Category: Tech Notes
-
SQL Joins: Combining Tables with INNER and LEFT JOIN (Data Analyst Series, Part 7)
Learn SQL joins the practical way. INNER JOIN keeps matches, LEFT JOIN keeps every row, and the ON versus WHERE trap that quietly drops the rows you need.
-
SQL SELECT, WHERE and ORDER BY: Your First Queries (Data Analyst Series, Part 6)
Write your first real SQL queries. SELECT to choose columns, WHERE to filter rows, ORDER BY to sort and LIMIT to cap, all against a five-row sample table.
-
How Data Is Stored: Tables, Types, CSV Files and Databases (Data Analyst Series, Part 5)
Tables, data types, CSV files and databases explained for beginners, so the SQL in the next parts reads like plain sentences instead of a puzzle.
-
Spreadsheet Formulas and Pivot Tables That Do Real Work (Data Analyst Series, Part 4)
Two spreadsheet features do most of an analyst’s real work: conditional formulas like SUMIFS and pivot tables. Here is how to use both to answer a question in seconds instead of scrolling for an hour.
-
How to Think in Data: Questions, Metrics and Hypotheses (Data Analyst Series, Part 3)
Analysis starts with a sharp question, not a spreadsheet. Here is how to turn a vague request into a clear question, the right metric, and a hypothesis the data can actually test.
-
The Analyst Toolkit and a Skills Roadmap for Beginners (Data Analyst Series, Part 2)
The four tools a data analyst actually uses, spreadsheets, SQL, a BI tool, and Python, and the order to learn them in so you become employable in a few months.
-
What a Data Analyst Really Does, vs Data Scientist and Data Engineer (Data Analyst Series, Part 1)
A plain, beginner-friendly breakdown of what a data analyst actually does day to day, how the job differs from data scientist and data engineer, and what the three roles pay.
-
IBM watsonx vs the Field, the Cost Recap and the Verdict (IBM Gen AI Series, Part 24)
The final part of the IBM watsonx series puts the platform against Bedrock, Azure, and Vertex on the axes that decide a regulated purchase, recaps what a governed deployment really costs, and gives a clear verdict on where watsonx wins and where to walk away.
-
watsonx Reference Architectures for RAG, Agentic, and Regulated Workloads (IBM Gen AI Series, Part 23)
The three watsonx reference architectures that recur in real builds: enterprise RAG on watsonx.data, agentic systems on watsonx Orchestrate, and a watsonx.governance overlay for regulated work. Which to build first, what each costs, and where they break.
-
watsonx LLMOps on OpenShift, from Notebook to Promotion Gate (IBM Gen AI Series, Part 22)
How to run generative AI features in production on the IBM stack: watsonx.ai for models and governance, Red Hat OpenShift AI for pipelines and GPUs, and a promotion gate that refuses to ship a regression.
-
EU AI Act Readiness and Responsible AI on watsonx (IBM Gen AI Series, Part 21)
The 2026 Digital Omnibus pushed high-risk deadlines to December 2027, but GPAI and transparency duties still bite this year. Here is how I classify a watsonx system and build the evidence pack before an auditor asks.
-
watsonx Cost Governance and FinOps, from Resource Units to a Real Budget (IBM Gen AI Series, Part 20)
watsonx charges in Resource Units, capacity unit hours, and a flat instance fee. Here is how those meters add up, and the plan choice that keeps your generative AI bill honest.
Architect’s Toolkit
PJ’s Tools
- Infra 360 Hub – All Series
- VCF 9 Interactive Walkthroughs
- VCF Design Cheatsheet
- VCF Upgrade Planner
- VCF 9 Series Hub
- VCF Deployment Hub
- AI Stack Hub
- AI Infra Sizing & Cost Calculator
- LLM & RAG Cost Calculator
- DrJhaGPT – Ask Pranay
VMware Cloud Foundation
- VCF Documentation
- VCF 9 Planning & Preparation Workbook
- VCF Bill of Materials (BoM)
- VMware Compatibility Guide
- VMware Interoperability Matrix
- VMware Configuration Maximums
- VMware Ports & Protocols
- VMware Hands-on Labs
- RVTools Download
Nutanix
AI & Cloud-Native Platform
- NVIDIA Build (Model Catalog)
- NVIDIA AI Enterprise Reference Architecture
- NVIDIA NIM Performance Benchmarking
- NVIDIA NGC Catalog
- NeMo Microservices Helm Chart
- Helm Charts Repository
- Hugging Face Models
Architecture & Design
About the Author
Dr Pranay Jha
Dr. Pranay Jha is a Cloud and AI Consultant with 18+ years of experience in hybrid cloud, virtualization, and enterprise infrastructure transformation. He specializes in VMware technologies, multi-cloud strategy, and Generative AI solutions. He holds a PhD in Computer Applications with research focused on Cloud and AI, has published multiple research papers, and has been a VMware vExpert since 2016 and a VMUG Community Leader.
You May Have Missed
DrJha