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Generative AI is pushing unstructured data to center stage

CIO Business Intelligence

When I think about unstructured data, I see my colleague Rob Gerbrandt (an information governance genius) walking into a customer’s conference room where tubes of core samples line three walls. While most of us would see dirt and rock, Rob sees unstructured data. have encouraged the creation of unstructured data.

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The most valuable AI use cases for business

IBM Big Data Hub

The IBM team is even using generative AI to create synthetic data to build more robust and trustworthy AI models and to stand in for real-world data protected by privacy and copyright laws. These systems can evaluate vast amounts of data to uncover trends and patterns, and to make decisions.

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Exploring real-time streaming for generative AI Applications

AWS Big Data

They can perform a wide range of different tasks, such as natural language processing, classifying images, forecasting trends, analyzing sentiment, and answering questions. FMs are multimodal; they work with different data types such as text, video, audio, and images.

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Modernize Using The BI & Analytics Magic Quadrant

Rita Sallam

By contrast, traditional BI platforms are designed to support modular development of IT-produced analytic content, specialized tools and skills, and significant upfront data modeling, coupled with a predefined metadata layer, is required to access their analytic capabilities. Answer: Better than every other vendor?

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Why Spreadsheets Are Your Secret Weapon for Efficient Data Governance

Alation

Other forms of governance address specific sets or domains of data including information governance (for unstructured data), metadata governance (for data documentation), and domain-specific data (master, customer, product, etc.). Data catalogs and spreadsheets are related in many ways. a spreadsheet.

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Top 10 Key Features of BI Tools in 2020

FineReport

Metadata management. Users can centrally manage metadata, including searching, extracting, processing, storing, sharing metadata, and publishing metadata externally. The metadata here is focused on the dimensions, indicators, hierarchies, measures and other data required for business analysis.

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A Flexible and Efficient Storage System for Diverse Workloads

Cloudera

Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases. There are also newer AI/ML applications that need data storage, optimized for unstructured data using developer friendly paradigms like Python Boto API. FILE_SYSTEM_OPTIMIZED Bucket (“FSO”).