Monthly Archives: January 2025

Effortless Automation: Scheduling Snowflake Pipelines

How to Schedule a Pipeline in Snowflake Snowflake offers an effective method for automating and scheduling data pipelines through the use of Tasks. These tasks enable the scheduling of SQL…

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Snowflake Meets AWS S3: A Complete Walkthrough for Data Loading

This blog provides a step-by-step guide to setting up a Snowflake environment for loading data from AWS S3. Prerequisites: Snowflake Account-> Ensure you have access to a Snowflake account. AWS…

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Backup and Restore SQL Server Databases Using PowerShell

Introduction:   The document outlines the procedures for performing backup and restoration of SQL Server databases using PowerShell. These processes ensure data safety, recovery readiness, and business continuity. Proper execution…

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SQL Server Database and Login migration

Introduction; The Data Migration Assistant (DMA) tool is a Microsoft utility designed to simplify the migration of databases from older SQL Server versions or on-premises environments to newer versions or…

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Step-by-Step Troubleshooting for SQL Server CPU Usage Spike

Introduction: The user is experiencing a high CPU usage spike on their SQL Server instance, leading to performance degradation. The objective is to identify the root cause of the CPU…

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Step-by-Step Troubleshooting for SQL Server Memory Usage Spike

Introduction: The user has reported a sudden memory usage spike on their SQL Server instance, resulting in degraded performance. You need to troubleshoot and identify the root cause of the…

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Troubleshooting Docker Container Issues

Introduction/Issue:While working with Docker containers in our environment, we encountered an issue where certain containers were failing to start, throwing cryptic error messages. This disrupted the workflow and required immediate…

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Scaling Applications in Kubernetes on GCP

Introduction/Issue:During a period of increased traffic, our application faced performance bottlenecks due to insufficient resources. Manual intervention for scaling was inefficient, so we decided to implement auto-scaling for our Kubernetes…

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Query to get Shipping and Inventory Material Transactions in fusion.

SELECT dha.source_order_number, dha.order_number, dfla.status_code, dfla.source_line_number   FROM  fusion.doo_headers_all dha, fusion.doo_fulfill_lines_all dfla, fusion.wsh_delivery_assignments wda, fusion.wsh_new_deliveries wnd, fusion.wsh_delivery_details wdd, fusion.inv_material_txns imt  WHERE dha.header_id=dfla.header_id    AND dfla.fulfill_line_id=wdd.source_shipment_id    AND wdd.delivery_detail_id=wda.delivery_detail_id    AND wda.delivery_id=wnd.delivery_id(+)…

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Query to get Inventory on hand quantity details in fusion.

SELECT esi.inventory_item_id, esi.item_number, esi.organization_id, inv.organization_code, esi.enabled_flag, esi.end_date_active, ohq.transaction_quantity onhand_qty   FROM fusion.egp_system_items_b esi, fusion.inv_org_parameters inv, fusion.inv_onhand_quantities_detail ohq  WHERE  inv.organization_id=esi.organization_id    AND inv.organization_id=ohq.organization_id    AND esi.inventory_item_id=ohq.inventory_item_id

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