A database schema, or DB schema, is an abstract design representing how your data is stored in a database. Database schemas can be visually represented using schema diagrams, such as the one below: A database schema diagram visually describes the following: Database schemas are at the heart of every scalable, high-performance database. They’re the blueprint that defines how a database stores and organizes data, its components’ relationships, and its response to queries.

LLM evaluation is the process of assessing the performance and capabilities of LLMs. This helps determine how well the model understands and generates language, ensuring that it meets the specific needs of applications. There are multiple ways to perform LLM evaluation, each with different advantages. In this blog post, we explain the role of LLM evaluation in AI lifecycles and the different types of LLM evaluation methods. In the end, we show a demo of a chatbot that was developed with crowdsourcing.

While controversial in functional programming, dependency injection can be a useful pattern in Elixir for managing dependencies and improving testability. In this, the first part of a two-part series, we will cover the basic concepts, core principles, and types of dependency injection. We'll explore its benefits in terms of modularity, testability, and maintainability. Then, we will look into a specific scenario where dependency injection can be beneficial, in this case, testing.

Ruby on Rails has long been celebrated for its ‘convention over configuration’ philosophy, simplifying web development for countless programmers. However, what if you’ve started with a lean Rails API-only application and now find yourself needing a front-end? This isn’t uncommon, especially with the rise of JavaScript frameworks and SPAs.

Imagine transforming raw business data into actionable insights with minimal effort. This is the value proposition of automated analytics, a form of data analytics fast becoming more accessible among modern business intelligence (BI) and analytics software solution vendors. Independent software vendors (ISVs) and enterprise organizations at the cusp of investing in analytics struggle with manual data processes that are time-consuming and prone to errors.

For flawless digital experiences, quality engineering (QE) is more than just a technical requirement—it’s the driving force behind innovation and success. Steve Semelsberger, Testlio’s CEO, will share his valuable insights in an engaging LinkedIn series designed to help fellow CEOs unlock the strategic benefits of QE. In this series, Steve will address your toughest questions and demystify the complexities of building a robust QE framework.