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In-depth guides, tutorials, and best practices for database design, data architecture, and healthcare data modeling.

Data Architecture Articles

15 articles

Showing 712 of 15 posts

Data Architecture

Redshift vs Snowflake vs BigQuery for Healthcare Claims

Choosing a cloud data warehouse for healthcare claims is not just a cost and performance decision — it is a compliance, security, and architecture decision. We break down how Redshift, Snowflake, and BigQuery compare across the dimensions that matter most for claims data.

11 min read·Apr 14
SnowflakeRedshift
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Data Architecture

Data Lake vs Delta Lake vs Data Warehouse vs Data Mart: Complete Guide

Your CTO asks: "Data lake or data warehouse?" Your architect says: "Delta Lake." Your analyst wants: "Just a data mart." Everyone''s confused. Here''s what each actually does, when to use them, and how they work together—with real costs, timelines, and healthcare examples.

15 min read·Mar 25
data lakedelta lake
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Data Architecture

Data Warehouse Design Patterns: Star vs Snowflake Schema

Compare star schema and snowflake schema designs for data warehouses with practical examples and guidance on when to use each pattern.

8 min read·Feb 24
["Data Warehouse""Design Patterns"
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Data Architecture

Database Naming Conventions: A Complete Style Guide

Establish consistent database naming conventions for tables, columns, indexes, and constraints that improve maintainability and team productivity.

10 min read·Feb 24
["Naming""Best Practices"
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Data Architecture

When Business Context Matters More Than 3NF

Third Normal Form is a technical achievement but business understanding is what makes data useful. This post explains why data models succeed or fail based on context, not normalization purity, and how enterprises should design models that reflect how the business actually thinks.

4 min read·Jan 12
["Data Architecture""Best Practices"
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Data Architecture

How Over-Normalization Destroys Reporting Performance

Normalization is foundational to relational design but taken too far, it quietly sabotages analytics. This post explains why over-normalized data models break reporting performance, frustrate analysts, and create unnecessary complexity in modern data platforms.

5 min read·Jan 12
["Data Architecture""Best Practices"
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