The banking and finance business industry is going through a huge change right now. Traditional banking models are changing into flexible, digital-first experiences because of fast technological progress, changing customer needs, and a complicated legal environment.

How versatile is the Ghost Inspector API? We’re so glad you asked! With our API, you can easily integrate Ghost Inspector into your current software testing processes and take full control over your automated testing workflow. Whether you want to execute tests, grab results, manage suites and folders, or pull historical data, the API lets you do it all without relying on the UI.

Jetpack Compose (sometimes mistakenly called Android Compose) is a powerful new UI toolkit for Android that embodies the principle of ‘Code As UI’, offering aa simpler and faster way to build native android UI using a declarative approach. Of all the UI components in Jetpack Compose, buttons have a special place, as these are the cornerstone of our user interface. They allow the user to take actions, submit forms, and navigate around the app smoothly.

Over 4000 engineering teams are building mobile apps and related projects using Bitrise. One trend we’ve observed is the increasing use of monorepos by some organizations. In this blog, I’ll show you an example setup that demonstrates the current best practice for using Bitrise CI with monorepos. You can use this as a reference for your own monorepo to achieve a CI setup that prioritizes efficiency, autonomy of project teams, and effective governance.

The e-commerce landscape is passionately competitive. Today is a prime example as consumers rush to secure the perfect Valentine’s Day gift before it's slim pickings on the chocolates and the sad looking roses! How do you meet the demand and keep those last minute bouquet hunters happy?

Artificial intelligence has become a driving force behind modern innovation, helping businesses across all industries optimize processes and generate income. But how do you monetize AI usage effectively? Whether you’re integrating AI features into an existing plan or launching entirely new AI products, choosing the right approach can unlock steady revenue growth and strengthen competitive advantage.

APIs power complex and modern applications and in doing so they’ve also become a challenge to observe, monitor, and analyze. Even the apps we rely on daily consists of numerous services, each glued together by dedicated APIs that interact with one another in intricate ways. In today’s market, you have to make sure that API complexity doesn’t hurt the visibility you need to possess into your product.

How many times have you struggled to find the right dataset for an ETL job? Have you wasted hours verifying column definitions, data sources, or lineage before using the data? If so, you're not alone. For data analysts working with ETL pipelines and data integration, one of the biggest challenges is ensuring data discoverability, quality, and governance. A data catalog solves these challenges by providing a centralized repository of metadata, helping teams easily find, understand, and manage data assets.

Have you ever struggled with duplicate records, inconsistent formats, or redundant data in your ETL workflows? If so, the root cause may be a lack of data normalization. Poorly structured data leads to data quality issues, inefficient storage, and slow query performance. In ETL processes, normalizing data ensures accuracy, consistency, and streamlined processing, making it easier to integrate and analyze.