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How to Optimize Data Warehouse with STAR Schema?

Analytics Vidhya

Introduction The STAR schema is an efficient database design used in data warehousing and business intelligence. It organizes data into a central fact table linked to surrounding dimension tables. A major advantage of the STAR […] The post How to Optimize Data Warehouse with STAR Schema?

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Analytics databases

Dataconomy

Analytics databases play a crucial role in driving insights and decision-making in today’s data-driven world. By providing a structured way to analyze historical data, these databases empower organizations to uncover trends and patterns that inform strategies and optimize operations. What are analytics databases?

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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

Flipboard

While customers can perform some basic analysis within their operational or transactional databases, many still need to build custom data pipelines that use batch or streaming jobs to extract, transform, and load (ETL) data into their data warehouse for more comprehensive analysis.

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Introducing Agent Bricks: Auto-Optimized Agents Using Your Data

databricks

In just under 60 minutes, we had a working agent that can transform complex unstructured data usable for Analytics.” — Joseph Roemer, Head of Data & AI, Commercial IT, AstraZeneca “Agent Bricks allowed us to build a cost-effective agent we could trust in production. Agent Bricks is now available in beta.

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Data lakes vs. data warehouses: Decoding the data storage debate

Data Science Dojo

When it comes to data, there are two main types: data lakes and data warehouses. Which one is right for your business? What is a data lake? An enormous amount of raw data is stored in its original format in a data lake until it is required for analytics applications.

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Enhance your Amazon Redshift cloud data warehouse with easier, simpler, and faster machine learning using Amazon SageMaker Canvas

AWS Machine Learning Blog

The analyst can easily pull in the data they need, use natural language to clean up and fill any missing data, and finally build and deploy a machine learning model that can accurately predict the loan status as an output, all without needing to become a machine learning expert to do so. A SageMaker domain.

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Introducing Databricks One

databricks

AI-powered search and recommendations help users find relevant dashboards, analytics and apps faster. Additionally, content is organized into Domains—collections of data, dashboards, Genie spaces, and apps grouped by business concept, such as a project, use case, or business unit.