Qingyang East Data West Cost Analysis

Background and problem

The “East Data, West Computing” project involves multiple categories of investment — data centres, energy, network and operations — so scattered cost data had to be organised into comparable definitions before the input-output relationship could be assessed.

Constraints

Public data is limited, so some costs had to be estimated from industry parameters.
The project timeline was short (about 3 months), requiring usable conclusions within a limited time.
The report targets non-technical readers, so conclusions must be traceable.

Approach and architecture

First establish a cost classification framework (construction, energy, network, operations), then collect and verify data item by item, build a cost estimation model, and finally carry out input-output analysis and scenario comparison.

Key decisions

Classify first: unify cost categories to avoid double counting.
Transparent parameters: estimation parameters and their sources are listed in the report for review.
Scenario analysis: present baseline, optimistic and conservative scenarios rather than a single-point conclusion.

Results and measurement

Completed the collection and organisation of cost data, contributed to building the cost estimation model, and independently completed the input-output analysis report, providing a structured basis for decision discussions.

Technical details

Broke down cost categories such as data centre, power, network and operations.
Used a cost estimation model to connect capacity, unit price and scenario assumptions.
Independently completed the input-output analysis and the report presentation.

Reflection

The credibility of estimation research depends on the sources of its parameters. If I did it again, I would record a source and confidence level for every parameter and add sensitivity analysis.

Scope and security

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