customers receive the information and promotions that are most interesting and relevant to them.
What it means for teams: Teams can use predictive analytics to forecast demand, identify trends, make proactive decisions, and inform business strategies.
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Secure data retrieval
In generative AI, secure data retrieval means that for each generative prompt — like, what’s our sales forecast? — data and outputs are delivered in a way that upholds permission levels and governance policies so users get only information they’re authorized to see.
What it means for customers: Customers can better trust an AI system that keeps data secure throughout the process.
What it means for teams: Teams can confidently prevent unauthorized data access because permissions are maintained at every stage.
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Structured, unstructured, and semi-structured data
Structured data is well-defined data in a fixed format, such as a afghanistan phone number list spreadsheet or customer database, with rows for each customer and columns for name, address, phone number, and email. Structured data is easily understandable, searchable, and machine-readable by traditional analytics tools.
Unstructured data is information that doesn’t have a predefined format or specific data model, and requires specialized tools to create insights. Examples of unstructured data include emails, social media posts, audio and video recordings, images, and web pages. Because unstructured data is growing at a higher rate than structured data, big data technologies that can seamlessly analyze it will be crucial to businesses.