Read Time:2 Minute, 59 Second Aggregation Policy: Let’s consider a scenario where Sachin Mittal, “Cloudyard,” has a central data repository stored in Snowflake. This repository contains detailed transaction records of customer orders across various stores. Sachin needs to share summarized transaction data with Vishal Kaushal (partner) regularly. However, Vishal is known for his inquisitive nature, and Sachin wants to enable him to perform analyses on the data while ensuring the privacy of individual customer transactions. Hence, Sachin must strike a balance between: Transparency and Collabora ..read more

Read Time:2 Minute, 59 Second Consider a Scenario where the Client manages a large Customer-Invoice details with constantly changing Invoice data. The company uses Snowflake to manage Invoice data in a table named S_INVOICE. This table receives daily loads(history + Current) to reflect changes in customer and invoice partial payment. The goal is to efficiently merge this dynamic data into a target table named S_INVOICE_TARGET while performing Insert operations using stored procedure. Dynamic Merge Procedure: The provided DYNAMIC_MERGE procedure can be directly utilized for this use case. Here ..read more

Read Time:1 Minute, 54 Second Imagine you’re responsible for overseeing the usage of Snowflake credits across different roles within your organization. You need a streamlined way to monitor credit consumption by role over specific periods to identify any anomalies or trends. This stored procedure, SendEmailWithCreditDetails, automates the process of notifying users about Snowflake credit usage within a specified timeframe. Consider you are managing a bustling Snowflake environment with multiple warehouses and roles. Keeping track of credit consumption across various departments and projects ca ..read more

Read Time:1 Minute, 51 Second In a dynamic database environment, users often leverage session-specific temporary tables to perform ad-hoc analyses, data manipulations, or intermediate computations. However, managing and identifying these temporary tables across sessions can pose challenges, especially when coexisting with permanent tables of the same name. Ensuring efficient utilization of temporary tables while preserving data integrity and performance becomes paramount. To ensure proper data management and avoid confusion, you want a way to identify the types of tables (permanent or temporar ..read more

Read Time:2 Minute, 13 Second Consider a scenario, you are part of data engineering team at a retail company. you’re tasked with leveraging customer behavior and preferences to improve engagement and marketing strategies. However, the volume of daily transaction data poses challenges in effectively segmenting customers and optimizing engagement. Traditional segmentation methods fall short in scalability and real-time insights. This blog post explores how Snowpark, a powerful tool for data processing within Snowflake, can be used to perform RFM segmentation and unlock actionable customer insigh ..read more

Read Time:3 Minute, 17 Second In the world of data warehousing, keeping track of changes to your Snowflake warehouse size is crucial. Unexpected adjustments can impact performance and potentially incur additional costs. This blog post introduces a solution for automated warehouse size change monitoring and email alerts using Snowflake Streams and Tasks. Imagine you’re a data analyst managing a busy Snowflake account. You rely on a designated warehouse to handle your data processing needs. However, you’re concerned about unauthorized modifications to the warehouse size, which could disrupt your ..read more

Read Time:1 Minute, 32 Second In this blog post, we will explore how to leverage Snowpark and Streamlit to build an interactive book exploration application. Snowpark is a feature in Snowflake that allows developers to write code in their preferred programming language, and Streamlit is a Python library for creating web applications with minimal effort. The combination of Snowpark and Streamlit provides a powerful platform for data exploration and visualization. Imagine this scenario: You’re an avid reader, yearning to delve into a new world. With this Streamlit application, you can: Browse a ..read more

Read Time:2 Minute, 18 Second In the ever-evolving world of data management, streamlining processes and ensuring data freshness are crucial. Snowflake, a cloud-based data platform, provides a revolutionary feature known as Dynamic Tables. This blog post showcases a novel approach combining Snowflake’s Event Logging and Dynamic Tables to automate the creation and population of dynamic tables based on Copy operations. Imagine you manage a data warehouse where numerous tables are populated through regular copy operations. Manually creating and updating dynamic tables for these newly added or modi ..read more

Read Time:1 Minute, 42 Second In this blog post, we’ll delve into a practical example that showcases the prowess of Snowpark by processing customer invoice data from a CSV file and handling credit card details from a JSON source. For instance, Consider a scenario where an organization needs to streamline the processing of customer invoice data and credit card details. The data, originating from different formats and sources, requires consolidation into Snowflake tables for comprehensive analysis. Therefore, Snowpark, with its capabilities in simplifying complex data workflows, becomes instrume ..read more

Read Time:1 Minute, 27 Second In this blog post, we will delve into a specific scenario concerning the suspension of Child tasks in Snowflake. A colleague recently presented a challenge where he sought to automate the suspension of particular CHILD tasks. In his current setup, there were over 20+ child task intricately connected to a parent TASK. While Snowflake provides a command to enable all child tasks at once (SELECT SYSTEM$TASK_DEPENDENTS_ENABLE('<<PARENT TASK>>')), there isn’t a corresponding command to suspend all child tasks. Consequently, manual intervention becomes neces ..read more