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Latest Blogs

iOS Data Persistence: A Guide for Swift Developers

The term ‘data persistence’ refers to data that remains available, even when the program that created it is idle, sleeping or unable to open. In many cases, our iOS apps need to provide support around the clock, so we need our data to be ‘always on’ – even when the apps themselves are not.

DoD AI: Using Artificial Intelligence to Improve Military Operations

With all the recent discussion about the use of artificial intelligence (AI) and large language models (LLMS) like ChatGPT, you may think that AI is a new phenomenon. But in fact, the US Department of Defense (DoD) has been investing in AI for more than 60 years.

Preventing Hallucinations in AI Apps with Human-in-the-Loop Testing

Artificial intelligence (AI) apps are becoming increasingly crucial for individual customers and businesses alike. These apps bring many benefits, such as task automation, efficient analysis of large data sets, and data-informed decision-making, making AI-powered applications highly valuable. As a result, DevOps teams working on AI apps can’t afford poor performance.

Top 10 Reasons to Acquire a Product Information Management Solution (PIM or PXM)

Implementing a PIM or PXM* solution will bring numerous benefits to your organization, in terms of improving efficiency, increasing sales and conversions, reducing returns, and promoting customer loyalty through more accurate, more complete, and more engaging product content. Here we explore these benefits in more detail.

What is Data Mapping?

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Mastering the API Lifecycle: Essential Stages & Proven Strategies for Success

What determines the success of an API? A significant part lies in mastering the API lifecycle—from planning to retiring, every step impacts your API’s performance and adoption. The API lifecycle involves several critical stages—planning, designing, developing, deploying, consuming, monitoring, and retiring. Each stage dictates the successful implementation of APIs, including governance models, transparency, and security being crucial throughout.

Automated Insurance Claims Processing: How Does It Work?

With more emerging players entering the insurance market and insurance companies recognizing the importance of the digital experience, consumer demands for a connected insurance experience have grown to new heights. For insurance customers, the claims process is a critical moment of truth, making it essential that insurers deliver a hassle-free, seamless experience with faster claims processing and excellent customer service.

5 Best Practices for Streaming Analytics with S3 in the AWS Cloud

Streaming analytics is an invaluable capability for organizations seeking to extract real-time insights from the log data they continuously generate through applications and cloud services. To help our community get started with streaming analytics on AWS, we published a piece last year called An Overview of Streaming Analytics in AWS for Logging Applications, where we covered all the basics.