Data Structure Synthesis
Data Structure Synthesis: Boosting Productivity Through Data Structure Reuse, by Doug Needham
Know the math that underpins everything we do in data.
Topics
Foreword by Dan Linstedt
Introduction
Chapter 1: My Journey Here
Why should anyone listen to me?
Early life
The Marine Corps
Professional life
The mathematical epiphany
Data modeling
Application
Integration
Presentation
Our journey
Chapter 2: Troubleshooting
Keep a record
Rule of three
Chapter 3: Synthesis
Chapter 4: Set Theory
Chapter 5: Logic
Implicational and conditional logic
Propositional logic
First order predicate logic
Chapter 6: Functions
Chapter 7: Relational Theory
Overview of the relational model
Relational algebra theory
Relational calculus theory
Difference between relational algebra and calculus
Chapter 8: SQL
TABLE
DDL
CREATE
ALTER
DROP
TRUNCATE
COMMENT
CLONE
DML
SELECT
INSERT
UPDATE
DELETE
MERGE
DCL
TCL
Query mechanics
SQL parser
CASE statements and aggregation
Key points
Relational algebra theory
Relational calculus theory
Relational algebra and calculus key takeaways
Clauses and functions
Structured and semi-structured data
Ingestion
XML
JSON
Chapter 9: SQL in Set Builder Notation
Chapter 10: Graph Theory
Chapter 11: Data Model
Schema
Design
Volumetrics
Operations
Chapter 12: Category Theory
Chapter 13: ETL and ELT
Chapter 14: Metric Spaces
Chapter 15: Data Vault
Hub
Probability
Link
Calculus
Satellite
Information theory/entropy
Chapter 16: Dimensional Data Model
Combinatorics
The Fundamental Counting Principle
Permutations
Combinations
Other important concepts
Chapter 17: Economics
Scarcity and choices
The demand curve
The supply curve
Equilibrium
Shifts in supply and demand
Chapter 18: Database Design Revisited
Chapter 19: Anthropology
With storytelling and lots of examples, Doug “The Data Guy” Needham explains the math that creates the foundation for efficient databases, flexible data interchange formats, and robust applications. Data modeling, SQL, and relational database design are covered in detail using global standards as well as many examples in Snowflake. Also covered are dimensional modeling, JSON, XML, data vault, and graph databases.
The math you will learn and be able to apply includes set theory, logic (implicational, conditional, prepositional, and first order predicate), functions, relational algebra and calculus, graph theory, and combinatorics.
There is foundational knowledge required to excel in any discipline. Accountants must know double-entry bookkeeping, doctors must know basic human anatomy, car mechanics must know engine mechanics, and data professionals must know the math behind their profession. This book provides the fundamental knowledge needed to appreciate and excel in data management.
You do not need to be a mathematician (or even like math!) to master the formulas and techniques within these pages that will prepare you for building robust data structures and queries within Agile timeframes.
About Doug
Doug “The Data Guy” Needham started his career as a Marine Database Administrator supporting operational systems that spanned the globe in support of the Marine Corps missions. Since then, Doug has worked as a consultant, data engineer, and data architect for enterprises of all sizes. He is currently working as a Data Scientist, tinkering with Graphs and Enrichment Platforms while showing others how to get more meaning from data. He always focuses on the Data Operations side of ensuring data moves throughout the Enterprise in the most efficient manner.
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