Skip to content
Anil Thapa
Anil Thapa

Anil Thapa

Data & AI Platform Leader

Both halves of the data problem.

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

For anyone paying for a data platform, or building a career on one.

The platform
Warehouses that agree on one number, rebuilt pipelines proven before anyone has to trust them, and a bill someone can explain. Now also assistants, which have to know which questions are theirs to answer.
The people and decisions around it
Who owns each definition, whether the data team is asked before a decision or after it, and whether its recommendations get adopted. A platform is a cost until it changes a decision, and a career in data grows the same way.
Advisory & mentoring Case studies and essays
Built from zero
Central data functions, hired and structured from scratch
In the room
Analysis that reaches the decision while it is still open
Hands on
Still in the query plan when that is what the problem needs
The tradeoff, written down
Every case study names what its decision cost

Selected case studies

All case studies
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 center for governance and stay close to their department
  • Org design
  • Hiring
  • Platform strategy
  • Enablement
Read the case study
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.

  • Connect the number to a decision, an alternative, and a condition that would change your view
  • Align on the strategy first; metric definitions are the mechanism, not the point
  • Exec partnership
  • Decision support
  • Stakeholder alignment
Read the case study
03Data quality and reliability as an operating discipline

Earning trust in the numbers

A plausible wrong number can change how people use an entire platform. Prioritizing critical data, exposing uncertainty, and rebuilding confidence through a response people can inspect.

  • Trust can fall quickly; recovery needs visible evidence of a better process
  • Cover the numbers your most skeptical stakeholder uses, first
  • Data quality
  • Governance
  • Stakeholder alignment
Read the case study

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.

Browse

Leading data teams

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

Browse

Data in the business

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

Browse

Trust & governance

Quality, definitions, lineage and incidents. How to make reliability visible and rebuild confidence when something goes wrong.

Browse

Architecture & economics

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

Browse

Recent essays

All essays
Data in the business

Recommendations that go nowhere

The analysis was sound and the recommendation was politely ignored. It usually never named the decision, offered no alternative, or buried the uncertainty that would have made it usable. Decision, alternative, condition.

Read the post
Leading data teams

Too many priorities, none of them yours

When a data team's roadmap is a list of other people's requests, a better scoring model only sorts the queue. What changes it is one sentence about what the team is for, used to decline something.

Read the post

Work through the next decision

Advisory for organizations, whether the question is a decision the platform has to serve or a team that needs to work differently, and mentoring for the people who want to shape those decisions rather than supply the numbers for them. Invitations for talks, podcasts, and team sessions go to the same address; the contact page says what to include.

Advisory & mentoring hello@anilthapa.com