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Data Applications Guide
Learn about the latest data application development trends, technology, and best practices.
Challenges and Solutions for Developing AI apps
Developing AI applications requires a well-structured process. Learn about the development process, challenges you might face and solutions to overcoming them.
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What Are Native Apps?
Native apps are applications that run natively within an organization’s data platform. Learn here what are native apps and how they differ from connected apps.
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Developing Data-Intensive Applications
Learn about different kinds of data applications, their capabilities and the core components required to successfully build, deploy and maintain these apps.
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Connected Apps: Separating Customer Data and Application Code
In this article, we’ll explore what connected applications are, the advantages they offer, and how vendors can experience their benefits.
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SQL Development
SQL development tools and capabilities play a big role in data application development. However, developers should choose the tools in their toolbox wisely
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Is PySpark SQL Still Relevant?
Explore PySpark SQL for data extraction and analysis, and discover how Snowpark challenges its relevance and boosts efficiency for data engineers and developers
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Conquering DevOps for Data
DevOps has compelling benefits for software development, integrating once-siloed teams for faster innovation and improved product quality.
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Data Streams
Learn about data streams and data streaming, which is the process for ongoing transfer of data at a high speed.
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What is Parquet?
Parquet is an open source file format designed to handle complex data in large volumes. Learn more about Parquet, its benefits and differences with CSV.
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