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Structural Evolutions in Data

O'Reilly on Data

” Each step has been a twist on “what if we could write code to interact with a tamper-resistant ledger in real-time?” ” There’s as much Keras, TensorFlow, and Torch today as there was Hadoop back in 2010-2012. This technique simulates interactions in a complex system.

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Run high-availability long-running clusters with Amazon EMR instance fleets

AWS Big Data

Amazon EMR is a cloud big data platform for petabyte-scale data processing, interactive analysis, streaming, and machine learning (ML) using open source frameworks such as Apache Spark , Presto and Trino , and Apache Flink. Customers love the scalability and flexibility that Amazon EMR on EC2 offers.

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Strategic planning: How CIOs can build the best possible future

CIO Business Intelligence

Situation analysis involves diagnostically fleshing out the psycho-social-economic reality of the present — how we think, how we live, how we interact, how we work. years) is becoming the optimal temporal “chunk” inside which to do career and strategic planning. Talking to mid-career knowledge workers, it appears that 30 months (2.5

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Why Data Driven Decision Making is Your Path To Business Success

datapine

It enables companies to create new business opportunities, generate more revenue, predict future trends, optimize current operational efforts, and produce actionable insights. Optimism Bias – Making decisions based on the belief that the future will be much better than the past. The proof is in the numbers. 1) General management.

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Euro Soccer Special: What Football Teaches Us About Analytics

Sisense

It’s no surprise that rivals followed suit and that by 2010 analytics were widely used by top teams in leading international leagues. In training, wearable devices measure players’ workload, movement, and fatigue levels to manage their fitness and positioning and optimize their performance during play.

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How to make the most of global talent opportunities

CIO Business Intelligence

The early 2010’s practice of co-locating talent supercharged collaboration, but also limited organizations’ ability to scale with a workforce based in high-density, cost-prohibitive metros. Communication should instead be optimized to provide the most time value for teams.

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Benchmark Results Position GraphDB As the Most Versatile Graph Database Engine

Ontotext

RDF engines are good for graph analytics Historically, the Labeled Property Graph (LPG) engines were optimized to deal with graph analytics, while the Resource Description Framework (RDF) engines were designed for data publishing and metadata management. This era is over! billion edges. CWI) and some of the major graph database vendors (e.g.,