Start For Free Contact Us

Data Applications Guide

Learn about the latest data application development trends, technology, and best practices.

Decoupling Customer Data from Application Code with Hybrid App Development

In a hybrid app development model the application code is separated from the data, allowing customers to maintain control of their data and eliminating data silos.

Conquering DevOps for Data

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

What is Parquet?

Parquet is an open-source file format for columnar storage of large and complex datasets, known for its high-performance data compression and encoding support.

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.

Best Practices for Building Database Applications

In this article, we’ll explore best practices for building database applications and highlight the latest cloud-based technologies for modern database applications.

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.

Spark Examples

What use cases are a good fit for the Spark framework? Here are a few scenarios where using Spark makes sense:

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