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Amazon Q data integration adds DataFrame support and in-prompt context-aware job creation

AWS Big Data

Data preparation The two datasets are hosted as two Data Catalog tables, venue and event , in a project in Amazon SageMaker Unified Studio (preview), as shown in the following screenshots. About the Authors Bo Li is a Senior Software Development Engineer on the AWS Glue team. Shubham Mehta is a Senior Product Manager at AWS Analytics.

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The future of data: A 5-pillar approach to modern data management

CIO Business Intelligence

By modern, I refer to an engineering-driven methodology that fully capitalizes on automation and software engineering best practices. The proposed model illustrates the data management practice through five functional pillars: Data platform; data engineering; analytics and reporting; data science and AI; and data governance.

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Cloud analytics migration: how to exceed expectations

CIO Business Intelligence

A cloud analytics migration project is a heavy lift for enterprises that dive in without adequate preparation. A modern data and artificial intelligence (AI) platform running on scalable processors can handle diverse analytics workloads and speed data retrieval, delivering deeper insights to empower strategic decision-making.

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Demystify data sharing and collaboration patterns on AWS: Choosing the right tool for the job

AWS Big Data

Let’s briefly describe the capabilities of the AWS services we referred above: AWS Glue is a fully managed, serverless, and scalable extract, transform, and load (ETL) service that simplifies the process of discovering, preparing, and loading data for analytics. He has around 20 years of software development and architecture experience.

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics. But today, dashboards and visualizations have become table stakes.

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Unlocking near real-time analytics with petabytes of transaction data using Amazon Aurora Zero-ETL integration with Amazon Redshift and dbt Cloud

AWS Big Data

Zero-ETL integration with Amazon Redshift reduces the need for custom pipelines, preserves resources for your transactional systems, and gives you access to powerful analytics. dbt Cloud is a hosted service that helps data teams productionize dbt deployments. For the purposes of this post, use a dbt Cloud-hosted managed repository.

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Turning Data Into Decisions: How Analytics Improves Transportation Strategy

Smart Data Collective

Reading: Turning Data Into Decisions: How Analytics Improves Transportation Strategy Share Notification Font Resizer Aa Font Resizer Aa Search About Help Privacy Follow US © 2008-23 SmartData Collective. Predictive analytics is another powerful tool. Accept X By using this site, you agree to the Privacy Policy and Terms of Use.