 Years Later: Who’s the GOAT of Data Catalogs?

Alation

January 2015: Alation acquires its first customer. March 2015: Alation emerges from stealth mode to launch the first official data catalog to empower people in enterprises to easily find, understand, govern and use data for informed decision making that supports the business. June 2017: Yahoo Japan Corp.

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Operationalizing responsible AI principles for defense

IBM Big Data Hub

Providing interpretable AI model metadata (for example, as factsheets ) specifying accountable persons, performance benchmarks (compared to human), data and methods used, audit records (date and by whom), and audit purpose and results. Capture key metadata to render AI models transparent and keep track of model inventory.

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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. One of the longer-term trends that we’re seeing with Airflow , and so on, is to externalize graph-based metadata and leverage it beyond the lifecycle of a single SQL query, making our workflows smarter and more robust. BTW, videos for Rev2 are up: [link].

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NEW: Octopai Announces Support of Microsoft Azure Data Factory

Octopai

Octopai can fully map the BI landscape and trace metadata movement in a mixed environment including complex multi-vendor landscapes. About Octopai: Octopai was founded in 2015 by BI professionals who realized the need for dynamic solutions in a stagnant market.

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Gartner D&A Summit Bake-Offs Explored Flooding Impact And Reasons for Optimism!

Rita Sallam

The first featured analytics and BI platform Gartner Magic Quadrant leaders while the other showcased high interest data science and machine learning platforms. Here is the link to Alteryx’s Data Science and Machine Learning Bake-Off video. We did two Bake-Offs this year. In 2000, the Netherlands had 8.5

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How Amazon Devices scaled and optimized real-time demand and supply forecasts using serverless analytics

AWS Big Data

Furthermore, it created further opportunities for our data scientists and engineers to use AI and machine learning (ML) services to continuously feed and analyze data. We used the same AWS Glue jobs to further transform and load the data into the required S3 bucket and a portion of extracted metadata into DynamoDB.