Faith is beautifully defined by Alma as a belief in something which is not seen but which is true. It is also defined as a seed which grows, and takes root because of truth and faith. However I learned something new about faith tonight. I was listening to Glenn Beck give a fireside to our the youth of our stake, and while i was listening I had one of those eureka moments. And this is it: "Faith is a degree of enthusiasm in something." To have faith in something is to be enthusiastic about it. To believe in something, one is moved to act and direct decisions in accordance to faith in a principle. Enthusiasm is both the affect and the effect. So faith is not a passive principle, it is one which requires our activity, else it is not. Faith without works is dead, Faith without enthusasm will never have works.
⚡ TL;DR I helped built a tool that lets you query Tableau’s semantic layer using natural language and AI. By integrating a LangChain agent with Tableau’s VizQL Data Service (VDS), we can repurpose Tableau’s trusted data model for conversational analytics . This means you can ask questions in plain English and get answers backed by the same definitions and security that your Tableau dashboards use. In this post, I’ll introduce this open-source agentic tool ( tableau_langchain ), why it’s transformative for analytics, and how it works under the hood. Why Connect LangChain Agents to Tableau? As a user of Tableau, I’ve seen how powerful Tableau’s semantic layer is. It encapsulates our organization’s business logic: things like predefined metrics, calculations, data relationships, and even row-level security rules. Traditionally, that semantic layer is only accessible through Tableau’s interface – you drag and drop fields to build a viz, and Tableau generates the query for you. Rece...
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