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Anil Thapa
Anil Thapa

Anil Thapa

Data & AI Platform Leader

Both halves of the data problem.

The platform, and the strategy it is supposed to serve.

I'm Anil Thapa. Fifteen-plus years across both: query plans and partition schemes early, then data functions hired from zero, warehouses consolidated out of silos and mergers, and ingestion rebuilt and proven before anyone was asked to trust it.

The hard part is usually the second half, and you don't get a hearing for it without the first. This site is where I write it down: the patterns that held, the ones that didn't, and what I'd tell someone facing the same call. No tutorials; a model answers those faster than I can.

Read the writing What I've built Speaking
Hands on
Still in the query plan when that is what the problem needs
Built from zero
Central data functions, hired and structured from scratch
Boardroom
Strategy with executives, not reporting to them
Run more than once
Patterns repeated across engagements, not a single project

Selected work

The full body of work
01Greenfield data function, analysts embedded across departments

Building a data function from zero

No data team. Engineers working in a vacuum, product managers asking developers for numbers, and every department with its own analyst producing a different answer to the same question. The platform was the straightforward part.

  • Centralize the definitions first, the people second, the tools last
  • Analysts join the centre for governance and stay close to their department
WarehouseTransformationOrchestrationBIGovernance
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02Executive partnership across departments and at board level

Data in the boardroom

Being in the room is not the same as being useful in it. Most of the work is not C-suite set pieces. It is department heads, one at a time, and the argument is never really about metric definitions.

  • Executives do not want the number, they want the decision it implies
  • Align on the strategy first; metric definitions are the mechanism, not the point
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03Data quality and reliability as an operating discipline

Earning trust in the numbers

Trust in a data platform does not degrade gracefully. It holds, then one confidently wrong number in a visible setting, then everyone checks everything manually forever. Treating quality as a discipline rather than a side effect.

  • Trust is a step function, not a gradient, protect the step
  • Cover the numbers your most skeptical stakeholder uses, first
TestingFreshness monitoringLineageAlerting
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What I write about

Agentic & AI systems

What actually happens when you put agents and LLMs to work inside a real data organization, and what the demos leave out.

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Leading data teams

Hiring, structure, capacity and the stakeholder work nobody puts on a roadmap. Building a function, not just a backlog.

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Data in the business

Executive partnership, strategy, and the difference between reporting on decisions and being present while they are made.

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Trust & governance

Quality, definitions, lineage and incidents. Why trust is a step function and how to keep it on the right side of the step.

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Architecture & economics

Platform decisions with the reasoning shown, including what they cost to run and the tradeoffs I accepted.

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Recent writing

All writing
Architecture & economics

The tools I use

The current working set, kept alongside the 2025 list rather than edited over it. The gap between the two is the interesting part: the core barely moved, a compliance tool became a runtime dependency, and a third of the list stopped being data tooling at all.

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Data in the business

What BI means, revisited

I defined business intelligence in 2021, revisited it in 2024, and I'm revisiting it again. What changed, what didn't, and which of my own definitions aged worst.

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Speaking, podcasts, and advisory

I speak about building data functions from zero, what changes when data reaches the boardroom, and agentic systems against warehouses that carry real history. I also advise a small number of data leaders, either on a specific decision or as a standing sounding board. If that fits your event or your problem, get in touch.

Speaking topics Advisory hello@anilthapa.com