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Introducing Amazon MWAA larger environment sizes

AWS Big Data

Running Apache Airflow at scale puts proportionally greater load on the Airflow metadata database, sometimes leading to CPU and memory issues on the underlying Amazon Relational Database Service (Amazon RDS) cluster. A resource-starved metadata database may lead to dropped connections from your workers, failing tasks prematurely.

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Gartner D&A Summit Bake-Offs Explored Flooding Impact And Reasons for Optimism!

Rita Sallam

We explored these questions and more at our Bake-Offs and Show Floor Showdowns at our Data and Analytics Summit in Orlando with 4,000 of our closest D&A friends and family. The first featured analytics and BI platform Gartner Magic Quadrant leaders while the other showcased high interest data science and machine learning platforms.

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Convergent Evolution

Peter James Thomas

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. One of the early promises of a Data Lake approach was that – once all relevant data had been ingested – this would be directly leveraged by Data Scientists to derive insight.

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Keeping Small Queries Fast – Short query optimizations in Apache Impala

Cloudera

Data science experiment result and performance analysis, for example, calculating model lift. While plan time statistics are unreliable, an execution engine that adapts in real-time based on actual data means that the right optimization can be applied dynamically when the query seems to be taking longer than it should.

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Cloudera Provides First Look at Cloudera Data Platform, the Industry’s First Enterprise Data Cloud

Cloudera

On June 18th, Cloudera provided an exclusive preview of these capabilities, and more, with the introduction of Cloudera Data Platform (CDP), the industry’s first enterprise data cloud. Over 2000 customers and partners joined us in this live webinar featuring a first-look at our upcoming cloud-native CDP services.

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How to Build a Performant Data Warehouse in Redshift

Sisense

Redshift sort keys allow you to specify in what order the data is stored across your nodes. By using metadata about where the data is stored, it allows the query engine to skip over chunks of data that it knows are not within the bounds of your query’s parameters.

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Natural Language in Python using spaCy: An Introduction

Domino Data Lab

Data science teams in industry must work with lots of text, one of the top four categories of data used in machine learning. That’s excellent for supporting really interesting workflow integrations in data science work. metadata=convention_df["speaker"]? ). category="democrat",?.