Understanding the fundamental concepts behind Rootstack Insight will help you make the most of its AI-powered capabilities. This glossary summarizes the main technical terms you’ll encounter when connecting data sources, generating insights, and managing information within your organization.
- MCP (Multi-Connector Pipeline): A framework that allows Rootstack Insight to connect with multiple data sources (SQL, NoSQL, APIs, CRMs) and analyze them in a single place.
- Data Source: The origin of the information. It can be a relational database (such as PostgreSQL or MySQL), a CSV file, or a business API.
- SQL (Structured Query Language): A language used to query and manipulate structured data in relational databases.
- NoSQL: A non-relational type of database that stores information in flexible structures (documents, graphs, key-value pairs). Example: MongoDB.
- RAG (Retrieval-Augmented Generation): An AI technique that combines real-time information retrieval with text generation, producing more accurate answers grounded in actual data.
- Fine-Tuning: Additional training applied to an AI model to specialize it in a specific domain or format, such as financial reports or medical diagnostics.
- Natural Language Query: A Rootstack Insight feature that allows users to query data using natural language (e.g., “How were sales in October?”) without writing SQL.
- AI Assistant: The conversational engine that interprets questions, generates analysis, and presents insights based on the connected data.
- Data Governance: A set of policies that ensure data is secure, consistent, and accessible only to authorized users within the organization.