Systems | Development | Analytics | API | Testing

In this blog series, I am exploring the “sliding doors”, or divergent paths, for creating value with data across different use cases, practices, and strategies. In this post, I want to discuss how to generate value with Data Products. As I reviewed in my last blog, grabbing the door to the better path for managing your data isn’t just about solving your particular use case: it’s ultimately about delivering value for your business.

Headline: The transition to Codemagic made our CI builds faster and more reliable and positively impacted the experience of contributors contributing to our open-source project, Tuist. Thanks to Codemagic’s support, we can bring new free goods to the Swift community and the ecosystem of app developers.

Last year was significant for us, so let's reflect briefly. As one of the key milestones, we released Xray Enterprise - a comprehensive solution for test management challenges, blending powerful features with user-friendly functionality. It is especially beneficial for larger companies with high scale and complexity of the development operations. Here are other noteworthy numbers/metrics.

Intelligent automation happens when robotic process automation (RPA) meets artificial intelligence (AI), bringing simple actions and cognitive tasks together for lightning-fast processing. Intelligent automation in insurance is a powerful tool that reduces both human error and the need to perform repetitive tasks manually. Imagine AI extracting data from an invoice then a bot entering that data into a software program.

Business process management solutions often tout their analysis and optimization capabilities, but few provide the full set of tools needed to build a process, measure its performance, and identify and implement improvements. And when you’re looking for information on how to optimize a process, it’s easy to quickly get lost in the information-overload about the best methodologies and tools. That’s likely because the answer to process improvement isn’t straightforward.

According to a study by Statista, the cloud storage market was valued at $90.17 billion in 2022 and will reach a value of $472.47 billion by 2030. These figures indicate a growing shift toward cloud computing and data storage solutions. A typical scenario in modern data management involves data transfer from cloud storage to cloud-based computing platforms. Amazon’s Simple Storage Service (S3) is among the go-to options for the former, and businesses trust Snowflake for the latter.

Considering BigQuery vs. Redshift for your data warehousing needs? This guide is for you. Both BigQuery and Redshift stand as leading cloud data warehouse solutions each offering a multitude of features catering to multiple use cases. Google’s BigQuery offers seamless scalability and performance within its cloud platform, while Amazon’s Redshift provides great parallel processing and tuning options.

In this article, we present some best practices and key concepts for using Confluent Schema Registry.

Managed File Transfer (MFT) stands as a cornerstone in the secure and efficient exchange of data across organizations, modernizing traditional methods and ensuring compliance with global data protection standards. Here are the five key takeaways from our What is MFT article.

Javascript Object Notation (JSON) is becoming the standard log format, with most modern applications and services taking advantage of its flexibility for their logging needs. However, the great flexibility for developers quickly turns into complexity for the DevOps and Data Engineers responsible for ingesting and processing the logs. That’s why we developed JSON FLEX: a scalable analytics solution for complex, nested JSON data.