Remove Data Analytics Remove Data Lake Remove Structured Data
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Incremental refresh for Amazon Redshift materialized views on data lake tables

AWS Big Data

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it cost-effective to analyze your data using standard SQL and business intelligence tools. Customers use data lake tables to achieve cost effective storage and interoperability with other tools.

Data Lake 105
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Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Both data warehouses and data lakes are used when storing big data.

Data Lake 135
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Recap of Amazon Redshift key product announcements in 2024

AWS Big Data

Today, Amazon Redshift is used by customers across all industries for a variety of use cases, including data warehouse migration and modernization, near real-time analytics, self-service analytics, data lake analytics, machine learning (ML), and data monetization.

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Accelerate Amazon Redshift Data Lake queries with AWS Glue Data Catalog Column Statistics

AWS Big Data

Amazon Redshift enables you to efficiently query and retrieve structured and semi-structured data from open format files in Amazon S3 data lake without having to load the data into Amazon Redshift tables. Amazon Redshift extends SQL capabilities to your data lake, enabling you to run analytical queries.

Data Lake 115
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Complexity Drives Costs: A Look Inside BYOD and Azure Data Lakes

Jet Global

Option 3: Azure Data Lakes. This leads us to Microsoft’s apparent long-term strategy for D365 F&SCM reporting: Azure Data Lakes. Azure Data Lakes are highly complex and designed with a different fundamental purpose in mind than financial and operational reporting. Data lakes are not a mature technology.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

In addition to real-time analytics and visualization, the data needs to be shared for long-term data analytics and machine learning applications. This approach supports both the immediate needs of visualization tools such as Tableau and the long-term demands of digital twin and IoT data analytics.

IoT 111
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Implement slowly changing dimensions in a data lake using AWS Glue and Delta

AWS Big Data

As organizations across the globe are modernizing their data platforms with data lakes on Amazon Simple Storage Service (Amazon S3), handling SCDs in data lakes can be challenging.

Data Lake 101