Remove Measurement Remove Optimization Remove Unstructured Data
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Unbundling the Graph in GraphRAG

O'Reilly on Data

decomposes a complex task into a graph of subtasks, then uses LLMs to answer the subtasks while optimizing for costs across the graph. presented the TRACE framework for measuring results, which showed how GraphRAG achieves an average performance improvement of up to 14.03%. For example, “ Graph of Thoughts ” by Maciej Besta, et al.,

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The Rise of Unstructured Data

Cloudera

Here we mostly focus on structured vs unstructured data. In terms of representation, data can be broadly classified into two types: structured and unstructured. Structured data can be defined as data that can be stored in relational databases, and unstructured data as everything else.

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Escaping POC Purgatory: Evaluation-Driven Development for AI Systems

O'Reilly on Data

Two big things: They bring the messiness of the real world into your system through unstructured data. How will you measure success? So now we have a user persona, several scenarios, and a way to measure success. Slow response/high cost : Optimize model usage or retrieval efficiency. The answers were: Our students.

Testing 174
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An Introduction To Data Dashboards: Meaning, Definition & Industry Examples

datapine

Learn all about data dashboards with our executive bite-sized summary! What Is A Data Dashboard? These are measured through Key Performance Indicators (KPIs), which provide insights that help to foster growth and improvement. In doing so, your business will be data-driven, and as a direct result – more successful.

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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

From reactive fixes to embedded data quality Vipin Jain Breaking free from recurring data issues requires more than cleanup sprints it demands an enterprise-wide shift toward proactive, intentional design. Data quality must be embedded into how data is structured, governed, measured and operationalized.

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Measure Twice, Cut Once: How the Right Data Modeling Tool Drives Business Value

erwin

The need for an effective data modeling tool is more significant than ever. For decades, data modeling has provided the optimal way to design and deploy new relational databases with high-quality data sources and support application development. There’s an expression: measure twice, cut once.

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The DataOps Vendor Landscape, 2021

DataKitchen

Monte Carlo DataData reliability delivered. Data breaks. Observe, optimize, and scale enterprise data pipelines. . Validio — Automated real-time data validation and quality monitoring. . DataOps requires that teams measure their analytic processes in order to see how they are improving over time.

Testing 304