Author name: Mahesh

Mahesh is a data and analytics professional with experience in SQL, Python, cloud technologies, automation, applied AI/ML, and production analytics systems. At Digital Stackroom, he writes practical technical guides covering AI, data engineering, automation, cloud architecture, and developer tools.

Digital Stackroom executive dashboard infographic showing hierarchy, clarity, alignment, KPI cards, trend charts, and actionable insights for Looker Studio dashboard design.

Data & Analytics

How to Build Actionable Executive Dashboards: Looker Studio Layout Principles and Metric Design

Mahesh / October 23, 2026

Most business intelligence dashboards fail not because the underlying SQL pipeline is broken, but because they overwhelm decision-makers with raw […]

Google BigQuery data modeling infographic showing table partitioning, clustering, optimized SQL queries, and cost controls for scalable analytics workloads.

Data & Analytics

Designing Scalable Data Models in Google BigQuery: Partitioning, Clustering, and Cost Controls

Mahesh / October 23, 2026

Google BigQuery’s serverless architecture delivers near-instant scalability across petabyte-scale datasets. However, because BigQuery operates on a decoupled compute-and-storage model with […]

SQL CTEs vs subqueries infographic comparing execution plans, readability, optimizer behavior, and memory impacts in complex analytical queries.

Data & Analytics

Common Table Expressions (CTEs) vs. Subqueries: Execution Plans, Readability, and Memory Impacts

Mahesh / October 23, 2026

Data analysts and backend engineers frequently debate whether to structure complex queries using Common Table Expressions (WITH blocks) or nested […]

SQL window functions optimization infographic showing PARTITION BY, ORDER BY, window frames, B-tree indexing, execution plans, and performance improvements for analytical queries.

Data & Analytics

Optimizing Window Functions in SQL for Analytics: Performance, Execution Plans, and Indexing

Mahesh / October 23, 2026

Window functions are indispensable in modern analytics. From running balances and cohort retentions to top-N row filtering, they replace convoluted […]

SQL indexing vs table partitioning infographic comparing B-tree indexes for faster row lookups with range partitioning for splitting large datasets into manageable date-based partitions.

Data & Analytics

SQL Indexing vs. Table Partitioning: When to Use B-Trees vs. Range Partitions in Large Datasets

Mahesh / October 23, 2026

When queries begin to slow down on multi-million row tables, engineering teams often reach for the same immediate fix: add […]

AI architecture infographic comparing prompt engineering, RAG, fine-tuning, and tools or APIs as different fixes for instructions, knowledge, specialized behavior, and live data or actions.

AI & Machine Learning

Your AI App Is Wrong. Should You Rewrite the Prompt, Add RAG, or Fine-Tune the Model?

Mahesh / October 17, 2026

Updated October 2026 The AI assistant was wrong. That part was obvious. What wasn’t obvious was what the team should […]

Person reviewing an AI assistant with a simplified Test, Measure, Improve, and Release evaluation workflow for LLMs, RAG systems, and AI agents.

AI & Machine Learning

The AI Demo Looked Great. Then We Tested It: A Practical Guide to Evaluating LLMs, RAG Systems and AI Agents

Mahesh / October 17, 2026

Updated October 2026 The demo lasted twelve minutes. Every question worked. “What’s our annual leave policy?” The assistant answered correctly. […]

GPT-6 Sol vs Claude Opus 5.5 comparison for coding, AI agents, pricing, and real-world production workloads.

AI & Machine Learning

GPT-6.1 Sol vs Claude Opus 5.5: Which Model Should You Actually Use for Coding and AI Agents?

Mahesh / September 24, 2026

Updated October 2026 A few years ago, choosing an AI model was mostly a capability decision. You looked for the […]

GPT-6 Sol and Luna compared with GPT-6 Astra across pricing, reasoning capability and AI workloads.

AI & Machine Learning

OpenAI Made Frontier AI Much Cheaper: What GPT-6.1 Sol and Luna Mean for Developers

Mahesh / September 24, 2026

Updated October 2026 For much of the generative AI race, the industry focused on one question: Which company has the […]

Gemini agentic video understanding showing how AI can search a video timeline, inspect relevant moments, adjust frame rate, use transcripts or audio, and avoid processing every frame.

AI & Machine Learning

AI Doesn’t Need to Watch Every Frame: How Gemini’s Agentic Video Understanding Changes Video Analysis

Mahesh / September 22, 2026

Video creates a strange problem for artificial intelligence. A ten-page document contains a limited amount of information. A ten-minute video […]