Snowflake’s PARSE_DOCUMENT function revolutionizes how unstructured data, such as PDF files, is processed within the Snowflake ecosystem. Traditionally, this function is used within SQL to extract structured content from documents. However, I’ve taken this a step further, leveraging Snowpark to extend its capabilities and build a complete data extraction process. […]
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Streamlit, coupled with Snowpark, provides an excellent platform for creating interactive and user-friendly data applications. This blog highlights the significance of “Multi-Select Filtering with Streamlit and Snowflake”, demonstrating how multi-select filters can simplify data exploration by allowing users to apply multiple filters dynamically. While the example discussed is a basic […]
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In the evolving landscape of data sharing, Snowflake offers two primary methods: Direct Share and Private Listing. While both facilitate data sharing, they cater to different needs and scenarios. This blog focuses on Private Listing and Masking Policies for Cross-Region Data Sharing, comparing it with Direct Share and examining how […]
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Snowflake continues to revolutionize the data world with its modern data platform, scalability, performance, and flexibility. One of its standout features is External Functions, which enable you to call external services directly from Snowflake SQL. In today’s competitive market, understanding customer sentiment is key to enhancing customer experience. Retail companies […]
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In today’s data-driven world, organizations demand powerful tools to transform, analyze, and present their data seamlessly. Snowflake’s Snowpark is a game-changing feature that enables data engineers and analysts to write scalable data transformation workflows directly within Snowflake using Python, Java, or Scala. In this blog, we’ll explore Building an ETL […]
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In data-driven organizations, File Archival in Snowflake: A Snowpark-Powered Solution has become a game-changer. Handling feed files in data pipelines is a critical task for many organizations. These files, often stored in stages such as Amazon S3 or Snowflake internal stages, are the backbone of data ingestion workflows. Once processed, these […]
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