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AI-201 · Question #198

AI-201 Question #198: Real Exam Question with Answer & Explanation

The correct answer is C: Data preparation Involves loading, chunking, vectorizing, and storing content in a search-. Why is "Loading, Chunking, Vectorizing, and Storing" the correct answer? Agentforce AI-powered search and retriever indexing requires data to be structured and optimized for retrieval. The Data Cloud preparation process involves: Key Steps in the Data Preparation Process for Agen

AI Features for Service (e.g., Einstein Bots, Next Best Action)

Question

In the context of retriever and search indexes, what best describes the data preparation process in Data Cloud?

Options

  • AData preparation focuses on real-time data ingestion and dynamic indexing to generate dynamic
  • BData preparation entails aggregating, normalizing, and encoding structured datasets to ensure
  • CData preparation Involves loading, chunking, vectorizing, and storing content in a search-

Explanation

Why is "Loading, Chunking, Vectorizing, and Storing" the correct answer? Agentforce AI-powered search and retriever indexing requires data to be structured and optimized for retrieval. The Data Cloud preparation process involves: Key Steps in the Data Preparation Process for Agentforce: Raw text from documents, emails, chat transcripts, and Knowledge articles is loaded into Data Chunking (Breaking Text into Small Parts) AI divides long-form text into retrievable chunks to improve response accuracy. Example: A 1000-word article might be split into multiple indexed paragraphs. Vectorization (Transforming Text for AI Retrieval) Each text chunk is converted into numerical vector embeddings. This enables faster AI-powered searches based on semantic meaning, not just keywords. Storing in a Vector Database The processed data is stored in a search-optimized vector format. Agentforce AI retrievers use this data to find relevant responses quickly.

Topics

#Data Preparation#Vectorization#Search Indexes#Salesforce Data Cloud

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