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Build a financial research assistant using Amazon Q Business and Amazon QuickSight for generative AI–powered insights

Flipboard

Their information is split between two types of data: unstructured data (such as PDFs, HTML pages, and documents) and structured data (such as databases, data lakes, and real-time reports). Different types of data typically require different tools to access them.

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Shaping the future: OMRON’s data-driven journey with AWS

AWS Machine Learning Blog

By analyzing their data, organizations can identify patterns in sales cycles, optimize inventory management, or help tailor products or services to meet customer needs more effectively. One key initiative is ODAPChat, an AI-powered chat-based assistant employees can use to interact with data using natural language queries.

AWS 82
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Query structured data from Amazon Q Business using Amazon QuickSight integration

AWS Machine Learning Blog

Amazon Q Business is a generative AI-powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in your enterprise systems. Upload the non-structured document(s) to Amazon S3 and sync the data source. Choose the link under Deployed URL.

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Exploring the fundamentals of online transaction processing databases

Dataconomy

Conversely, OLAP systems are optimized for conducting complex data analysis and are designed for use by data scientists, business analysts, and knowledge workers. OLAP systems support business intelligence, data mining, and other decision support applications.

Database 159
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A Guide to Data Analytics in the Travel Industry

Alation

While this industry has used data and analytics for a long time, many large travel organizations still struggle with data silos , which prevent them from gaining the most value from their data. What is big data in the travel and tourism industry?

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AI that’s ready for business starts with data that’s ready for AI

IBM Journey to AI blog

Open is creating a foundation for storing, managing, integrating and accessing data built on open and interoperable capabilities that span hybrid cloud deployments, data storage, data formats, query engines, governance and metadata. Trusted, governed data is essential for ensuring the accuracy, relevance and precision of AI.

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How to Build a Successful Metadata Management Framework

Alation

A metadata management framework combines organizational structure and a set of tools to create a data asset taxonomy. Document type: describes creation, storage, and use during business processes. Establish business glossaries: Define business terms and create standard relationships for data governance.