> ## Documentation Index > Fetch the complete documentation index at: https://docs.credibledata.com/llms.txt > Use this file to discover all available pages before exploring further. # Migrate from Omni > Convert your Omni shared model, topics, and views into governed Malloy semantic models Omni's model spans layers — a shared model every workbook inherits, per-workbook extensions, and branches in between. Credible reads across all of them, reconciles the definitions into one canonical set, and rebuilds your analytical domain as governed Malloy. ## What Credible Reads Your Omni model — `.view` files (dimensions and measures over tables) and `.topic` files (views joined into queryable units, with AI context and default filters), authored in YAML. The agent works from those files directly, inventorying workbook-level extensions too — logic often lives there, not just in the shared model. Connecting Omni's **MCP server** or **Model API** is optional and adds live validation (and can round-trip the model files). ## What Comes Across The everyday modeling carries over. Here's how the bigger pieces land — and where they get better: | In Omni | In Credible | | ---------------------------------------------------- | ------------------------------------------------------------------------------------------------ | | Shared model, topics, views | Malloy **sources** (base + joined); `import`/`export` curate exposure | | Dimensions & measures | Carried over, filtered and ratio measures included | | Field-level `sql:` with `${…}` refs | Resolved into Malloy expressions with explicit types | | Logic split across shared / branch / workbook layers | Reconciled into **one canonical definition per field** | | Model access controls | **Fine-grained access control in the model**, versioned and enforced on every surface | | `ai_context` and descriptions | `#(doc)` / `#(index)`, indexed by the [Context Engine](/how-to/analyzing/overview) | | Workbooks & dashboards | Rebuilt as [data apps](/how-to/analyzing/data-apps) or [notebooks](/how-to/analyzing/workspaces) | ## The Migration Flow Credible [reads](/how-to/migrating/overview) the shared model, topics, and workbook layers, translates views to sources and topics to joined sources, enriches with `#(doc)`/`#(index)` tags (seeded from `ai_context`), and — where you connect it — validates against Omni's query engine. ## What Credible Handles * **Logic split across layers** — the "real" definition of a field may live in an un-promoted workbook model, not the shared model. Credible reconciles the shared, branch, and workbook layers into one canonical Malloy definition, resolving promotion lineage as it goes. * **Field-level inline SQL** — Omni encourages `sql:` with `${…}` references and implicit typing. Credible resolves the references and makes Malloy types explicit. * **Removable default filters** belong in the query, not the model, so query-time defaults become part of a named view rather than a source-level filter. ## Before & After An Omni `.view` and `.topic`: ```yaml theme={"languages":{"custom":["/languages/motly.tmGrammar.json","/languages/malloy.tmGrammar.json"]}} # order_items.view views: - name: order_items sql_table_name: analytics.public.order_items dimensions: status: type: string sql: ${TABLE}.order_status value_tier: type: string sql: | CASE WHEN ${TABLE}.sale_price >= 100 THEN 'High' WHEN ${TABLE}.sale_price >= 25 THEN 'Medium' ELSE 'Low' END measures: total_revenue: description: Gross merchandise value across all order items sql: ${TABLE}.sale_price aggregate_type: sum completed_revenue: sql: ${TABLE}.sale_price aggregate_type: sum filters: { status: { is: Complete } } order_count: sql: ${TABLE}.order_id aggregate_type: count_distinct ``` ```malloy theme={"languages":{"custom":["/languages/motly.tmGrammar.json","/languages/malloy.tmGrammar.json"]}} source: order_items is conn.table('analytics.public.order_items') extend { primary_key: order_item_id join_one: users is conn.table('analytics.public.users') on user_id dimension: #(doc) Order item status #(index) status is order_status #(doc) Sale-price value bucket value_tier is pick 'High' when sale_price >= 100 pick 'Medium' when sale_price >= 25 else 'Low' measure: #(doc) Gross merchandise value across all order items # currency total_revenue is sum(sale_price) #(doc) Recognized revenue from completed items # currency completed_revenue is sum(sale_price) { where: status = 'Complete' } #(doc) Distinct orders order_count is count(order_id) #(doc) Average order value # currency avg_order_value is total_revenue / order_count view: #(doc) Revenue by month revenue_by_month is { group_by: created_at.month aggregate: total_revenue } } ``` The topic's `ai_context` becomes `#(doc)` intent on the source and its views; the same physical view joined multiple ways in a topic becomes multiple named joins in Malloy. **More than a reformat.** Definitions once split across shared, branch, and workbook layers collapse into one canonical, AI-discoverable model that composes into new questions. [See what you gain →](/how-to/migrating/overview#more-than-a-reformat) ## Next Steps The method behind every migration Package and publish your migrated model