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Manage Query Workloads with Query Monitoring Rules in Amazon Redshift | AWS Big Data Blog

Data warehousing workloads are known for high variability due to seasonality, potentially expensive exploratory queries, and the varying skill levels of SQL developers. To obtain high performance in the face of highly variable workloads, Amazon Redshift workload management (WLM) enables you to flexibly manage priorities and resource usage. With WLM, short, fast-running queries don’t get stuck in queues behi ...

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Deep Learning with Emojis (not Math) – tech-at-instacart

Sorting shopping lists with deep learning using Keras and Tensorflow. Shopping for groceries is hard. Stores are large and have complex layouts that are confusing to navigate. The hummus you want could be in the dairy section, the deli section, or somewhere else entirely. Efficiently navigating a store can be a daunting task. At Instacart, our customers can order millions of products from hundreds of retail ...

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Introducing Apache Arrow: A Fast, Interoperable In-Memory Columnar Data Structure Standard – Cloudera Engineering Blog

Engineers from across the Apache Hadoop community are collaborating to establish Arrow as a de-facto standard for columnar in-memory processing and interchange. Here’s how it works. Apache Arrow is an in-memory data structure specification for use by engineers building data systems. It has several key benefits: A columnar memory-layout permitting O(1) random access. The layout is highly cache-efficient in a ...

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An Exclusive Look at How AI and Machine Learning Work at Apple

Three years earlier, Apple had been the first major tech company to integrate a smart assistant into its operating system. Siri was the company’s adaptation of a standalone app it had purchased, along with the team that created it, in 2010. Initial reviews were ecstatic, but over the next few months and years, users became impatient with its shortcomings. All too often, it erroneously interpreted commands. ...

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Google adds new data analytics and database offerings | ZDNet

Google adds new data analytics and database offerings For the first time, Google is directly integrating its advertising services with the Google Cloud Platform. Google on Thursday rolled out new data analytics and database products, allowing Cloud customers to better manage and more fully exploit their data.First, the company is introducing a new data transfer service for BigQuery, its data analysis servic ...

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Using Apache Spark for large-scale language model training | Engineering Blog | Facebook Code

Processing large-scale data is at the heart of what the data infrastructure group does at Facebook. Over the years we have seen tremendous growth in our analytics needs, and to satisfy those needs we either have to design and build a new system or adopt an existing open source solution and improve it so it works at our scale. For some of our batch-processing use cases we decided to use Apache Spark, a fast- ...

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Announcing real-time Geospatial Analytics in Azure Stream Analytics | Blog | Microsoft Azure

We recently announced the general availability of Geospatial Functions in Azure Stream Analytics to enable real-time analytics on streaming geospatial data. This will make it possible to realize scenarios such as fleet monitoring, asset tracking, geofencing, phone tracking across cell sites, connected manufacturing, ridesharing solutions, etc. with production grade quality with a few lines of code. The conn ...

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Solar, wind, storage and big data: Why energy may soon be free : Renew Economy

Solar, wind, storage and big data: Why energy may soon be free By Giles Parkinson on 1 August 2016 Global investment bank Citi is predicting that the combination of near zero-variable cost energy sources such as solar and wind, along with smart analytics and “big data”, may deliver what the nuclear industry promised nearly half a century ago – free energy. “The notion of free energy came to prominence in th ...

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Review: The best frameworks for machine learning and deep learning | InfoWorld

Over the past year I've reviewed half a dozen open source machine learning and/or deep learning frameworks: Caffe, Microsoft Cognitive Toolkit (aka CNTK 2), MXNet, Scikit-learn, Spark MLlib, and TensorFlow. If I had cast my net even wider, I might well have covered a few other popular frameworks, including Theano (a 10-year-old Python deep learning and machine learning framework), Keras (a deep learning fro ...

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Stacking up the cloud vendors: AWS vs. Microsoft Azure, IBM, Google, Oracle

It's not easy tracking the girth of public cloud providers amid run rates, as-a-service sales projections, and a lack of transparency. Here's how AWS stacks up against Microsoft Azure, IBM, Google, and Oracle. Amazon Web Services continues to lead the cloud pack as it delivered a 2016 operating profit of $3.1 billion on revenue of $12.22 billion, up from $7.88 billion in 2015. While analysts will fret about ...

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