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Modernize your legacy databases with AWS data lakes, Part 2: Build a data lake using AWS DMS data on Apache Iceberg

AWS Big Data

This is part two of a three-part series where we show how to build a data lake on AWS using a modern data architecture. This post shows how to load data from a legacy database (SQL Server) into a transactional data lake ( Apache Iceberg ) using AWS Glue.

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Incremental refresh for Amazon Redshift materialized views on data lake tables

AWS Big Data

You can use Amazon Redshift to analyze structured and semi-structured data and seamlessly query data lakes and operational databases, using AWS designed hardware and automated machine learning (ML)-based tuning to deliver top-tier price performance at scale. Amazon Redshift delivers price performance right out of the box.

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Rapidminer Platform Supports Entire Data Science Lifecycle

David Menninger's Analyst Perspectives

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization.

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Steps taken to build Sevita’s first enterprise data platform

CIO Business Intelligence

Here, CIO Patrick Piccininno provides a roadmap of his journey from data with no integration to meaningful dashboards, insights, and a data literate culture. You ’re building an enterprise data platform for the first time in Sevita’s history. Second, the manual spreadsheet work resulted in significant manual data entry.

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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. We have launched new RA3.large large instances.

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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.

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MongoDB Enhances Developer Data Platform

David Menninger's Analyst Perspectives

While new and emerging capabilities might catch the eye, features that address data platform security, performance and availability remain some of the most significant deal-breakers when enterprises are considering potential data platform providers. This is especially true for mission-critical workloads.

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