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The data flow map = a practical guide to clear and creative analytics in any data environment /

Record Type:	Electronic resources : Monograph/item
Title/Author:	The data flow map/ by Nick Ryberg.
Reminder of title:	a practical guide to clear and creative analytics in any data environment /
Author:	Ryberg, Nick.
Published:	Berkeley, CA :Apress : : 2025.,
Description:	xix, 204 p. :ill. (chiefly col.), digital ;24 cm.
[NT 15003449]:	Chapter 1: Introduction -- Chapter 2: Framework Overview -- Chapter 3: Data Flow Map Deep Dive -- Chapter 4: Examples - Files -- Chapter 5: Examples - Databases -- Chapter 6: Examples - Python -- Chapter 7: Examples - APIs -- Chapter 8: Platforms -- Chapter 9: Pipelines -- Chapter 10: Analog Side of Analytics -- Appendix A: Sample Data Sourcing.
Contained By:	Springer Nature eBook
Subject:	Data flow computing. -
Online resource:	https://doi.org/10.1007/979-8-8688-1883-7
ISBN:	9798868818837

The data flow map = a practical guide to clear and creative analytics in any data environment /
Ryberg, Nick.

The data flow mapa practical guide to clear and creative analytics in any data environment /[electronic resource] :by Nick Ryberg. - Berkeley, CA :Apress :2025. - xix, 204 p. :ill. (chiefly col.), digital ;24 cm. - Apress pocket guides,3004-9288. - Apress pocket guides..

Chapter 1: Introduction -- Chapter 2: Framework Overview -- Chapter 3: Data Flow Map Deep Dive -- Chapter 4: Examples - Files -- Chapter 5: Examples - Databases -- Chapter 6: Examples - Python -- Chapter 7: Examples - APIs -- Chapter 8: Platforms -- Chapter 9: Pipelines -- Chapter 10: Analog Side of Analytics -- Appendix A: Sample Data Sourcing.

Unlock the secrets of practical data analysis with the Data Flow Map framework-a game-changing approach that transcends tools and platforms. This book isn't just another programming manual; it's a guide to thinking and communicating about data at a higher level. Whether you're working with spreadsheets, databases, or AI-driven models, you'll learn how to express your analytics in clear, common language that anyone can understand. In today's data-rich world, clarity is the real challenge. Technical details often obscure insights that could drive real impact. The Data Flow Map framework simplifies complexity into three core motions: source, focus, and build. The first half of the book explores these concepts through illustrations and stories. The second half applies them to real-world datasets using tools like Excel, SQL, and Python, demonstrating how this approach adapts seamlessly across platforms and use cases. A vital resource for analysts at any level, this book offers a practical, tool-agnostic approach to data analysis. With hands-on examples and a universal mental model, you'll gain the confidence to tackle any dataset, align your team, and deliver insights that matter. Whether you're a beginner or a seasoned pro, the Data Flow Map framework will transform how you approach data analytics. What You Will Learn Grasp essential elements applicable to every data analysis workflow Adapt quickly to any dataset, tool, or platform Master analytic thinking at a higher level Use analytics patterns to better understand the world Break complex analysis into manageable, repeatable steps Iterate faster to uncover deeper insights and better solutions Communicate findings clearly for better decision-making.

ISBN: 9798868818837

Standard No.: 10.1007/979-8-8688-1883-7doiSubjects--Topical Terms:

1005622
Data flow computing.

LC Class. No.: QA76.9.D338

Dewey Class. No.: 005.73

The data flow map = a practical guide to clear and creative analytics in any data environment /
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300 $a xix, 204 p. : $b ill. (chiefly col.), digital ; $c 24 cm.
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505 0 $a Chapter 1: Introduction -- Chapter 2: Framework Overview -- Chapter 3: Data Flow Map Deep Dive -- Chapter 4: Examples - Files -- Chapter 5: Examples - Databases -- Chapter 6: Examples - Python -- Chapter 7: Examples - APIs -- Chapter 8: Platforms -- Chapter 9: Pipelines -- Chapter 10: Analog Side of Analytics -- Appendix A: Sample Data Sourcing.
520 $a Unlock the secrets of practical data analysis with the Data Flow Map framework-a game-changing approach that transcends tools and platforms. This book isn't just another programming manual; it's a guide to thinking and communicating about data at a higher level. Whether you're working with spreadsheets, databases, or AI-driven models, you'll learn how to express your analytics in clear, common language that anyone can understand. In today's data-rich world, clarity is the real challenge. Technical details often obscure insights that could drive real impact. The Data Flow Map framework simplifies complexity into three core motions: source, focus, and build. The first half of the book explores these concepts through illustrations and stories. The second half applies them to real-world datasets using tools like Excel, SQL, and Python, demonstrating how this approach adapts seamlessly across platforms and use cases. A vital resource for analysts at any level, this book offers a practical, tool-agnostic approach to data analysis. With hands-on examples and a universal mental model, you'll gain the confidence to tackle any dataset, align your team, and deliver insights that matter. Whether you're a beginner or a seasoned pro, the Data Flow Map framework will transform how you approach data analytics. What You Will Learn Grasp essential elements applicable to every data analysis workflow Adapt quickly to any dataset, tool, or platform Master analytic thinking at a higher level Use analytics patterns to better understand the world Break complex analysis into manageable, repeatable steps Iterate faster to uncover deeper insights and better solutions Communicate findings clearly for better decision-making.
650 0 $a Data flow computing. $3 1005622
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856 4 0 $u https://doi.org/10.1007/979-8-8688-1883-7
950 $a Professional and Applied Computing (SpringerNature-12059)