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Laying the Foundation for Modern Data Architecture

Cloudera

Behind every business decision, there’s underlying data that informs business leaders’ actions. It’s not enough for businesses to implement and maintain a data architecture. Modern Data Architectures are Ready for the Future There is an important distinction between data architecture and modern data architecture.

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Beyond Data Fabrics: Cloudera Modern Data Architectures

Cloudera

What used to be bespoke and complex enterprise data integration has evolved into a modern data architecture that orchestrates all the disparate data sources intelligently and securely, even in a self-service manner: a data fabric. Cloudera data fabric and analyst acclaim. Move beyond a fabric.

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Modernizing the Data Warehouse: Challenges and Benefits

BI-Survey

Especially in times of rapidly changing markets, decision-support systems should promote the quickest possible knowledge growth. Advanced analytics and new ways of working with data also create new requirements that surpass the traditional concepts. But what are the right measures to make the data warehouse and BI fit for the future?

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How Automation and No-Code are Driving Modern Data Warehousing

CIO Business Intelligence

Investment in data warehouses is rapidly rising, projected to reach $51.18 billion by 2028 as the technology becomes a vital cog for enterprises seeking to be more data-driven by using advanced analytics. Data warehouses are, of course, no new concept. More data, more demanding. “As

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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. Nidhi Gupta is a Sr. Partner Solution Architect at AWS.

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Amazon Redshift announcements at AWS re:Invent 2023 to enable analytics on all your data

AWS Big Data

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

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Announcing zero-ETL integrations with AWS Databases and Amazon Redshift

AWS Big Data

To run analytics on their operational data, customers often build solutions that are a combination of a database, a data warehouse, and an extract, transform, and load (ETL) pipeline. ETL is the process data engineers use to combine data from different sources.