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Building Data Products Introduction to Data and Analytics Engineering for Non-Programmers
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This book balances technical demonstrations with business management strategies to focus on delivering the highest business value sustainably.
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Produkto Aprašymas
| Publisher | Brian McMillan |
| Publication date | August 2, 2021 |
| Language | English |
| Print length | 449 pages |
| ISBN-10 | 1737536536 |
| ISBN-13 | 978-1737536536 |
| Item Weight | 1.92 pounds (870 grams) |
| Dimensions | 7.5 x 1.06 x 9.25 inches (19.1 x 2.7 x 23.5 cm) |
Who Should Buy?
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Business Professionals
Ideal for those looking to understand data analytics to drive business decisions without technical coding skills.
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Marketing Specialists
Great for marketers who want to leverage data insights to optimize campaigns without deep technical knowledge.
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Students in Analytics
Perfect for students seeking a foundational understanding of data engineering concepts without prior programming experience.
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Experienced Programmers
Not suitable for seasoned developers who require advanced analytics techniques beyond beginner-level content.
PRODUKTO APRAŠYMAS
Building Data Products Introduction to Data and Analytics Engineering for Non-Programmers
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Production & Operations Editorial Review
Building Data Products is an excellent resource for non-programmers who want to learn about data and analytics engineering. The book provides a comprehensive introduction to the field, covering topics such as data collection, data storage, data analysis, and data visualization. The author does a great job explaining technical concepts in a clear and accessible way, making it easy for readers to grasp the material. The book includes practical examples and case studies, allowing readers to apply what they've learned to real-world scenarios. Overall, Building Data Products is a must-read for anyone interested in data and analytics engineering.
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Argumentai
- Comprehensive introduction to data and analytics engineering
- Clear and accessible explanations of technical concepts
- Includes practical examples and case studies
- Helps readers apply learning to real-world scenarios
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Savybės ir privalumai
- Designed for non-programmers to understand data and analytics engineering.
- Covers technical skills and software development philosophy.
- Helps managers handle business change and competition effectively.
- Equips analysts with strategies to enhance productivity and focus.
- Provides seasoned engineers with teaching tools for the product lifecycle.
- Focuses on agile principles and modern DevOps practices for better data management.
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