{"id":9144741363986,"title":"BigQuery Watch Rows Integration","handle":"bigquery-watch-rows-integration","description":"\u003cbody\u003e\n\n\n\u003cmeta charset=\"UTF-8\"\u003e\n\u003cmeta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\"\u003e\n\u003ctitle\u003eBigQuery Watch Rows Integration\u003c\/title\u003e\n\n\n \u003ch1\u003eBigQuery Watch Rows Integration\u003c\/h1\u003e\n \u003cp\u003e\n The API endpoint for \u003cstrong\u003eBigQuery Watch Rows Integration\u003c\/strong\u003e provides users with the ability to monitor and react to changes in data within Google BigQuery tables in real-time. With this API, developers have a powerful tool for creating applications that can respond immediately to modifications in BigQuery datasets, such as new row additions, updates, or deletions.\n \u003c\/p\u003e\n \u003ch2\u003eApplications and Use Cases\u003c\/h2\u003e\n \u003cp\u003e\n This API can be utilized to handle various scenarios across different domains. For example, in the e-commerce sector, when a sales transaction is completed, it may trigger an inventory update; using BigQuery Watch Rows, a related warehouse management system can be informed instantly of the change, thereby keeping the inventory levels accurate. In the finance sector, real-time monitoring of transactional tables can assist in the detection of fraudulent activity by triggering alerts when certain patterns of data changes are identified.\n \u003c\/p\u003e\n \u003cp\u003e\n IoT (Internet of Things) applications stand to benefit significantly from this API, as it can be used to ingest and analyze high volumes of sensor data that constantly change\u003c\/p\u003e\n\u003c\/body\u003e","published_at":"2024-03-13T01:25:55-05:00","created_at":"2024-03-13T01:25:56-05:00","vendor":"BigQuery","type":"Integration","tags":[],"price":0,"price_min":0,"price_max":0,"available":true,"price_varies":false,"compare_at_price":null,"compare_at_price_min":0,"compare_at_price_max":0,"compare_at_price_varies":false,"variants":[{"id":48259906240786,"title":"Default Title","option1":"Default Title","option2":null,"option3":null,"sku":"","requires_shipping":true,"taxable":true,"featured_image":null,"available":true,"name":"BigQuery Watch Rows Integration","public_title":null,"options":["Default Title"],"price":0,"weight":0,"compare_at_price":null,"inventory_management":null,"barcode":null,"requires_selling_plan":false,"selling_plan_allocations":[]}],"images":["\/\/consultantsinabox.com\/cdn\/shop\/products\/1e5dac61be6d9577c2d015c2f29160e0_71eb0069-3cab-4bb3-a49b-dfede82bc0bb.png?v=1710311156"],"featured_image":"\/\/consultantsinabox.com\/cdn\/shop\/products\/1e5dac61be6d9577c2d015c2f29160e0_71eb0069-3cab-4bb3-a49b-dfede82bc0bb.png?v=1710311156","options":["Title"],"media":[{"alt":"BigQuery Logo","id":37928195457298,"position":1,"preview_image":{"aspect_ratio":2.977,"height":1760,"width":5240,"src":"\/\/consultantsinabox.com\/cdn\/shop\/products\/1e5dac61be6d9577c2d015c2f29160e0_71eb0069-3cab-4bb3-a49b-dfede82bc0bb.png?v=1710311156"},"aspect_ratio":2.977,"height":1760,"media_type":"image","src":"\/\/consultantsinabox.com\/cdn\/shop\/products\/1e5dac61be6d9577c2d015c2f29160e0_71eb0069-3cab-4bb3-a49b-dfede82bc0bb.png?v=1710311156","width":5240}],"requires_selling_plan":false,"selling_plan_groups":[],"content":"\u003cbody\u003e\n\n\n\u003cmeta charset=\"UTF-8\"\u003e\n\u003cmeta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\"\u003e\n\u003ctitle\u003eBigQuery Watch Rows Integration\u003c\/title\u003e\n\n\n \u003ch1\u003eBigQuery Watch Rows Integration\u003c\/h1\u003e\n \u003cp\u003e\n The API endpoint for \u003cstrong\u003eBigQuery Watch Rows Integration\u003c\/strong\u003e provides users with the ability to monitor and react to changes in data within Google BigQuery tables in real-time. With this API, developers have a powerful tool for creating applications that can respond immediately to modifications in BigQuery datasets, such as new row additions, updates, or deletions.\n \u003c\/p\u003e\n \u003ch2\u003eApplications and Use Cases\u003c\/h2\u003e\n \u003cp\u003e\n This API can be utilized to handle various scenarios across different domains. For example, in the e-commerce sector, when a sales transaction is completed, it may trigger an inventory update; using BigQuery Watch Rows, a related warehouse management system can be informed instantly of the change, thereby keeping the inventory levels accurate. In the finance sector, real-time monitoring of transactional tables can assist in the detection of fraudulent activity by triggering alerts when certain patterns of data changes are identified.\n \u003c\/p\u003e\n \u003cp\u003e\n IoT (Internet of Things) applications stand to benefit significantly from this API, as it can be used to ingest and analyze high volumes of sensor data that constantly change\u003c\/p\u003e\n\u003c\/body\u003e"}