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- Data Pipelines Pocket Reference: Moving and P...
Data Pipelines Pocket Reference: Moving and Processing Data for Analytics
88% من المشترين سيوصون بهذا المنتج لصديق
IQD 34378
تفاصيل السعر
باستثناء رسوم الشحن والجمارك ( سيتم احتساب رسوم الشحن والجمارك عند إتمام الشراء )
*سيتم استيراد جميع العناصر من أمريكا
كمية:
تعمل يوباي جاهدة لحماية أمنك وخصوصيتك. يضمن نظام أمان الدفع المتقدم لدينا السرية من خلال تشفير معلوماتك أثناء النقل باستخدام بروتوكولات AES (معايير التشفير المتقدمة) وSSL (طبقة المنافذ الآمنة). تفاصيل الدفع الخاصة بك آمنة بنسبة %100 لأننا لا نشارك تفاصيل الدفع الخاصة بك مع بائعين تابعين لجهات خارجية
Data pipelines are the foundation for success in data analytics.
شحن
سريع
استرجاع
مجاني*
تغليف آمن
منتجات أصلية %100
الامتثال لمعيار PCI DSS
حاصل على شهادة ISO 27001
أبرز ما يلفت الانتباه
تفاصيل المنتج
- Defines data pipelines and explains how they work in the modern data stack
- Discusses common considerations and key decision points when implementing pipelines
- Covers batch and streaming data ingestion options and build versus buy decisions
- Addresses common tools and products used by data engineers to build pipelines
- Explains how pipelines support analytics and reporting needs
- Provides considerations for pipeline maintenance, testing, and alerting
| Publisher | O'Reilly Media |
| Publication date | March 16, 2021 |
| Edition | 1st |
| Language | English |
| Print length | 274 pages |
| ISBN-10 | 1492087831 |
| ISBN-13 | 978-1492087830 |
| Item Weight | 2.31 pounds (1.05 kg) |
| Dimensions | 4 x 0.75 x 7 inches (10.2 x 1.9 x 17.8 cm) |
من يجب أن يشتري؟
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Data Engineers
Ideal for data engineers who need concise guidance on building and managing efficient data pipelines for analytics.
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Data Scientists
Useful for data scientists who require practical strategies for data processing to enhance their analytical models.
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Students in Tech
A great resource for students studying data analytics or data engineering, providing foundational knowledge in a compact format.
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Beginners in Data
Not suitable for absolute beginners without prior knowledge of data pipelines, as it lacks detailed introductory material.
وصف المنتج
Data Pipelines Pocket Reference: Moving and Processing Data for Analytics
أسئلة العملاء & الإجابات
-
سؤال:
What is the main focus of the *Data Pipelines Pocket Reference*?
إجابه: The *Data Pipelines Pocket Reference* primarily focuses on best practices for designing and implementing data pipelines for analytics. It covers essential techniques for moving and processing data efficiently, helping data engineers and analysts understand how to manage data flows, integrate various data sources, and utilize appropriate tools for analytics. This makes it a practical guide for professionals looking to enhance their skills in data processing and ensure high-quality data availability for analytics. -
سؤال:
Who is the target audience for this book?
إجابه: This book is targeted towards data engineers, data scientists, and IT professionals who are involved in the field of data analytics. With its concise format, it is ideal for those who need quick access to key concepts and practical tips while working with data pipelines. By leveraging this reference, readers can quickly navigate complex processes associated with data movement and processing, enabling them to tackle challenges in real-time data flow and analysis. -
سؤال:
What essential concepts about data pipelines are covered?
إجابه: The book covers essential concepts such as data ingestion, transformation, loading, and monitoring of data pipelines. It delves into various architectures and frameworks that assist in optimizing data flow for analytics. Understanding these concepts is crucial for anyone handling large volumes of data. By mastering these principles, readers can efficiently build robust data pipelines that ensure clean, accurate, and timely data for business intelligence and reporting needs. -
سؤال:
Can this book help beginners in data analytics?
إجابه: Yes, the *Data Pipelines Pocket Reference* is designed to be accessible for beginners in data analytics as well as seasoned professionals. It breaks down complex topics into manageable sections, making it easier for newcomers to grasp the fundamentals of data pipelines. With practical examples and straightforward explanations, beginners can gain a solid grounding in data processing techniques, allowing them to engage in real-world projects with confidence. -
سؤال:
What tools and technologies are discussed in the book?
إجابه: The book discusses a variety of tools and technologies beneficial for building data pipelines, including Apache Kafka, Apache Airflow, and cloud services like AWS and Google Cloud. Each tool's specific use cases and advantages are highlighted, providing readers with insights into which technologies best fit their data processing needs. By familiarizing themselves with these tools, professionals can optimize their data workflows to improve efficiency and scalability. -
سؤال:
How can this book be integrated into existing projects?
إجابه: Readers can integrate the *Data Pipelines Pocket Reference* into their existing projects by using it as a practical guide while designing or optimizing their data workflows. Professionals can refer to the book’s case studies and examples that relate to real-life scenarios they may encounter. This hands-on approach allows them to apply theoretical concepts directly to their projects, enhancing their effectiveness in managing data for analytics. -
سؤال:
What are the benefits of using this pocket reference?
إجابه: The primary benefit of the *Data Pipelines Pocket Reference* is its concise and focused approach to data pipeline management. It serves as a quick and handy guide, providing essential information without overwhelming details. Users can access key topics on-the-go, making it ideal for busy professionals. This allows for efficient learning and reference, ultimately enhancing productivity while dealing with data-related tasks. -
سؤال:
Does the book contain real-world examples?
إجابه: Yes, the book includes real-world examples that illustrate the application of data pipeline principles in various industries. These case studies help readers understand how organizations handle data movement and analytics challenges. By exploring practical scenarios, readers can better relate theoretical knowledge to their own situations, making it easier to visualize effective data pipeline strategies in action. -
سؤال:
Is this book suitable for advanced data professionals?
إجابه: Absolutely, while the *Data Pipelines Pocket Reference* is beginner-friendly, it also offers advanced insights that can benefit experienced data professionals. It covers complex topics and emerging trends in data processing, encouraging seasoned individuals to expand their knowledge and refine their skills. By engaging with the book, advanced users can stay updated with current practices and enhance their existing expertise in data pipeline architecture and management. -
سؤال:
Where can I buy *Data Pipelines Pocket Reference: Moving and Processing Data for Analytics 1st Edition* in Iraq?
إجابه: You can buy the *Data Pipelines Pocket Reference: Moving and Processing Data for Analytics 1st Edition* on Ubuy in Iraq. Ubuy offers a reliable platform to purchase various books, ensuring you can easily find this valuable resource for enhancing your data analytics skills.
Data Modeling & Design Editorial Review
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IQD 34378
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كمية:
نوفر لك مدفوعات مشفّرة، وحماية متكاملة للمشتري، مع الالتزام بمعايير PCI DSS وشهادة ISO 27001:2022 لضمان أعلى مستويات الأمان في كل عملية شراء.
المميزات والفوائد
- Define data pipelines and their importance in modern data stack.
- Explore the common considerations and key decision points when implementing pipelines.
- Learn about the common tools and products used by data engineers to build pipelines.
- Understand how pipelines support analytics and reporting needs.
- Address the considerations for pipeline maintenance, testing, and alerting.
ضمان Ubuy
تسوّق بثقة مع منتجات أصلية %100، ومدفوعات آمنة متوافقة مع معيار PCI DSS، وحماية بيانات معتمدة وفق ISO 27001، وشحن دولي سريع، وإرجاع مجاني*، وتغليف آمن لكل طلب.