How deeply does The Art of AI Product Development cover unstructured data?

Defines the category and identifies preprocessing needs, but stops short of detailing specific cleaning or structuring procedures.

Unstructured data

As explained in The Art of AI Product Development

Unstructured data is information without a consistent predefined tabular or schema-based organization, such as free text or images.

Unstructured data lacks consistent tabular or schema-based organization. Free text, images, sales calls, and emails require preprocessing, cleaning, and structuring before effective training, inference, or analysis. section 12.1.2 section 9.1.1

Treat unstructured sources according to their access and meaning:

Query sales calls and emails with retrieval-augmented generation rather than specialized structured-data methods. section 9.1.1
Expect different repositories, connectors, and questions across files, databases, cloud stores, and other sources. section 9.1.1
Use data-engineering pipelines to improve quality and make text or images usable for generative AI systems. section 12.1.2

Product-roadmap research

A product manager can combine sales calls, user interviews, reviews, usage data, and competitive research. RAG can retrieve signals from unstructured calls and emails, while specialized algorithms query structured usage data; starting with the most important sources limits complexity. section 9.1.1

How The Art of AI Product Development covers it

Cover of The Art of AI Product Development

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Also explained in

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Elasticsearch in Action, Second EditionUnstructured data is data that does not conform to a fixed field-based or tabular schema, such as free-form text.
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AI-Powered SearchUnstructured data is information without a rigid predefined schema, often containing rich content and relationships in flexible forms such as text, images, video, and audio.
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Data Without LabelsUnstructured data lacks an easily usable row-and-column schema and may include text, images, audio, or video.
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Delivering Machine Learning Projects: From design to deploymentAn unstructured field is a data field containing content such as images, text, or sounds without a fixed tabular representation.
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Essential GraphRAGUnstructured data is information without a predefined tabular or schema-based organization, such as free-form text.
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Machine Learning for Tabular Data: XGBoost, Deep Learning, and AIData whose varied modalities and organization do not conform to a fixed rows-and-columns schema.
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Fast Python: High performance techniques for large datasets
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Machine Learning System DesignData that lacks a fixed machine-readable schema for its content, such as free text or images.
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Knowledge Graphs and LLMs in ActionUnstructured data is information lacking a fixed tabular or schema-constrained organization, such as free-form documents.
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Financial AI in PracticeInformation that does not conform to a predefined schema for direct machine-readable interpretation.

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Related concepts

structured datacontrasts with · Structured data is information organized according to an explicit schema or predictable fields, types, records, or relationships for consistent machine processing.
textincludes · Text is written or digitally encoded linguistic content represented as characters, words, tokens, or other textual units.
retrieval-augmented generationused by · Retrieval-augmented generation is a technique that retrieves relevant information from external sources and supplies it as context to a generative model when producing an output.
language modelused by · A language model is a computational model that represents patterns in linguistic tokens to estimate sequence probabilities and predict or generate language from context.
deep learningused by · Deep learning is a machine-learning approach that uses neural networks with multiple computational layers to learn representations from data.

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