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.

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.

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.

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.

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

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

Conquering DevOps for Data

DevOps has compelling benefits for software development, integrating once-siloed teams for faster innovation and improved product quality.

Data Streams

Learn about data streams and data streaming, which is the process for ongoing transfer of data at a high speed.

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.