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How Amazon Devices scaled and optimized real-time demand and supply forecasts using serverless analytics

AWS Big Data

This data is used in procuring devices’ inventory to meet Amazon customers’ demands. With data volumes exhibiting a double-digit percentage growth rate year on year and the COVID pandemic disrupting global logistics in 2021, it became more critical to scale and generate near-real-time data.

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5 Key Takeaways from #Current2023

Cloudera

Flink was launched in 2015 as the world’s first open source streaming-first distributed stream processing engine and has since grown to rival Spark in terms of popularity. The adoption of Flink mirrors growth in streaming data volumes and maturity of the streaming market. What about data lock-in? Is this yet another database?

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Upcoming Power BI Workshop in Huntington Beach, CA – Apr 10, 2015

Ms SQL Girl

Apr 10, 2015 7:45 AM – 5:15 PM. Early bird (until Apr 1, 2015) $99.00. Acquiring and Preparing Data for Power View and Excel. Data Modelling Patterns 101 using Power Pivot. Tips and Tricks on Charts and Data Models. Acquiring and Preparing Data for Power View and Excel. Regular price $109.00.

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Upcoming Power BI Workshop in Huntington Beach, CA – Apr 10, 2015

Ms SQL Girl

Apr 10, 2015 7:45 AM – 5:15 PM. Early bird (until Apr 1, 2015) $99.00. Acquiring and Preparing Data for Power View and Excel. Data Modelling Patterns 101 using Power Pivot. Tips and Tricks on Charts and Data Models. Acquiring and Preparing Data for Power View and Excel. Regular price $109.00.

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Moving Enterprise Data From Anywhere to Any System Made Easy

Cloudera

Since 2015, the Cloudera DataFlow team has been helping the largest enterprise organizations in the world adopt Apache NiFi as their enterprise standard data movement tool. This need has generated a market opportunity for a universal data distribution service. Why does every organization need it when using a modern data stack?

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Themes and Conferences per Pacoid, Episode 11

Domino Data Lab

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated.

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Build a serverless analytics application with Amazon Redshift and Amazon API Gateway

AWS Big Data

Data abstraction – Decouple and refactor underlying data structure and infrastructure. In this post, you will learn how to build a serverless analytics application using Amazon Redshift Data API and Amazon API Gateway WebSocket and REST APIs. The Data API takes care of managing database connections and buffering data.