As can be inferred from their name, foundation models are the foundation upon which developers build AI applications for tasks like language translation, text summarization, sentiment analysis and more. Models such as OpenAI's GPT, Google's Gemini, Meta’s Llama and Anthropic’s Claude, are pre-trained on vast amounts of text data and have the capability to understand and generate human-like language.

Now-a-days the data needs to be shared across different systems and platforms. One of the most common formats for this data exchange is JSON (JavaScript Object Notation). Understanding how to properly handle special characters in JSON is crucial for ensuring data integrity. In this blog, we’ll explore JSON escape and unescape, explain their importance. So let’s get started!

Data management is one of today's most critical business function. Without a solid grasp of what data management entails, organizations can't use data effectively. So, businesses look to ETL developers and data engineers for everything from data processing and management basics to regulatory compliance and the overall processes that help businesses use data to steer organizational decisions.

Is there a formula or approach to estimate how much you should spend on your quality engineering (QE) efforts? Our CEO, Steve Semelsberger, is frequently asked that question in discussions with other leaders. In part II of his quality engineering for CEOs series, Steve guides us through various scenarios and offers a unique approach to calculating your QE spend based on your specific business needs. Read the article now! If you missed part I, you can catch up on it here.

IT organizations serve the business. Their mission is to help optimize business operations to enhance performance across the enterprise and enable the organization to meet mission-critical goals. With the rapid pace of change, it’s critical to make smarter, faster decisions around business processes to generate a tangible, measurable impact.

Due to market pressures and disruptions, life sciences organizations need to reexamine their supply chain operations and how to more safely and efficiently bring products to market. However, deciding where to begin implementing change can be daunting. Here are some best practices for achieving streamlined end-to-end supply chain orchestration.

A longtime top innovation partner to Databricks, we continue to demonstrate the power of better analytics through automation.