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SAP Datasphere Powers Business at the Speed of Data

Rocket-Powered Data Science

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Plus, AI can also help find key insights encoded in data.

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Recap of Amazon Redshift key product announcements in 2024

AWS Big Data

Amazon Redshift , launched in 2013, has undergone significant evolution since its inception, allowing customers to expand the horizons of data warehousing and SQL analytics. Industry-leading price-performance Amazon Redshift offers up to three times better price-performance than alternative cloud data warehouses.

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Domo Addresses Data Products and Agentic AI

David Menninger's Analyst Perspectives

Domo is best known as a business intelligence (BI) and analytics software provider, thanks to its functionality for visualization, reporting, data science and embedded analytics. Domos platform addresses the full breadth of an enterprises analytics needs.

Metrics 130
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Empower financial analytics by creating structured knowledge bases using Amazon Bedrock and Amazon Redshift

AWS Big Data

Traditionally, financial data analysis could require deep SQL expertise and database knowledge. Now with Amazon Bedrock Knowledge Bases integration with structured data, you can use simple, natural language prompts to query complex financial datasets. or Give me details of all accounts for a specific customer.

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Accelerate analytics and AI innovation with the next generation of Amazon SageMaker

AWS Big Data

At AWS re:Invent 2024, we announced the next generation of Amazon SageMaker , the center for all your data, analytics, and AI. It enables teams to securely find, prepare, and collaborate on data assets and build analytics and AI applications through a single experience, accelerating the path from data to value.

Analytics 111
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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes.

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Cloudera Data Warehouse outperforms Azure HDInsight in TPC-DS benchmark

Cloudera

Performance is one of the key, if not the most important deciding criterion, in choosing a Cloud Data Warehouse service. In today’s fast changing world, enterprises have to make data driven decisions quickly and for that they rely heavily on their data warehouse service. . benchmark.