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Delta Lake でのスキーマ（schema）DB の適用・展開とは
データブリックスの Notebook シリーズを試す データは常に進化し、蓄積されていきます。私たち人間の日々の経験と似ているかもしれません。私たちは、自身の周りの世界の変化についていくために、常に新しいデータを取り込み、認識し、ときにはその中から新たな概念や解釈を得ます。このような認識モデルは、まさにテーブルのスキーマそのものです。どちらも、新しく得る情報の分類と処理のしかたを決める役割を持っています。 データベースにおけるスキーマとは ：そもそも「スキーマ（schema）」とは、日本人にとっても馴染みのある「スキーム（scheme）」という言葉の派生語です。計画や図などの意味を持ち、データベース関連だけでなく、哲学や心理学で使われている言葉でもあります。この記事で説明するデータベーススキーマ（DBスキーマ）とは、簡単に言えばデータベースの構造や整理の仕方のことです。細かな定義は、データ
Best Practices to Secure Data Lake on AWS (ANT327) - AWS re:Invent 2018
Best Practices to Secure Data Lake on AWS (ANT327) - AWS re:Invent 2018 As customers are looking to build Data lakes to AWS, managing security, catalog and data quality becomes a challenge. Once data is put on Amazon S3, there are multiple processing engines to access it. This could be either through a SQL interface, programmatic, or using API. Customers require federated access to their data with
How Amazon is solving big-data challenges with data lakes
How Amazon is solving big-data challenges with data lakesJanuary 20, 2020 • 2157 words Back when Jeff Bezos filled orders in his garage and drove packages to the post office himself, crunching the numbers on costs, tracking inventory, and forecasting future demand was relatively simple. Fast-forward 25 years, Amazon's retail business has more than 175 fulfillment centers (FC) worldwide with over 2
Abstract
Data Lake Management: Challenges and Opportunities Tuesday, August 27, 11:00 – 12:30 -- VLDB 2019, Los Angeles, California Abstract The ubiquity of data lakes has created fascinating new challenges for data management research. In this tutorial, we review the state-of-the-art in data management for data lakes. We consider how data lakes are introducing new problems including dataset discovery and
How to Move Beyond a Monolithic Data Lake to a Distributed Data Mesh
How to Move Beyond a Monolithic Data Lake to a Distributed Data Mesh Many enterprises are investing in their next generation data lake, with the hope of democratizing data at scale to provide business insights and ultimately make automated intelligent decisions. Data platforms based on the data lake architecture have common failure modes that lead to unfulfilled promises at scale. To address these
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https://dl.acm.org/doi/10.1145/3318464.3380605
Data Market Platforms: Trading Data Assets to Solve Data Problems
https://dl.acm.org/doi/10.1145/3318464.3389726
GitHub - RJMillerLab/data-lake-tutorial-slides: Data Lake Management: Challenges and Opportunities, VLDB 2019
Scorecard of a Data Platform for Analytics & ML
AWS Lake Formation
https://jp.techcrunch.com/2020/02/25/2020-02-24-databricks-makes-bringing-data-into-its-lakehouse-easier/
GitHub - mozilla-services/mozilla-pipeline-schemas: Schemas for Mozilla's data ingestion pipeline and data lake outputs
Building a Data Streaming Platform — How Zillow Sends Data to its Data Lake
http://www.vldb.org/pvldb/vol10/p1853-maccioni.pdf
Productionizing Machine Learning with Delta Lake
http://www.cs.toronto.edu/~ekzhu/papers/josie.pdf
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