Insights
Practical guides on remote engineering, data and AI.
Written by the people who do the work. Plain answers to the questions teams ask before they hire a remote data, software or AI team.
AI engineering
How Do You Let an AI Assistant Query Your Data Warehouse Safely?
A step-by-step pattern for giving Claude, GPT or Gemini read-only access to a warehouse: scoped identity, checked SQL, row limits, redaction and provenance.
Warehouse migration
How Do You Move Excel Reporting into a Cloud Data Warehouse?
How to move month-end Excel reporting into Snowflake or BigQuery: finding the sources and rules behind the spreadsheets, the order of work and reconciliation.
Finance data engineering
Reconciling Dynamics 365 Business Central With Your Data Warehouse
Why Business Central ledger data drifts from warehouse reports, a reconciliation-first integration method and what to check before trusting a dashboard.
Cost guide
What Does a Remote Data Engineering Team from India Cost?
What sets the price of a remote data engineering team from India, where the saving really comes from, how to compare quotes and the costs buyers forget.
Buyer question
Looking for a Data Consultancy Company for an Offshore Team?
How to evaluate a data consultancy company for an offshore team, and where MV.tech fits for data engineering, analytics, BI and AI delivery from India.
Buyer's guide
12 Questions to Ask Before Hiring a Remote Data Engineering Consultancy
A buyer's checklist for choosing a remote data engineering partner: who does the work, how the first milestone is scoped, how correctness is proven and what is included.
Remote delivery playbook
How to Work with an India-Based Engineering Team Across Timezones
Realistic overlap windows, what to agree before you start and the async habits that make a remote engineering team in India work for US, UK, EU and Australian companies.
AI engineering
RAG vs Fine-Tuning: Choosing the Right Approach for an Internal Knowledge Assistant
A plain-language comparison of retrieval-augmented generation and fine-tuning for company knowledge assistants: when each fits, permissions, evaluation and cost.
Engagement models
Staff Augmentation vs Project Consulting vs Recruitment: Which Engagement Model Fits?
How to choose between embedding a consultant, commissioning a scoped project and hiring permanently for data, software and AI work: control, cost, speed and risk.
AI engineering
What Is an MCP Server, and When Should a Business Build One?
A business-level explanation of the Model Context Protocol: what an MCP server exposes, when building one makes sense, the security decisions involved and a first project.
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