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Data Analytics Case Studies

Dashboards, KPI systems, and decision support designed for operators, founders, and investors.

These projects are about turning data into choices that someone can actually make: narrative interfaces, KPI definitions, reward dashboards, market analyses, and analytics patterns that reduce ambiguity instead of producing one more chart.

Narrative dashboards KPI and BI design Decision support Market analysis
December 2025

Attimo V0.1 - A Narrative Dashboard for Live Sport

Turning raw match events into auditable story objects, QA cues, and locale-aware outputs for editorial and product teams.

Attimo narrative dashboard preview
October 2025

Sunshine Features - Rapid EDA for Feature Viability

A quick but disciplined analytics pass that answered whether weather was worth modeling or just another expensive distraction.

Sunshine feature heatmap
May 2025

On-chain Rewards - From Solidity Calls to Tableau

A hybrid analytics pipeline combining live contract reads, market data, and capacity data into one reporting layer.

On-chain rewards dashboard preview
March 2025

Bootstrap Pool - Jump-starting Hardware Capacity with Liquidity Incentives

Modeling the runway, uptake, and economic shape of a liquidity-incentive program before it became an expensive experiment.

Bootstrap pool runway chart
September 2024

Collateral vs Rewards - Stress-Testing the Economic Levers

Using analytics and simulation outputs together to understand how reward design and collateral requirements pulled against each other.

Collateral versus rewards chart
May 2024

SWOT Analysis of the Gaming Industry

A market-intelligence piece on the gaming sector focused on strategic pressure points, monetization risk, and where the industry still has room to grow.

Gaming market SWOT graphic
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Attimo V0.1 - A Narrative Dashboard for Live Sport

1. Problem

Sports content is abundant. The scarce thing is a trustworthy story layer that turns raw events into something editors, sponsors, and product teams can act on without losing factual grounding.

2. Approach

Attimo V0.1 structured the interface around beats, state, arcs, and output variants. That made the narrative layer inspectable instead of mystical.

3. Evidence

Narrative timeline
The narrative timeline made the model logic visible enough for product and editorial review.
Caption panel with QA badges
QA badges next to generated output turned trust from a vague claim into something reviewable.

4. Outcome

Attimo proved a product primitive: one event stream can feed many audiences if the narrative layer is explicit, inspectable, and tied back to facts. That is what helped it move from demo to early commercial traction.

5. Tech stack

6. Useful links

7. Related reading

8. Call to action

If you are building a narrative product around event data and need the output to stay explainable, I can help with the data model, UI, and QA surface.

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Sunshine Features - Rapid EDA for Feature Viability

1. Problem

Weather features look appealing because they feel intuitive, but intuition is not a good enough reason to increase pipeline complexity. The real question was whether sunshine carried enough signal to justify modeling effort.

2. Approach

I ran a quick exploratory pass that prioritized data quality, interaction effects, and sample-size visibility over fancy modeling. The aim was to decide whether the feature was worth a proper sprint.

3. Evidence

Mean sales by sunshine deciles
The heatmap surfaced non-linear patterns quickly, but it also made the weak sample corners obvious.
Within-site uplift by sunshine deciles
Within-site uplift was the more honest view because it stripped away the baseline differences between locations.

4. Outcome

The analysis did its job: it stopped the team from overcommitting to a pretty idea before the feature had earned the operational cost of proper integration.

5. Tech stack

6. Useful links

7. Related reading

8. Call to action

If you need to decide whether a feature idea deserves proper modeling work, I can help design the fast analytics pass that answers the question cleanly.

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On-chain Rewards - From Solidity Calls to Tableau

1. Problem

Reward analytics needed to combine live contract state, market pricing, and capacity context. None of those lived in one place, and nobody wanted a reporting stack that depended on hand-maintained exports.

2. Approach

The pipeline pulled contract data, blended it with market feeds and capacity data, then published a presentation layer designed for dashboards rather than notebooks.

3. Evidence

Claimed versus unclaimed rewards view
Once the feeds were joined upstream, the reporting layer could answer commercial and operational questions from one place.
Unclaimed rewards per PB
The per-PB view made efficiency and capacity behavior legible to stakeholders who did not care about raw contract calls.

4. Outcome

The resulting analytics surface supported investor, finance, and operations conversations without forcing each audience to reconstruct the data story from separate dashboards.

5. Tech stack

6. Useful links

7. Related reading

8. Call to action

If you need one reporting layer across on-chain, market, and operational data, I can help design the ingestion and presentation model that makes it hold together.

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Bootstrap Pool - Jump-starting Hardware Capacity with Liquidity Incentives

1. Problem

Liquidity incentives are easy to announce and hard to justify. Before launching a bootstrap pool, the team needed to know whether the mechanism could actually accelerate hardware supply without creating a short-lived optics win and a long-lived economic mess.

2. Approach

The analysis focused on runway, uptake, and incentive quality. Instead of treating the pool as a marketing event, I treated it as a measurable program with failure modes.

3. Evidence

Bootstrap pool runway chart
The runway view forced the conversation toward durability instead of just headline APR.
Capacity by region view
Regional capacity views helped test whether the program was shaping the right supply, not just any supply.

4. Outcome

The work gave stakeholders a clearer picture of what the bootstrap pool could and could not realistically achieve, which made the incentive design discussion far more grounded.

5. Tech stack

6. Useful links

7. Related reading

8. Call to action

If you are considering an incentive program and need to pressure-test the economics before launch, I can help build the decision model.

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Collateral vs Rewards - Stress-Testing the Economic Levers

1. Problem

Collateral and rewards were both trying to stabilize the same system, but in different ways. The question was how far each lever could move before it started undermining the other.

2. Approach

I framed the analytics around tradeoffs rather than single metrics. That meant comparing reward attractiveness, safety margins, and system behavior together instead of optimizing one in isolation.

3. Evidence

Collateral ratio versus reward
The useful view was not a single optimum. It was the band where the system stayed viable without becoming economically unappealing.
Collateral ratio trajectory
Trajectory views helped explain how the system behaved over time rather than at one arbitrary snapshot.

4. Outcome

The analysis clarified why collateral and reward policy had to be discussed together. That later connected directly into the stronger Monte Carlo work on collateral safety.

5. Tech stack

6. Useful links

7. Related reading

8. Call to action

If your policy or incentive design has interacting levers that are being discussed separately, I can help build the shared analytics surface that keeps the tradeoffs visible.

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SWOT Analysis of the Gaming Industry

1. Problem

The gaming industry is usually described in slogans: huge market, high growth, constant innovation. That is not enough for strategy. The interesting part is where the strengths are real, where monetization pressure creates fragility, and which opportunities still justify investment.

2. Approach

I rewrote the SWOT as a market-intelligence exercise rather than a classroom template. The goal was to isolate the commercial pressure points founders and operators actually need to think about.

3. Evidence

Gaming market SWOT graphic
The useful output of the SWOT was not the quadrant graphic. It was the prioritization conversation it enabled around growth, risk, and monetization quality.

4. Outcome

The final piece served as a strategic summary for anyone trying to understand where the gaming market remained structurally strong and where the underlying model was getting more fragile.

5. Tech stack

6. Useful links

7. Related reading

8. Call to action

If you need a strategy memo or market-intelligence piece that goes beyond boilerplate trends, I can help turn the research into something your team can act on.