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Data Modeling with Snowflake

Data Modeling with Snowflake - Second Edition

By : Serge Gershkovich
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Data Modeling with Snowflake

Data Modeling with Snowflake

By: Serge Gershkovich

Overview of this book

Struggling with rising Snowflake costs and constant tuning? Poorly aligned data models can lead to bloated expenses, inefficient queries, and time-consuming rework. Data Modeling with Snowflake helps you harness the Snowflake Data Cloud’s scalable, cloud-native architecture and expansive feature set to deliver data solutions faster than ever. This book introduces simple, practical data modeling frameworks that accelerate agile design and evolve alongside your projects from concept to code. Rooted in decades of proven database design principles, these frameworks are paired, for the first time, with Snowflake-native objects and real-world examples, offering a two-in-one crash course in theory and direct application. Through real-world examples designed to make learning easy, you’ll leverage Snowflake’s innovative features like Time Travel, Zero-Copy Cloning, and Change Data Capture (CDC) to create cost-efficient solutions. Whether you're just starting out or refining your architecture, this book will guide you in designing smarter, scaling faster, and cutting costs by aligning timeless modeling principles with the power of Snowflake. *Email sign-up and proof of purchase required
Table of Contents (27 chapters)
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Lock Free Chapter
1
Part 1: Core Concepts in Data Modeling and Snowflake Architecture
9
Part 2: Applied Modeling from Idea to Deployment
15
Part 3: Solving Real-World Problems with Transformational Modeling
21
Part 4: Data Modeling for Enterprise Teams
23
Unlocking Value for Enterprise Organizations
24
Other Books You May Enjoy
25
Index
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Index

A

ACID properties 107

alternate key (AK) 227

using, as unique constraints 94

American National Standards Institute (ANSI) 7, 169

Apache Iceberg Open Table Format (OTF) 106

artificial intelligence (AI) 372

associative 173

Atomic Consistent Isolated Durable (ACID) 106

atomic grain 156

attributes 25

adding 169, 170

attributes, as columns 84, 94

semi-structured data, storing 85, 86

Snowflake data types 84, 85

automatic clustering 83

Avro 60

B

big data

value 367

variety 367

velocity 367

veracity 367

volume 367

BI tools

functionality, automating 100

Boyce-Codd Normal Form (BCNF) 188, 192, 193

bridge table 341, 352

Business as Usual (BAU) 379

Business Event Analysis and Modeling (BEAM) 152

business process, engaging 152, 153

business intelligence (BI) 35, 100, 213, 378

business key 91

Business Vault 352

bus matrix 155

C

capital expenditure...

CONTINUE READING
83
Tech Concepts
36
Programming languages
73
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Data Modeling with Snowflake
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