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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. Delete the bucket.

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Understanding the Differences Between Data Lakes and Data Warehouses

Smart Data Collective

Data lakes and data warehouses are probably the two most widely used structures for storing data. Data Warehouses and Data Lakes in a Nutshell. A data warehouse is used as a central storage space for large amounts of structured data coming from various sources. Data Type and Processing.

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Of Muffins and Machine Learning Models

Cloudera

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g.

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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. Rapidminer Studio is its visual workflow designer for the creation of predictive models.

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NVIDIA RAPIDS in Cloudera Machine Learning

Cloudera

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. RAPIDS on the Cloudera Data Platform comes pre-configured with all the necessary libraries and dependencies to bring the power of RAPIDS to your projects. Data Ingestion.

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Data Modeling 301 for the cloud: data lake and NoSQL data modeling and design

erwin

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. This blog is an introduction to some advanced NoSQL and data lake database design techniques (while avoiding common pitfalls) is noteworthy. Machine Learning.

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5 things on our data and AI radar for 2021

O'Reilly on Data

MLOps attempts to bridge the gap between Machine Learning (ML) applications and the CI/CD pipelines that have become standard practice. The Time Is Now to Adopt Responsible Machine Learning. Data use is no longer a “wild west” in which anything goes; there are legal and reputational consequences for using data improperly.

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