Open the brief
Read the requester, cutoff, response window, decision standard, and required handoff before touching the data.
WORKBENCH GUIDE / LEARNER WORKFLOW
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.
Read the requester, cutoff, response window, decision standard, and required handoff before touching the data.
Use the public data dictionary to understand grain, keys, reliability, clocks, known exceptions, and relationships.
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.
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.
Use scratch notes for assumptions and open questions, append concise evidence records, then write the decision-ready conclusion in Final Brief.
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.
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.
Setup expectations, time ranges, scaffolding guidance, grading boundaries, and the local submission viewer are collected in the instructor desk, separate from the working interface.