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The sequence diagram is used primarily to show the interactions between objects in the sequential order that those interactions occur. Much like the class diagram, developers typically think sequence diagrams were meant exclusively for them.
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Sequence Diagram
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Python Foundation
5 MIN READ
GCP network design for healthcare application
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GCP network design for a E-Commerce Application
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What “Least-Privilege Access” Means
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Data Governance
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June 2026
[DRAFT] Data Migration Strategy
An increasing number of organizations are running their workloads on Google Cloud. However, migrating workloads from another cloud provider can be a complex undertaking. Planning, designing, and executing the migration of applications, data, and operational processes requires careful consideration, particularly when there are strict requirements such as achieving zero downtime during the transition.
SDWAN - "Secure Data Transfer"
SD-WAN (Software-Defined Wide Area Network) is a networking technology that uses software to manage and optimize traffic across a wide area network (WAN). It replaces rigid, traditional networks by acting like a smart GPS, automatically routing data across the best available connection.
March 2026
Data Governance
What is Data Governance? (A practical explanation)
Data Modeling: Kimball Approach
Mastering Data Modeling: The Ralph Kimball Approach
Microsoft Fabric terms for a Data Engineer
10 Must to know Microsoft Fabric terms for a Data Engineer:
Data Governance
Why Data Governance Matters More Than Ever - Lets understand
Star vs Snowflake vs Data Vault
Star vs Snowflake vs Data Vault – A Data Architect’s Dilemma
February 2026
SQL Exercises
Exercises involve a simplified database of e-commerce data.
What “Least-Privilege Access” Means
What “Least-Privilege Access” Means
GCP network design for healthcare application
Below is a step-by-step GCP network design tailored for a healthcare application, with security, compliance (HIPAA), reliability, and scalability baked in from the start. I’ll walk you from high-level principles down to concrete network components you’d actually deploy in Google Cloud Platform.
GCP network design for a E-Commerce Application
Alright, let’s build this like a real production e-commerce network, not a toy diagram. I’ll go step-by-step, explain why each piece exists, and call out common e-commerce gotchas along the way. I’ll assume Google Cloud Platform (GCP), multi-tier app (web → API → data), and growth in mind.
Internal Chargeback Models
Internal Chargeback Models That Change Engineering Behavior
Event-Driven Near-Real-Time Global Lakehouse
Event-Driven Near-Real-Time Global Lakehouse
Warehouse Architecture for GenAI Workloads
Warehouse Architecture for GenAI Workloads
Cost War-Room Optimization Strategy
Cost War-Room Optimization Strategy
Designing a 100PB Multi-Continent Data Platform
Designing a 100PB Multi-Continent Data Platform
Real-World Cost Breakdown of a $10M/Year Warehouse
Real-World Cost Breakdown of a $10M/Year Warehouse
Designing a Global Analytics Control Plane
Designing a Global Analytics Control Plane
Hybrid BigQuery + Spark Architecture
Hybrid BigQuery + Spark Architecture
Multi-Cloud Analytics Strategy
Multi-Cloud Analytics Strategy
Designing 50PB+ Lakehouse Patterns
Designing 50PB+ Lakehouse Patterns
Designing BigQuery for AI/ML Feature Stores
Designing BigQuery for AI/ML Feature Stores
BQ Query Rewrite Strategies
Query Rewrite Strategies Used by Top Tech Companies
BQ Real Slot Pricing Optimization Math
Real Slot Pricing Optimization Math
BQ Internal Column Encoding Mechanics
Internal Column Encoding Mechanics
BigQuery vs Snowflake at Extreme Scale
BigQuery vs Snowflake at Extreme Scale
Designing a 10PB Architecture
Designing a 10PB Architecture
Cost Modeling Formulas for CFO Reporting
Cost Modeling Formulas for CFO Reporting
BQ Cross Region
Cross-Region Data Considerations
BQ Event Architecture
Designing a 1PB Event Architecture
BQ Slot
How Slot Fairness Scheduling Works Internally
BigQuery Adaptive Repartitioning
How BigQuery Adaptive Repartitioning Works
BQ Isolation Strategies
Advanced Workload Isolation Strategies
BigQuery columnar storage
How BigQuery Internally Stores Column Chunks
Google BQ BI Engine
BI Engine vs Slots
Google BQ Join
How to Design Join Keys to Avoid Skew
Google BigQuery Shuffling
How Shuffle Memory Pressure Causes Stage Reattempts
Google BigQuery Troubleshooting
Debug Slow Queries Using Execution Plans
BigQuery Query Execution
How BigQuery Query Execution Stages Use Slots Internally?
Google Big Query Optimisation
Optimizing Google BigQuery is about reducing scanned data, improving parallelism, and managing compute capacity effectively. Below is a structured explanation covering partitioning, clustering, slot management, and the difference between slots and slot contention.
GCP Data Architect Series - Part X
When would you use Cloud SQL vs. Cloud Spanner vs. Bigtable?
GCP Data Architect Series - Part IX
Here’s a clear comparison of Pub/Sub, Storage Transfer Service, and BigQuery Data Transfer Service in Google Cloud — what they’re for, how they work, and when to use each.
GCP Data Architect Series - Part VIII
Here’s a clear, practical comparison between Google Cloud Dataflow (Apache Beam) and Google Cloud Dataproc (Apache Spark / Hadoop) — focusing on architecture, use cases, and decision guidance.
GCP Data Architect Series - Part VII
Compare BigQuery vs Snowflake dimensional modeling differences
GCP Data Architect Series - Part VI
Real Production Architecture Pattern (BigQuery)
GCP Data Architect Series - Part V
Kimball vs Data Vault in BigQuery
GCP Data Architect Series - Part IV
Implementing SCD Type 2 in BigQuery Let’s say customer address changes must be tracked historically.
GCP Data Architect Series - Part III
Walk through a concrete example (e.g., e-commerce in SQL)
GCP Data Architect Series - Part II
Dimensional modeling in BigQuery follows classic data warehouse principles (Kimball-style) — but you optimize for cloud-native, columnar, massively parallel processing.
GCP Data Architect Series - Part I
GCP Data Architect interviews focus on designing scalable, secure data pipelines and warehouses using services like BigQuery, Dataflow, Pub/Sub, and Cloud Storage. Key areas include optimizing storage costs, selecting between transactional (Spanner/SQL) and analytical (BigQuery) databases, ensuring data governance, and implementing hybrid/multi-cloud solutions.
Cassandra for AI: No more Small Data
A common design strategy for a new application’s data storage is to build the app with a simple, smaller-scale database. However, the last few years have seen global data usage hitting exponential growth, largely driven by AI use cases. The old adage of “SQLite is all you need” just doesn’t cut it anymore; especially when building an AI application.
Identify true cloud versus pseudo-cloud
This blog aims to expose the blurred lines between data centre hosting and real cloud computing — and to make a strong case for why recognising these pseudo clouds is critical, especially for enterprises and financial institutions running mission-critical workloads. What’s being marketed as cloud may in reality be a repackaged infrastructure offering — a mere subset of what true cloud platforms are designed to deliver.
Python Foundation
Python has become one of the most accessible and widely used programming languages in the world. It was created by Guido van Rossum in the late 1980s and released publicly in 1991. It is open source, and today it powers various applications including websites, scientific computing, artificial intelligence, automation, and more. This beginner's guide is designed for readers who have never written code before and will demonstrate some Python basics.
Sequence Diagram
The sequence diagram is used primarily to show the interactions between objects in the sequential order that those interactions occur. Much like the class diagram, developers typically think sequence diagrams were meant exclusively for them.