A common ask from teams evaluating Sigma is migrating their MicroStrategy (Strategy One) footprint — usually to take advantage of all the amazing things Sigma offers. The conversion itself can be a blocker — and the part this QuickStart automates.

The usual MicroStrategy-to-Sigma migration loop is rebuild-the-schema-by-hand, re-author every attribute / fact / metric as a Sigma formula, recreate each dossier chapter and visualization, line the layout up against the source, then eyeball the numbers and hope nothing drifted in the translation. Done on a single dossier it's tedious. Across a project with dozens of dossiers reading from a shared classic schema, it's the reason migration projects slip.

This QuickStart walks through a Claude Code skill called microstrategy-to-sigma that automates the loop.

Point it at a MicroStrategy dossier; it extracts the dossier definition and the full semantic model (attributes, facts, metrics, logical tables, hierarchy relationships) via the MicroStrategy REST API into a single bundle.json, translates each metric's MicroStrategy expression into a Sigma formula, builds a Sigma data model from the logical tables and joins the converter discovers in the schema, mirrors each chapter's tables and selectors as a Sigma workbook page, and runs a row-level parity pass that compares Sigma's output to MicroStrategy's own report results. It surfaces a punch list of anything it couldn't auto-translate — instead of silently producing a broken workbook.

Sample dashboard

For the demonstration, we'll convert a MicroStrategy dossier called Retail Insights — a merchandising dashboard that tracks inventory health, sell-through, and YTD revenue across a product catalog. The dossier surfaces overstock-vs-capacity, per-product ranking within product line, and store-level sales performance, all driven from a single denormalized warehouse table (3,592 rows at product-day grain, 27 columns covering brand / product / store attributes plus inventory and sales metrics):

What else this enables

A pure lift-and-shift is the floor, not the ceiling. The same skill family supports three follow-on moves that turn a migration into an upgrade:

Target Audience

Sigma SEs, technical CSMs, and migration partners running MicroStrategy-to-Sigma conversions — or scoping a batch migration with the companion microstrategy-assessment skill.

Prerequisites

Sigma Free Trial

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microstrategy-to-sigma is one of two skills that ship together as a single repo (cloned in the next section). Most of this QuickStart focuses on the converter — but knowing where the assessment skill fits saves dead ends later when scoping a batch migration.

Skill

Role

When to reach for it

microstrategy-assessment

Scoping

Auditing a MicroStrategy environment before committing to a conversion plan. Emits a per-dossier complexity readout (visualization-type histogram, metric convertibility, AE row-collapse flags, schema size), datasource inventory, and a value/cost-ranked migration shortlist that microstrategy-to-sigma can consume. Read-only — only GETs against the MSTR API.

microstrategy-to-sigma

Conversion

The subject of this QuickStart. Converts a single MicroStrategy dossier (or a batch via shortlist) to a Sigma data model and matching workbook with verified row-level parity.

Here's how the two skills connect in a full migration — microstrategy-assessment hands the converter a ranked shortlist, and microstrategy-to-sigma produces the Sigma workbooks with a verified parity report:

Which skill for your situation

Not every migration needs both skills. Use the table below to map your scenario to the smallest set that fits.

In this QuickStart we're in the first row — one MicroStrategy dossier whose classic schema reads from warehouse tables that we'll land in Snowflake — then run microstrategy-to-sigma.

Your situation

Skill(s) to use

1 dossier, classic schema reads from your warehouse

microstrategy-to-sigma

1 dossier, schema reads from a warehouse Sigma can't connect to

Land the data in your warehouse first (covered in Prepare the Demo Data), then microstrategy-to-sigma

10+ dossiers (any data source)

microstrategy-assessment → microstrategy-to-sigma in batch mode

Auditing MicroStrategy sprawl without converting yet

microstrategy-assessment only

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First we need to clone the skill's GitHub repository, configure MicroStrategy REST credentials, and capture your Sigma credentials.

The two skills live in sigmacomputing/quickstarts-public under microstrategy-migration-skills/.

From a terminal, run each command below one at a time so you can confirm each step before moving on.

Step 1: Create a local folder for the clone

mkdir -p ~/quickstarts-public

Step 2: Move into the new folder

cd ~/quickstarts-public

Step 3: Clone the repo without pulling any files yet

git clone --filter=blob:none --sparse https://github.com/sigmacomputing/quickstarts-public.git .

Step 4: Fill in only the microstrategy-migration-skills folder

git sparse-checkout set microstrategy-migration-skills

Step 5: Symlink microstrategy-to-sigma into the Claude skills folder

ln -s ~/quickstarts-public/microstrategy-migration-skills/microstrategy-to-sigma ~/.claude/skills/microstrategy-to-sigma

Step 6: Symlink microstrategy-assessment

ln -s ~/quickstarts-public/microstrategy-migration-skills/microstrategy-assessment ~/.claude/skills/microstrategy-assessment

Steps 5 and 6 should return with no error.

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Step 7: Install the Python dependencies the skill uses.
 The skill reads MSTR's YAML spec responses with PyYAML. Everything else is in Python's standard library.

python3 -m pip install pyyaml

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Step 8: Capture your Sigma API credentials.
 This script prompts for SIGMA_BASE_URL, SIGMA_CLIENT_ID, and SIGMA_CLIENT_SECRET and writes them into Claude's settings + the neutral ~/.sigma-migration/env file that the skill family uses to mint Sigma API tokens at runtime.

Run once per machine.

ruby ~/.claude/skills/microstrategy-to-sigma/scripts/setup.rb

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Step 9: Capture your MicroStrategy credentials.
 This script prompts for the Library URL, username, password, and optional project ID, then writes them into Claude's settings + the same neutral ~/.sigma-migration/env file.

Run once per machine.

ruby ~/.claude/skills/microstrategy-to-sigma/scripts/setup-microstrategy.rb

When the script asks for the Library URL, use the form below as a template. Replace the host with your own tenant's hostname (visible in your browser's address bar when you're logged into MicroStrategy Cloud). The /MicroStrategyLibrary suffix is required for both Cloud and on-prem deployments — the REST API lives under that path, and dropping it returns 404 on every call:

https://env-aBc12345xYz67890.cloud.strategy.com/MicroStrategyLibrary

The final prompt asks for a Project ID and is optional. Press Enter to skip.

The skill will default to the first project visible to your user, which is what you want for this QuickStart. If your tenant has multiple projects and the target dossier lives in a non-default one, paste that project's ID here (visible in MicroStrategy's URL when you have the project open).

MicroStrategy uses session-based auth — there's no API key concept; the skill calls POST /api/auth/login with loginMode 1.

Verify auth works:

source ~/.sigma-migration/env && python3 ~/.claude/skills/microstrategy-to-sigma/scripts/mstr.py

You should see a successful login probe and a list of projects visible to your user.

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Step 10: Verify Claude Code can invoke the skill.
 Type claude in your terminal to start Claude Code, then invoke the skill:

claude

/microstrategy-to-sigma

Claude should start reading the reference files and ask what dossier you want to convert.

Pause at that prompt — we'll hand it everything in one shot via the kickoff prompt in Run the Conversion:

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The MicroStrategy dossier we're migrating reads from a single denormalized retail-insights table — 27 columns covering brand / product / store dimensions plus inventory and sales metrics. For the migration to land in Sigma cleanly, the same table needs to exist in a connection your Sigma org can reach.

Data prep has two halves:

  1. MicroStrategy side — nothing to do here for this QuickStart. We've already exported the source table and hosted it as a CSV in Amazon S3. The Snowflake COPY INTO statement below reads from S3 directly — no local download needed.
  2. Sigma side (this section) — the same data needs to live in a Snowflake schema your Sigma connection can read. We'll create one.
USE ROLE ACCOUNTADMIN;
USE WAREHOUSE COMPUTE_WH;

CREATE DATABASE IF NOT EXISTS QUICKSTARTS;
CREATE SCHEMA  IF NOT EXISTS QUICKSTARTS.MSTR_RETAIL_INSIGHTS;
USE SCHEMA QUICKSTARTS.MSTR_RETAIL_INSIGHTS;

CREATE OR REPLACE FILE FORMAT csv_format
  TYPE = CSV
  FIELD_DELIMITER = ','
  SKIP_HEADER = 1
  FIELD_OPTIONALLY_ENCLOSED_BY = '"'
  NULL_IF = ('', 'NULL')
  EMPTY_FIELD_AS_NULL = TRUE;

CREATE OR REPLACE STAGE mstr_retail_stage
  URL = 's3://sigma-quickstarts-main/Microstrategy/'
  FILE_FORMAT = csv_format;

CREATE OR REPLACE TABLE RETAIL_INSIGHTS (
  "Brand"                    VARCHAR,
  "Date"                     DATE,
  "Date First Available"     DATE,
  "Product Color"            VARCHAR,
  "Product Description"      VARCHAR,
  "Product Image"            VARCHAR,
  "Product Line"             VARCHAR,
  "Product Link"             VARCHAR,
  "Product Name"             VARCHAR,
  "Product Size"             VARCHAR,
  "Product SKU"              VARCHAR,
  "Product Type"             VARCHAR,
  "Ranking in Product Line"  NUMBER(38,0),
  "Store Location"           VARCHAR,
  "Avg Unit Sold"            NUMBER(38,4),
  "Inventory"                NUMBER(38,4),
  "Inventory Capacity"       NUMBER(38,0),
  "Order Quantity"           NUMBER(38,0),
  "Overstock Percentage"     NUMBER(38,10),
  "Product Cost"             NUMBER(38,2),
  "Product Inventory"        NUMBER(38,4),
  "Product List Price"       NUMBER(38,2),
  "Product Rating"           NUMBER(38,4),
  "Product YTD Revenue"      NUMBER(38,2),
  "Product YTD Sales"        NUMBER(38,2),
  "Row Count"                NUMBER(38,0),
  "Total Sales"              NUMBER(38,2)
);

COPY INTO RETAIL_INSIGHTS FROM @mstr_retail_stage/retail_insights.csv ON_ERROR = ABORT_STATEMENT;

GRANT USAGE  ON DATABASE QUICKSTARTS                                      TO ROLE SIGMA_SERVICE_ROLE;
GRANT USAGE  ON SCHEMA   QUICKSTARTS.MSTR_RETAIL_INSIGHTS                 TO ROLE SIGMA_SERVICE_ROLE;
GRANT SELECT ON ALL    TABLES IN SCHEMA QUICKSTARTS.MSTR_RETAIL_INSIGHTS  TO ROLE SIGMA_SERVICE_ROLE;
GRANT SELECT ON FUTURE TABLES IN SCHEMA QUICKSTARTS.MSTR_RETAIL_INSIGHTS  TO ROLE SIGMA_SERVICE_ROLE;

-- Sanity-check row count. Expected: 3592.
SELECT COUNT(*) AS ROW_COUNT FROM RETAIL_INSIGHTS;

-- Total Sales baseline (~$3,169,933.01 for the warehouse snapshot).
SELECT TO_CHAR(SUM("Total Sales"), '$999,999,999.99') AS TOTAL_SALES_BASELINE
FROM RETAIL_INSIGHTS;

If the load completes cleanly, the Total Sales check returns roughly $3,169,933.01. Any mismatch means either a COPY partial-load error (check Snowflake's load history) or a different S3 file than expected.

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The converter needs a Sigma folder to land the new data model and workbook in. The skill will ask for the folder's UUID — it will be easier to have it ready before you return to the Claude prompt that's still paused after the skill loaded.

To keep this simple, we will use a plain folder and not a workspace.

Step 1: Create (or pick) a folder in Sigma.
 Open your Sigma org, navigate to where you want the migrated workbook to live, and create a folder for it. Something like:

MicroStrategy Migration Demo

Step 2: Grab the folder ID.
 Open the folder. The ID is the last segment of the URL — a short alphanumeric string, 21 characters. Copy it from the address bar and keep it on the clipboard for the next section.

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The skill can run interactively, asking for the dossier, warehouse, and Sigma destination one at a time. For a known target — like ours — it's faster to give Claude the entire job in one message. The skill recognizes a structured kickoff prompt and walks the pipeline directly, going straight from "go" through extract → convert → data model → workbook build → layout → parity.

If Claude is still running and paused at the skill's first prompt from Install and Configure the Skill, return to that terminal. If you closed Claude after that step, restart it now:

claude

/microstrategy-to-sigma

When Claude finishes loading the skill and asks what to migrate, choose Chat about this:

Paste the block below. Substitute your own values where the placeholders are:

The URL follows the shape /MicroStrategyLibrary/app/{projectId}/{dossierId}/{state}.

For example:

Copy the 32-character dossier ID — the second hex segment after /app/. Ignore the project ID (the skill defaults to your user's first project) and the trailing state token.

Run /microstrategy-to-sigma on the following. Walk every phase in SKILL.md end-to-end and stop only if a hard gate fails.

MicroStrategy
- Credentials sourced from ~/.sigma-migration/env (MSTR_BASE_URL, MSTR_USERNAME, MSTR_PASSWORD, optional MSTR_PROJECT_ID)
- Dossier ID: <your-dossier-object-id>

Warehouse (Snowflake)
- Database: QUICKSTARTS
- Schema: MSTR_RETAIL_INSIGHTS

Sigma
- SIGMA_API_TOKEN = mint from ~/.sigma-migration/env
- SIGMA_CONNECTION_ID: <your-snowflake-connection-id>
- SIGMA_FOLDER_ID: <your-folder-id>

Options
- Name prefix: MicroStrategy Retail Insights
- Auto-approve mid-pipeline questions: yes
- Parity: tolerate row-count drift between MicroStrategy (live) and the warehouse snapshot — this QuickStart uses a frozen CSV copy of the source. Report the delta with a row-level diff, but treat warehouse-snapshot staleness as a soft fail (not a gate-red).

Don't declare GREEN until the parity gate passes (or the tolerance above applies) and the visual-QA loop passes.

Claude reads the block, mints a fresh Sigma token from ~/.sigma-migration/env, sources the MSTR variables, and walks the phases end-to-end. The rest of the run is hands-off until a gate or decision point.

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When the migration completes, Claude prints a final summary covering the whole pipeline — every phase's result, the visual-QA outcome, the hard-gate verdict, and the URLs of the new Sigma data model and workbook:

The summary walks through six phases plus a visual-QA pass:

Open the new workbook in Sigma to see the migrated dossier:

Open the data model too:

Hand-polish items the skill flags rather than silently working around:

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A single dossier is the easy case. Real migrations involve MicroStrategy projects with dozens or hundreds of dossiers reading from a shared classic schema — and migrating them one-by-one through the converter loses the leverage of doing the planning work once. That's where the companion microstrategy-assessment skill comes in.

Point microstrategy-assessment at a MicroStrategy environment and it inventories every project, report, dossier, and datasource, scoring each on:

The output is a Sigma-branded readout.md you can share with stakeholders, plus a ranked migration shortlist sorted by value / (1 + cost) — the cheapest, highest-value dossiers to convert first.

The shortlist becomes input to a batch conversion plan — microstrategy-assessment groups dossiers that share the same logical tables so one Sigma data model can serve a whole family of workbooks instead of producing N near-duplicate DMs. microstrategy-to-sigma consumes that plan in batch mode and runs the conversions concurrently.

Typical flow for a real migration engagement:

  1. Run microstrategy-assessment against the target environment; review the shortlist with stakeholders.
  2. Pick the top N dossiers to convert first — or drop the cold ones entirely.
  3. Hand the batch plan to microstrategy-to-sigma and let it work through them.
  4. Spot-check each output; file the inevitable gap items upstream.

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The following is a "grab bag" of things that might come up during real conversions, with the fix for each.

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What you built is less a single conversion and more a repeatable migration path. The skill took a MicroStrategy dossier — classic schema, attributes, facts, metrics, chapter layout, selectors — and produced a Sigma data model, a workbook, and a row-level parity report against the live warehouse, all from a single structured prompt. No one rebuilt the dossier by hand, and the parity numbers are evidence rather than hope.

The patterns worth carrying into your next migration:

A first-pass conversion produces a working starting point and a documented punch list, not a hand-polished workbook. The polish loop is short, and you know exactly what to look at. That's the migration approach you can scale across an entire MicroStrategy project.

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