As Snowflake's capabilities expand, staying updated with its latest features and functionalities can be overwhelming. The platform's rapid development gave rise to advanced tools like Snowpark and the Native App Framework, which are crucial for optimizing data operations but may seem complex to navigate.
In this essential book, author Muhammad Fasih Ullah offers a detailed guide to understanding these sophisticated tools, ensuring you can leverage the full potential of Snowflake for data processing, application development, and deploying machine learning models at scale. You'll gain actionable insights and structured examples to transform your understanding and skills in handling advanced data scenarios within Snowflake. By the end of this book, you will:
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Muhammad Fasih Ullah is the head of data and analytics for NordicFeel Group, the leading Nordic beauty ecommerce group. His current work focuses on developing resilient and high-functioning data organizations that manage scalable data and analytics needs. He has helped teams design and build scalable data layers that process millions of rows daily and prepare data for analytical use across multiple brands and markets.
As a four-time Snowflake Data Superhero, the platform's highest community recognition, Fasih has leveraged his in-depth knowledge of Snowflake to help save his organization and clients hundreds of thousands of dollars in data warehousing costs while dramatically improving performance and capabilities. With over eight years of experience in data, analytics, data architecture, and AI, Fasih has built his expertise across diverse industries at companies including Voi Technology and Afiniti.
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Taschenbuch. Zustand: Neu. Advanced Snowflake | Processing Data, Developing Applications, and Deploying ML Models at Scale | Muhammad Ullah | Taschenbuch | Einband - fest (Hardcover) | Englisch | 2025 | O'Reilly Media | EAN 9781098170219 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu. Artikel-Nr. 134111965
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