Data Enginerring - Gustavo Gama

Gustavo Gama

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Data Enginerring

A collection of 12 posts

Diagram showing "THE CONCEPTUAL MODELING RENAISSANCE" comparing metadata chaos to SCOPE Framework's organized AI approach.

Data Architecture

The Conceptual Modeling Renaissance: Why the SCOPE Framework Was Already Ahead of the Curve

The SCOPE framework anticipated AI's "context problem" by establishing data hierarchy and semantic authority to help the facing these challenges. While others rush to solve AI's semantic chaos, SCOPE already provided the organizational foundations needed for effective context engineering.

Where Data at Rest Meets Data in Motion: Bridging historical insights and real-time updates for innovative data strategies

Data Architecture

Where Data at Rest Meets Data in Motion

Explore how historical data (at rest) and real-time updates (data in motion) merge in a modern pipeline. Technologies like Kafka, ByteWax, Flink and Faust process data seamlessly, transforming raw JSON into actionable insights on real-time dashboards.

The Battle for Truth - Bonus Part - The Way Forward: Building an Enterprise That Trusts Its Own Data

Data Architecture

The Battle for Truth - Bonus Part - The Way Forward: Building an Enterprise That Trusts Its Own Data

A strategic guide for technology and data leaders navigating the complexity of modern data ecosystems and data in enterprise.

The Battle for Truth - Part 5 - The Decision Deadlock: When Everyone Owns the Data and Nobody Does.

Data Architecture

The Battle for Truth - Part 5 - The Decision Deadlock: When Everyone Owns the Data and Nobody Does.

A strategic guide for technology and data leaders navigating the complexity of modern data ecosystems and data in enterprise.

The Battle for Truth - Part 4 - The Implementation Gap: When technical complexity meets organizational reality

Data Architecture

The Battle for Truth - Part 4 - The Implementation Gap: When technical complexity meets organizational reality

A strategic guide for technology and data leaders navigating the complexity of modern data ecosystems and data in enterprise.

The Battle for Truth - Part 3 - The Scope Trap: Why unclear requirements kill data projects before they start

Data Architecture

The Battle for Truth - Part 3 - The Scope Trap: Why unclear requirements kill data projects before they start

A strategic guide for technology and data leaders navigating the complexity of modern data ecosystems and data in enterprise.

The Battle for Truth - Part 2 - The Integration Nightmare: When Your Data Sources Fight Each Other

Data Architecture

The Battle for Truth - Part 2 - The Integration Nightmare: When Your Data Sources Fight Each Other

A strategic guide for technology and data leaders navigating the complexity of modern data ecosystems and data in enterprise.

The Battle for Truth - Part 1: The Master Data Maze: Why Multiple Sources Create More Confusion Than Clarity

The Battle for Truth - Part 1: The Master Data Maze: Why Multiple Sources Create More Confusion Than Clarity

A strategic guide for technology and data leaders navigating the complexity of modern data ecosystems and data in enterprise.

The Invisible War at the Data Domains Realm

Data Architecture

The Invisible War at the Data Domains Realm

Why Your Organization's Greatest Asset is Tearing Teams Apart

Turning Data Challenges into Wins

Turning Data Challenges into Wins

Discover one way to transforms fragmented data management into a structured and effective governance strategy

Rethinking Data Domains

Data Enginerring

Rethinking Data Domains

adding the Transaction Level

Why does Data Integration Require so Many Tools?

Data Architecture

Why does Data Integration Require so Many Tools?

Data integration can be intricate. It combines, transforms, and harmonizes data from various sources to create a unified and meaningful format.