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Snowflake: 3 Benefits of a Self-Adapting Data Warehouse

Corinium

With the rise of new data streams, the ability to access more data and derive insights from it more quickly is critical. By 2023, worldwide revenue for big data solutions will reach $260 billion.* Anticipate patterns more accurately and optimize queries. Automate data organization, optimize workloads, and more.

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Accelerate your data warehouse migration to Amazon Redshift – Part 7

AWS Big Data

With Amazon Redshift, you can use standard SQL to query data across your data warehouse, operational data stores, and data lake. Migrating a data warehouse can be complex. You have to migrate terabytes or petabytes of data from your legacy system while not disrupting your production workload.

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Simplifying data processing at Capitec with Amazon Redshift integration for Apache Spark

AWS Big Data

This integration expands the possibilities for AWS analytics and machine learning (ML) solutions, making the data warehouse accessible to a broader range of applications. Your applications can seamlessly read from and write to your Amazon Redshift data warehouse while maintaining optimal performance and transactional consistency.

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Achieve near real time operational analytics using Amazon Aurora PostgreSQL zero-ETL integration with Amazon Redshift

AWS Big Data

When data is used to improve customer experiences and drive innovation, it can lead to business growth,” – Swami Sivasubramanian , VP of Database, Analytics, and Machine Learning at AWS in With a zero-ETL approach, AWS is helping builders realize near-real-time analytics. Choose a suitable instance size (the default is db.r5.2xlarge ).

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How IBM and AWS are partnering to deliver the promise of AI for business

IBM Big Data Hub

IBM and AWS partnership focuses on delivering solutions in areas like: Supply chain optimization with AI-infused Planning Analytics IBM Planning Analytics on AWS offers a powerful platform for supply chain optimization, blending IBM’s analytics expertise with AWS’s cloud capabilities.

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Peloton embraces Amazon Redshift to unlock the power of data during changing times

AWS Big Data

During that same time, AWS has been focused on helping customers manage their ever-growing volumes of data with tools like Amazon Redshift , the first fully managed, petabyte-scale cloud data warehouse. One group performed extract, transform, and load (ETL) operations to take raw data and make it available for analysis.

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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics

AWS Big Data

The end benefit for you is more effective and optimized AWS Glue for Apache Spark workloads. About the Authors Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team. With these enhanced metrics, you can more easily identify and troubleshoot issues in real time. Check it out!

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