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Google BigQuery Architecture for Data Engineers

Analytics Vidhya

BigQuery was first launched as a service in 2010, with general availability in November 2011. The post Google BigQuery Architecture for Data Engineers appeared first on Analytics Vidhya. Since its inception, BigQuery has evolved into a more economical and fully managed data warehouse that can run lightning-fast […].

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Boosting RAG-based intelligent document assistants using entity extraction, SQL querying, and agents with Amazon Bedrock

AWS Machine Learning Blog

This is especially true for questions that require analytical reasoning across multiple documents. This task involves answering analytical reasoning questions. In this post, we show how to design an intelligent document assistant capable of answering analytical and multi-step reasoning questions in three parts.

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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning Blog

Without specialized structured query language (SQL) knowledge or Retrieval Augmented Generation (RAG) expertise, these analysts struggle to combine insights effectively from both sources. SageMaker Unified Studio setup SageMaker Unified Studio is a browser-based web application where you can use all your data and tools for analytics and AI.

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Top 9 AI conferences and events in USA – 2023

Data Science Dojo

A Glimpse into the future : Want to be like a scientist who predicted the rise of machine learning back in 2010? The speaker is Andrew Madson, a data analytics leader and educator. However, in previous iterations of the summit, speakers have included prominent voices in data engineering and analytics. Link to event -> Live!

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Analyzing the history of Tableau innovation

Tableau

In this blog post, I'll describe my analysis of Tableau's history to drive analytics innovation—in particular, I've identified six key innovation vectors through reflecting on the top innovations across Tableau releases. And with this work, I invite discussions about this history, my analysis, and the implications for the future of analytics.

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On the implementation of digital tools

Dataconomy

Forbes reports that global data production increased from 2 zettabytes in 2010 to 44 ZB in 2020, with projections exceeding 180 ZB by 2025 – a staggering 9,000% growth in just 15 years, partly driven by artificial intelligence. While accounting teams typically book summarized versions, users needed line item details for analytics.

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Analyzing the history of Tableau innovation

Tableau

In this blog post, I'll describe my analysis of Tableau's history to drive analytics innovation—in particular, I've identified six key innovation vectors through reflecting on the top innovations across Tableau releases. And with this work, I invite discussions about this history, my analysis, and the implications for the future of analytics.

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