Big Data

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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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Unlocking the power of today’s big data through governance

Contrary to what some believe, data governance isn’t about creating a veil of secrecy around data

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7 essential technologies for a modern data architecture

These key technologies are “re-platforming” the enterprise to enable faster, easier, more flexible access to large volumes of precious data

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Review: Neo4j supercharges graph analytics

When it comes to tracking relationships, Neo4j is faster, more flexible, and more scalable than relational databases

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Cython tutorial: How to speed up Python

How to use Cython and its Python-to-C compiler to give your Python applications a rocket boost

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Get started with TensorFlow

Begin harnessing the power of Google’s open source machine learning library with InfoWorld's hands-on tutorial

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