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This enables you to create custom views, reports, and datasets without modifying the main dataset structure.\n\n\u003Cbr>\n\n## 📝 Configuration Guide\n\nFollow the steps below to create the **Custom Queries** module.\n\n\u003Cbr>\n\n### 🔧 Module Configuration\n\nGo to the **Solutions** section in the menu > Click **Create Data Solutions**.\n\n\u003Cbr>\u003Cbr>\n\n![](https://a.storyblok.com/f/296300/1920x911/2ab844ee5c/step1.png)\n\n\u003Cbr>\u003Cbr>\n\nFrom the list of available integrations, select **Custom Queries**.\n\n\u003Cbr>\u003Cbr>\n\n![](https://a.storyblok.com/f/296300/1920x911/c7edac38fb/step2.png)\n\n\u003Cbr>\u003Cbr>\n\nEnter the process name, e.g., `\"Example Custom Query\"`.\n\n\u003Cbr>\u003Cbr>\n\n![](https://a.storyblok.com/f/296300/1920x911/b048877d9f/step3.png)\n\n\u003Cbr>\u003Cbr>\n\nEnter the SQL query content in the **Query content** field.  \nYou can use the full BigQuery syntax and the `{{RUN_DATE}}` variable, which will automatically be replaced with the process execution date.\n\nThe `{{RUN_DATE}}` variable follows the `YYYYMMDD` format and corresponds to the scheduled task execution date or the manual run date.\n\n\u003Cbr>\u003Cbr>\n\n### 💾 Saving Results\n\nTo save the query results in BigQuery, enable the **Save Query results** switch.\n\n\u003Cbr>\u003Cbr>\n\n![](https://a.storyblok.com/f/296300/1920x911/0937a81a8a/step4.png)\n\n\u003Cbr>\u003Cbr>\n\nIn the **Table settings** section, you can define save parameters:\n\n\u003Cbr>\n\n**Table prefix** – the prefix for table names where the results will be stored (e.g., `total_spend`).  \n\n\u003Cbr>\n\n![](https://a.storyblok.com/f/296300/1920x911/aec0d09024/step5.png)\n\n\u003Cbr>\n\n**Write disposition** – the method of writing data:\n  - `Overwrite if table/partition exists` – overwrites the existing table or partition.  \n  - `Append to table/partition` – appends data to the existing table.  \n  - `Write only if table/partition is empty` – writes data only if the table is empty.\n\n\u003Cbr>\n\n![](https://a.storyblok.com/f/296300/1920x911/d0de747ed5/step6.png)\n\n\u003Cbr>\u003Cbr>\n\n### 🧱 Data Partitioning\n\nIf you want the results to be saved in a partitioned table, enable the **Partitioned** option.\n\nThen choose the partitioning method:\n- **Ingestion time** – partitions by the time data was ingested.\n- **Custom field** – partitions by a selected field from the query (e.g., `date`, `event_date`, etc.).\n\nThis allows you to easily manage large datasets and speed up processing in BigQuery.\n\n\u003Cbr>\u003Cbr>\n![](https://a.storyblok.com/f/296300/1920x911/06906f468b/step7.png)\n\n\u003Cbr>\u003Cbr>\n\n### 🧪 Query Testing\n\nBefore saving the configuration, you can perform a test execution by clicking **Test Query**.  \nThis allows you to verify the syntax and data correctness before adding the task to the schedule.\n\n\u003Cbr>\u003Cbr>\n\n![](https://a.storyblok.com/f/296300/1920x911/742b6a2828/step8.png)\n\n\n\u003Cbr>\u003Cbr>\n\n✅ **Done!** The **Custom Query** module has appeared on the **Solutions** list and is now ready to use.\n\n> Remember that the table will appear only after the module is run in the Workflow!\n\n\u003Cbr>\n\n### ⏳ Execution and Scheduling\n\nTo run the module and set up its schedule, you need to configure a **Workflow**.  \nYou can read more about it [here](/docs/workflow).\n\n\u003Cbr>\n","markdown-blok","docs-page",[],"custom-queries","witcloud/docs/collect/custom-queries",-90,[],211372208359902,"bad20122-e7eb-4efe-ba67-41ae4453fb94","2025-10-21T09:59:00.081Z",[],[],[],{"age":236,"cache-control":187,"connection":188,"content-encoding":189,"content-type":190,"date":237,"etag":238,"referrer-policy":193,"sb-be-version":194,"server":195,"transfer-encoding":196,"vary":197,"via":198,"x-amz-cf-id":239,"x-amz-cf-pop":200,"x-cache":201,"x-content-type-options":202,"x-frame-options":203,"x-permitted-cross-domain-policies":30,"x-request-id":240,"x-runtime":241,"x-xss-protection":206},"668","Fri, 21 Aug 2026 13:20:20 GMT","W/\"ce190f76833495a1cd3f5314c40df540\"","7WELrXcCaGEgLpjfvIWzn6d9YvNctaPSWzWEnZ0XS57cLj1Y199YcQ==","337ecc0b-5507-414f-af6d-018cdc58db5c","0.021171",{"data":243,"body":245,"excerpt":-1,"toc":847},{"title":244,"description":19},"Custom Queries Integration",{"type":246,"children":247},"root",[248,256,260,264,271,284,287,293,304,307,314,333,342,350,359,369,378,385,394,407,416,423,432,457,476,485,491,503,512,519,528,540,543,561,564,571,574,584,622,625,632,641,647,659,664,703,708,721,730,736,752,761,768,777,802,811,814,820,844],{"type":249,"tag":250,"props":251,"children":253},"element","h1",{"id":252},"custom-queries-integration",[254],{"type":255,"value":244},"text",{"type":249,"tag":257,"props":258,"children":259},"hr",{},[],{"type":249,"tag":261,"props":262,"children":263},"br",{},[],{"type":249,"tag":265,"props":266,"children":268},"h2",{"id":267},"introduction",[269],{"type":255,"value":270},"📢 Introduction",{"type":249,"tag":272,"props":273,"children":274},"p",{},[275,277,282],{"type":255,"value":276},"The ",{"type":249,"tag":278,"props":279,"children":280},"strong",{},[281],{"type":255,"value":210},{"type":255,"value":283}," module allows you to create, run, and automate your own SQL queries within the data stored in your data warehouse — both data collected by WitCloud and data from external sources. 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