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This concise yet comprehensive guide explains how to adopt a data lakehouse architecture to implement modern data platforms. It reviews the design considerations, challenges, and best practices for implementing a lakehouse and provides key insights into the ways that using a lakehouse can impact your data platform, from managing structured and unstructured data and supporting BI and AI/ML use cases to enabling more rigorous data governance and security measures.
Practical Lakehouse Architecture shows you how to:
- • Understand key lakehouse concepts and features like transaction support, time travel, and schema evolution • Understand the differences between traditional and lakehouse data architectures • Differentiate between various file formats and table formats • Design lakehouse architecture layers for storage, compute, metadata management, and data consumption • Implement data governance and data security within the platform • Evaluate technologies and decide on the best technology stack to implement the lakehouse for your use case • Make critical design decisions and address practical challenges to build a future-ready data platform • Start your lakehouse implementation journey and migrate data from existing systems to the lakehouse
This concise yet comprehensive guide explains how to adopt a data lakehouse architecture to implement modern data platforms. It reviews the design considerations, challenges, and best practices for implementing a lakehouse and provides key insights into the ways that using a lakehouse can impact your data platform, from managing structured and unstructured data and supporting BI and AI/ML use cases to enabling more rigorous data governance and security measures.
Practical Lakehouse Architecture shows you how to:
- • Understand key lakehouse concepts and features like transaction support, time travel, and schema evolution • Understand the differences between traditional and lakehouse data architectures • Differentiate between various file formats and table formats • Design lakehouse architecture layers for storage, compute, metadata management, and data consumption • Implement data governance and data security within the platform • Evaluate technologies and decide on the best technology stack to implement the lakehouse for your use case • Make critical design decisions and address practical challenges to build a future-ready data platform • Start your lakehouse implementation journey and migrate data from existing systems to the lakehouse
| Erscheinungsjahr: | 2024 |
|---|---|
| Genre: | Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| ISBN-13: | 9781098153014 |
| ISBN-10: | 1098153014 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Thalpati, Gaurav |
| Hersteller: | O'Reilly Media |
| Maße: | 230 x 176 x 16 mm |
| Von/Mit: | Gaurav Thalpati |
| Erscheinungsdatum: | 31.08.2024 |
| Gewicht: | 0,512 kg |
| Erscheinungsjahr: | 2024 |
|---|---|
| Genre: | Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| ISBN-13: | 9781098153014 |
| ISBN-10: | 1098153014 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Thalpati, Gaurav |
| Hersteller: | O'Reilly Media |
| Maße: | 230 x 176 x 16 mm |
| Von/Mit: | Gaurav Thalpati |
| Erscheinungsdatum: | 31.08.2024 |
| Gewicht: | 0,512 kg |
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