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Migrate from Amazon Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics Studio

AWS Big Data

Amazon Kinesis Data Analytics makes it easy to transform and analyze streaming data in real time. In this post, we discuss why AWS recommends moving from Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics for Apache Flink to take advantage of Apache Flinkā€™s advanced streaming capabilities.

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Simplify and speed up Apache Spark applications on Amazon Redshift data with Amazon Redshift integration for Apache Spark

AWS Big Data

Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark is a popular framework that you can use to build applications for use cases such as ETL (extract, transform, and load), interactive analytics, and machine learning (ML). groupBy("qtr").sum("qtysold").select(

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Themes and Conferences per Pacoid, Episode 5

Domino Data Lab

Lately Iā€™ve been developing curriculum for a client for their new ā€œIntro to Data Scienceā€ sequence of courses. Iā€™ve been teaching data science since 2008 privately for employers ā€“ exec staff, investors, IT teams, and the data teams Iā€™ve led ā€“ and since 2013, for industry professionals in general. Thatā€™s no problem.

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Data Observability and Monitoring with DataOps

DataKitchen

Thatā€™s a fair point, and it places emphasis on what is most important ā€“ what best practices should data teams employ to apply observability to data analytics. We see data observability as a component of DataOps. In our definition of data observability, we put the focus on the important goal of eliminating data errors.

Testing 214
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Themes and Conferences per Pacoid, Episode 12

Domino Data Lab

Heā€™s been out of Wolfram for a while and writing exquisite science books including Elements: A Visual Explanation of Every Known Atom in the Universe and Molecules: The Architecture of Everything. 2008 – Financial crisis : scientists flee Wall St. 2018 – Global reckoning about data governance, aka ā€œOops!