Remove Analytics Remove Data Architecture Remove Data Lake Remove Data Warehouse
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Laying the Foundation for Modern Data Architecture

Cloudera

It’s not enough for businesses to implement and maintain a data architecture. The unpredictability of market shifts and the evolving use of new technologies means businesses need more data they can trust than ever to stay agile and make the right decisions.

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Migrate a petabyte-scale data warehouse from Actian Vectorwise to Amazon Redshift

AWS Big Data

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. Legacy architecture The customer’s platform was the main source for one-time, batch, and content processing.

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Use Apache Iceberg in your data lake with Amazon S3, AWS Glue, and Snowflake

AWS Big Data

They understand that a one-size-fits-all approach no longer works, and recognize the value in adopting scalable, flexible tools and open data formats to support interoperability in a modern data architecture to accelerate the delivery of new solutions.

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Query your Iceberg tables in data lake using Amazon Redshift (Preview)

AWS Big Data

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

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Checklist Report: Preparing for the Next-Generation Cloud Data Architecture

Data architectures to support reporting, business intelligence, and analytics have evolved dramatically over the past 10 years. Download this TDWI Checklist report to understand: How your organization can make this transition to a modernized data architecture. The decision making around this transition.

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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

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Get maximum value out of your cloud data warehouse with Amazon Redshift

AWS Big Data

With the right analytics approach, this is possible. In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments.