Big Data

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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

App dev trends going hot -- and cold

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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Data governance 2.0

Part 1 of a conversation with Jason Fishbain, chief data officer, University of Wisconsin at Madison

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3 tips for a successful data strategy

Most modern businesses will survive only if they use data to acquire and retain customers, and if they use data to automate their supply chain or protect their valuable assets

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Stateful stream processing with Apache Flink

Apache Flink is made for applications that continuously apply the same business logic to a series of inputs. That’s most business applications

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Real-time data pipelines: pairing message queues and databases

Data leaders need to stay on top of the technologies of message queues and databases

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How to choose the right data-integration tools

For data integration, pipelining, and wrangling data: Here are the seven types of tools you should build your data tool set from

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What is a graph database? A better way to store connected data

Learn why graph databases excel at exploring highly connected data, and how to leverage them in your organization

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What’s new in Apache Spark? Low-latency streaming and Kubernetes

Continuous processing and native Kubernetes support in Apache Spark 2.3 spell the end for micro-batching and Hadoop

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Helping your workforce become data-literate

How to start building a data-literate organization without extensive training

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How to bring BI and analytics to modern nested data structures

Nested data structures are a boon to modeling, storage, and query performance, but pose challenges to traditional BI tools. Here’s how to overcome them

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The wonders of AI—or the shortcomings of search?

Thus far, the case for AI seems to mainly center on how it is taking search to the next level

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Big data analytics: The cloud-fueled shift now under way

Public clouds are the future of enterprise big data analytics, and their use is creating the unified platform needed to fully gain its value

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Adding speed and scalability to existing applications with in-memory data grids

Powering data-intensive and time-sensitive applications with in-memory data grids (IMDGs)

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PyTorch tutorial: Get started with deep learning in Python

Learn how to create a simple neural network, and a more accurate convolutional neural network, with the PyTorch deep learning library

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Think every business should become a software business? Think again

Rather than view themselves as software companies, organizations need to think of themselves as data companies

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The marvels of an event-based schema

When working with various data types at the speed of big data, this method is ideal for integrating and aggregating assorted information for the holistic value it provides

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