If you think workflow orchestration sounds like tech jargon, check out this simple explanation and consider practical advice for how to apply it to your business processes. Let’s start with the basics: what is workflow orchestration? Put simply, workflow orchestration is the end-to-end management of people, digital workers, systems, and data in a process.

except Exception as e is a construct in Python used for exception handling. It allows you to catch exceptions that occur during the execution of a block of code by using a try block to wrap the code that might raise an exception, and an except block to catch and handle the exception. The Exception part specifies that any exception of this type or its subclasses should be caught, and the as e part assigns the caught exception to a variable e, which you can then use to access details about the exception.

When two different software applications want to join forces by sharing information, it’s not always a perfect union. Different database structures, programming languages, and network protocols tend to complicate the process. When reading about the various API technologies, you’ve probably come across two terms, OData vs REST, and wondered, “what’s the difference?” It turns out that OData vs. REST are two closely related concepts.

The 2024 Gartner Magic Quadrant for Analytics and BI Platforms just dropped, and we’re thrilled to announce that ThoughtSpot was recognized as a Leader in the report. But, we aren’t the only ones finding ourselves in a new position this year. The analytics and BI space has undergone some of the most significant shifts in over a decade, an aftershock of generative AI.

In this post, we demonstrate how a robust and scalable generative artificial intelligence (GenAI) chatbot is built using Amazon Bedrock and Confluent Cloud. We walk through the architecture and implementation of this generative AI chatbot, and see how it uses Confluent's real-time event streaming capabilities along with Amazon's infrastructure to continually stay up to date with the latest advances from the AI landscape.

If you’re one of the cool kids building AI-based products you’ve probably heard of — or are already doing — RAG. If you’re not, let me tell you what RAG is before telling you one weird fact about it. “Retrieval-Augmented Generation” is nothing more than a fancy way of saying “including helpful information in your LLM prompt.” Still, there are many ways to do it and many questions to answer when building a RAG pipeline.

When creating an ODBC driver, it is essential to convert data from the data source into a relational format. This is necessary because ODBC and SQL require and operate on data that is organized with a fixed schema and returned in a tabular structure.