The retail industry is constantly evolving, and so is the way that businesses use BI tools. Retail business intelligence (BI) dashboards are now more important than ever, as they allow businesses to monitor their operations in a more comprehensive way. In this article, we explore the benefits of using BI dashboards in the retail industry, and discuss some of the ways in which they are transforming how it operates.

In the ever-evolving world of sports and entertainment, fan engagement has emerged as a critical factor in driving retention and long-term success. At the Ably Realtime Fan Engagement Summit in New York City, industry experts shared valuable insights into the relationship between fan engagement and retention, emphasizing the importance of creating compelling digital experiences and fostering genuine connections.

Deal broadens FP&A offerings for insightsoftware, delivering more value and confidence in financial transactions and reporting.

After Twitter moved from Ruby to Scala in 2009, the story was born that Ruby on Rails can’t scale. The story goes that it lacks robustness, is a memory hog, and lacks the concurrency features you need to grow an application. This has been the prevailing wisdom for over a decade. And then along came Shopify, showing that, as Lutke says, Ruby on Rails is a framework that can process billions of events per day and evidently does scale. Ruby on Rails is an excellent candidate for scaling.

AWS Lambda is a serverless compute service that enables you to run code without the need to provision or manage servers. This makes it an ideal choice for developers aiming to build scalable and efficient applications with minimal infrastructure overhead.

There are many ways AI can improve government case management processes. Examples include: AI capabilities often depend on a large language model (LLM), an advanced AI system that can understand, analyze, interpret, and generate human language. It uses deep learning techniques to predict and produce coherent text based on input prompts. A large language model trained on government agency data is capable of tasks like text extraction, translation, summarization, and conversational responses.

The life sciences industry is rapidly embracing artificial intelligence (AI) to automate complex processes, enhance efficiency, and improve outcomes. From drug development to patient care, AI-driven automation is transforming the landscape. Here are some of the top artificial intelligence use cases for process automation in the pharmaceutical industry.

Google regularly updates its developer policies to make sure Google Play is a safe and trustworthy platform for everyone. While this is unquestionably necessary and essential to protect users and their data, keeping up with the latest changes to ensure applications remain safe and compliant can feel a little overwhelming for developers.

In today’s world, innovation doesn’t happen in a vacuum; collaboration can help technological breakthroughs happen faster. The rise of AI, for example, will depend on the collaboration between data and development. We’re increasingly seeing software engineering workloads that are deeply intertwined with a strong data foundation.

Apps are the way to democratize AI: to make it accessible to everyone and streamline customers’ experiences with faster time to insights. According to a recent IDC survey, AI applications is currently the largest category of AI software, accounting for roughly one-half of the market’s overall revenue in 2023.