Remove Analytics Remove Data Warehouse Remove Metadata
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Data Warehouses: Basic Concepts for data enthusiasts

Analytics Vidhya

Introduction The purpose of a data warehouse is to combine multiple sources to generate different insights that help companies make better decisions and forecasting. It consists of historical and commutative data from single or multiple sources. Most data scientists, big data analysts, and business […].

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SAP Datasphere Powers Business at the Speed of Data

Rocket-Powered Data Science

In fact, by putting a single label like AI on all the steps of a data-driven business process, we have effectively not only blurred the process, but we have also blurred the particular characteristics that make each step separately distinct, uniquely critical, and ultimately dependent on specialized, specific technologies at each step.

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Enriching metadata for accurate text-to-SQL generation for Amazon Athena

AWS Big Data

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on. Table metadata is fetched from AWS Glue.

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Expand data access through Apache Iceberg using Delta Lake UniForm on AWS

AWS Big Data

This expands data access to broader options of analytics engines. You can learn how to query Delta Lake native tables through UniForm from different data warehouses or engines such as Amazon Redshift as an example of expanding data access to more engines.

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Write queries faster with Amazon Q generative SQL for Amazon Redshift

AWS Big Data

Amazon Redshift is a fully managed, AI-powered cloud data warehouse that delivers the best price-performance for your analytics workloads at any scale. It enables you to get insights faster without extensive knowledge of your organization’s complex database schema and metadata. Your data is not shared across accounts.

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The next generation of Amazon SageMaker: The center for all your data, analytics, and AI

AWS Big Data

This week on the keynote stages at AWS re:Invent 2024, you heard from Matt Garman, CEO, AWS, and Swami Sivasubramanian, VP of AI and Data, AWS, speak about the next generation of Amazon SageMaker , the center for all of your data, analytics, and AI. The relationship between analytics and AI is rapidly evolving.

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How Eightfold AI implemented metadata security in a multi-tenant data analytics environment with Amazon Redshift

AWS Big Data

The Eightfold Talent Intelligence Platform powered by Amazon Redshift and Amazon QuickSight provides a full-fledged analytics platform for Eightfold’s customers. It delivers analytics and enhanced insights about the customer’s Talent Acquisition, Talent Management pipelines, and much more.

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