Big Data

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How to get real value from big data in the cloud

Cloud computing makes big data affordable, but few companies know how to actually take actual advantage of it

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What is Julia? A fresh approach to numerical computing

A “no compromises” programming language for data scientists, Julia combines the ease of a dynamic language with the speed of a compiled language

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In an age of fake news, is there really such a thing as fake data?

The pitfalls and benefits of using synthetic data to train AI algorithms

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It’s time we tapped APIs for business analytics

With so much information flowing through APIs, the API management system offers a central hub for business insight

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9 Splunk alternatives for log analysis

Splunk may be the most famous way to make sense of mass quantities of log data, but it is far from the only player around

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Human data is the future of information

That’s good for everyone, as it respects that data has become so important to people’s livelihood—their credit scores just as much their personalities—that it shouldn’t be treated differently than they would be treated

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What is TensorFlow? The machine learning library explained

TensorFlow is a Python-friendly open source library for numerical computation that makes machine learning faster and easier

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How will data intelligence transform the enterprise?

Traditional business methods aren’t enough to help businesses stay competitive in today’s data-driven world. Data science outperforms these outdated methods, especially in certain key areas

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How Arcadia Data brings self-service BI to the data lake

The data lake is a new approach to data management that requires a new approach to analytics

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Tales of eTail West, big data, and e-commerce success—or failure

The Retail Death Star (a euphemism for whoever you think it is) has such a glowing reputation for its acumen with data that other companies clamor to know how the Death Star does it. Personal experience suggests myth does not match...

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Big data + AI: Context, trust, and other key secrets to success

Machine learning can supercharge data analysis and spur innovation, but it lacks the business context to make optimal decisions every time

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Review: Amazon SageMaker scales deep learning

AWS machine learning service offers easy scalability for training and inference, includes a good set of algorithms, and supports any others you supply

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The era of the cloud database has finally begun

Enterprises are waking up to discover that their database needs have changed dramatically—and that the old-school RDBMS is no longer the best tool

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6 hidden bottlenecks in cloud data migration

From navigating cloud storage options to verifying the data post-transfer, follow these steps to avoid the hazards of cloud migration

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3 requirements of modern archive for massive unstructured data

As the nature and scale of enterprise data changes, secondary storage—especially archive—becomes a huge opportunity to add value to organizational data

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21 hot programming trends—and 21 going cold

Hot or not? From the web to the motherboard to the training ground, get the scoop on what’s in and what’s out in app dev

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Why data democratization is crucial to your business

Data democratization will catapult companies to new heights of performance—if done right

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Google Cloud tutorial: Get started with Google Cloud

From virtual machines and Kubernetes clusters to serverless functions and machine learning APIs — how to navigate Google’s cloud riches

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