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SuccessKPI internship projectAdopted by the Solutions team

Greyline

Turn a customer question into a buildable dashboard plan.

A workspace that keeps discovery, demo datasets, metric definitions, visualization plans, and presentation components connected, so a consultant can carry one consistent story into the final analytics platform.

My role
Architecture, analytical logic, implementation, validation, and handoff
Built with
Browser application, Python MCP tools, structured project artifacts
Greyline’s Metrics Sheet showing a synthetic support-operations project and the exact first-contact-resolution formula, dependencies, and build notes.
Actual application: the metric catalog and an inspected first-contact-resolution definition from a synthetic portfolio build.View full size

The Metrics Sheet and planner screenshots show a fresh, entirely synthetic support-operations demonstration generated in Greyline’s deterministic mode. The validation screen is a saved synthetic QA build. No customer discovery records are included.

Why I built it

A useful analytics demo starts well before the dashboard. The discovery questions, dataset, metric definitions, visualization choices, and implementation instructions all need to agree.

I built Greyline during my solutions-consulting internship to make that preparation reusable. The goal was to give the next person a coherent build kit they could understand and carry forward, rather than a collection of disconnected outputs.

My part in the work

I owned the architecture, analytical logic, implementation, testing, iteration, and handoff. I also built a Python MCP server with nine tools for tasks such as dataset profiling, formula validation, and checking claims against source data. The SuccessKPI Solutions team adopted the application for continued use.

How the pieces connect

  1. Frame the question

    Capture the audience, use case, story, datasets, and intended dashboard structure.

  2. Generate one kit

    A shared generation workflow records the request and maps its output into synchronized project artifacts.

  3. Inspect and assemble

    Review formulas, dependencies, visualization assignments, page layout, and reusable HTML components.

  4. Build and hand off

    A consultant imports the data and constructs the native metrics and visuals in the target analytics platform.

Inside the work

Actual screens, with the reasoning beside them

Keep the page plan connected to the objects.

The Dashboard Planner opens with the active project’s HTML components and native visualization plan already arranged. In this synthetic example, eight planned tiles make the page structure visible before the final dashboard is assembled.

The distinction between HTML presentation elements and native analytics visuals matters: the blueprint tells the builder what each object is, instead of treating the whole dashboard as an opaque picture.

Greyline Banner Builder showing a generated one-page dashboard plan with eight labeled HTML and native visualization tiles.
A real generated plan from the synthetic portfolio example, with separate labels for HTML components and native visualizations.View full size

Make implementation traps part of the handoff.

The preparation checklist carries forward practical issues such as import types, joins, metric scales, and the formula syntax expected by the analytics platform.

The metric view goes further: its first-contact-resolution definition includes the exact formula, dependencies, build order, and a warning about comparing a text attribute to a quoted value. That detail helps another person reproduce the intended calculation.

Greyline’s saved Offline QA Build showing its pre-flight checks for dataset preparation, formula syntax, and metric scales.
Saved release evidence from the synthetic Offline QA Build: checks travel with the project rather than living in a separate conversation.View full size

What the demonstration actually produced

The synthetic portfolio run generated a 450-row interaction dataset, one chapter, five metric/object definitions, three native visualization definitions, and five HTML components. These counts describe this example, not a product limit or customer deployment.

Dataset
450 synthetic interaction rows
Metric example
First-contact resolution, with numerator, denominator, dependencies, and exact formula
Page plan
Five HTML components plus three native visualization tiles

Decisions that shape the project

One project owns the artifacts

Datasets, the Blueprint, Metrics Sheet, Viz Assembly, HTML Kit, and planner all refer to the same build context.

Keep local generation honest

The standalone workflow uses a deterministic browser engine. Optional provider adapters are separate; a local result is not presented as a cloud-model response.

Design for the next builder

Copyable formulas, explicit dependencies, visual plans, and validation guidance make the handoff part of the product.

Where it stands

The application was adopted internally by the Solutions team. It prepares a dashboard build kit; it does not directly author a production MicroStrategy dashboard. The screens here show the Grey Line release. Later project materials use the name DTD, or Data to Dashboard.

What comes next

Continue improving the generation, verification, and handoff workflow while keeping the dataset, metrics, and page plan consistent.