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Nº de artículo:
40417305
Distributed Data Systems with Azure Databricks: Create, deploy, and manage enterprise data pipelines
80% of respondents would recommend this to a friend
Nº de artículo:
40417305
PEN 264
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What Stands Out
Enterprise Integration
Seamlessly integrates with Azure services, making it easier to build, deploy, and manage robust data pipelines tailored for enterprise-level applications.
Scalable Architecture
Offers a highly scalable cloud-based architecture that supports big data workloads, allowing businesses to efficiently process large datasets without performance issues.
Simplified Management
Provides user-friendly tools and dashboards for monitoring and managing data pipelines, reducing operational complexity and enhancing decision-making capabilities.
Detalles de producto
| Publisher | Packt Publishing |
| Publication date | May 25, 2021 |
| Language | English |
| Print length | 414 pages |
| ISBN-10 | 183864721X |
| ISBN-13 | 978-1838647216 |
| Item Weight | 1.56 pounds (710 grams) |
| Dimensions | 7.5 x 0.94 x 9.25 inches (19.1 x 2.4 x 23.5 cm) |
Who Should Buy?
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Data Engineers
Ideal for data engineers seeking to create and manage scalable data pipelines using Azure Databricks efficiently.
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Data Analysts
Helpful for data analysts who need powerful tools for data transformation and insights generation through collaborative notebooks.
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Cloud Architects
Beneficial for cloud architects designing distributed data systems in Azure, taking advantage of Databricks’ integrated analytics services.
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Beginner Users
Not suitable for beginners unfamiliar with data engineering concepts or cloud technologies, as it may overwhelm them.
DESCRIPCIÓN DEL PRODUCTO
Distributed Data Systems with Azure Databricks: Create, deploy, and manage enterprise data pipelines
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Data Warehousing Editorial Review
Distributed Data Systems with Azure Databricks: Create, deploy, and manage enterprise data pipelines provides a comprehensive guide for those seeking to learn about Azure Databricks and its functionalities. With its 414 pages, the book covers essential topics such as setting up an Azure workspace, ETL operations, and machine learning integration. Readers have noted that the hands-on approach, especially with practical examples, allows for a better grasp of the material. However, some critics find the content outdated due to UI changes in Azure and changes in public datasets. This book remains a useful resource for beginners aiming to delve into data engineering with Azure Databricks.
Customer Reviews & Ratings
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ventajas
- Provides detailed explanations on core Databricks functionalities
- Hands-on examples enhance practical understanding of technology
- Covers both machine learning and data streaming effectively
- The author's ambitious approach encourages experimentation
- Suitable for beginners with minimal knowledge in data engineering
Contras
- Some content may feel outdated compared to current tutorials
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31 October 2026 · via Trustpilot
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