Big Data
Big Data | News, how-tos, features, reviews, and videos
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
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
Machine learning megaguide: Amazon, Microsoft, Databricks, Google, HPE, IBM
Download InfoWorld's massive roundup of Amazon, Microsoft, Databricks, Google, HPE, and IBM machine learning toolkits
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
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
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
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
Public cloud megaguide: Amazon, Microsoft, Google, IBM, and Joyent compared
The top five public clouds pile on the services and options, while adding unique twists
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
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 Data science outperforms these outdated methods, especially in certain key areas
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
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...
Quick guide: Learn to crunch big data with R
Get started using the open source R programming language to do statistical computing and graphics on large data sets
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
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
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
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
Build an IoT analytics solution with big data tools
The Internet of things seems futuristic, but real systems are delivering real analytics value today. Here’s some real-world IoT advice from the field
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
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
Why data democratization is crucial to your business
Data democratization will catapult companies to new heights of performance—if done right
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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