THE ANALYSTANALYTICAL WORK SIMULATIONS
OPEN WORKBENCH ↗

WORKBENCH GUIDE / LEARNER WORKFLOW

Arrive, investigate, hand off.

No account or local setup is required. A current laptop or desktop browser is required to complete an assignment; phones are suitable only for previewing the brief. All assignment data and code execution remain on the learner’s device.

01

Open the brief

Read the requester, cutoff, response window, decision standard, and required handoff before touching the data.

02

Inspect the source register

Use the public data dictionary to understand grain, keys, reliability, clocks, known exceptions, and relationships.

03

Establish evidence in SQL

Run the starter query, inspect counts and grains, then replace it with your own reconciled evidence layer. Query results are limited to 1,000 displayed rows; the engine evaluates the full assignment data pack.

04

Use Python for analytical work

Load the same named tables with `from analyst import table`, then use Pandas, Matplotlib, SciPy, or scikit-learn. Matplotlib figures appear directly below the worksheet; no file paths or data uploads are required.

05

Keep reasoning separate from conclusions

Use scratch notes for assumptions and open questions, append concise evidence records, then write the decision-ready conclusion in Final Brief.

06

Ask for focused AI help—optionally

Choose AI Help Packet in the workbench to download a reviewable Markdown brief for an external AI tool. You choose which worksheet or notes to include; The Analyst creates the file locally and does not send it. Follow your course or institution policy, and verify the advice by running the work yourself.

07

Export the handoff

Download one .analystcase file containing SQL, Python, scratch notes, the final brief, evidence, captured outputs, versions, and hashes. Keep it for your own record or share it for grading, coaching, or peer review.

SUPPORTEDCurrent Chrome, Edge, Firefox, or Safari on a laptop/desktop
STORAGEDrafts autosave to this browser only
PRIVACYExecution and AI-packet creation are local; sharing is always your action
RECOVERYDownload submissions regularly when working across devices
READY FOR THE FIRST ASSIGNMENT

Start with the Monday scorecard.

OPEN WORKBENCH →
FACILITATING THE WORK?

Setup expectations, time ranges, scaffolding guidance, grading boundaries, and the local submission viewer are collected in the instructor desk, separate from the working interface.

OPEN INSTRUCTOR DESK →