Analytics

Analytics news, information, and how-to advice

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Monetizing your models with machine learning solutions

Connecting the business user to the science is a necessary step for companies looking to extend their leadership position

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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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‘To supervise or not to supervise’ is a question at the heart of machine learning

A guide to unsupervised and supervised machine learning and understanding their application by businesses today

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Moving your data analytics to the cloud isn’t so easy

If you dream of modernizing data warehouses—and data marts—in the new platform of the cloud, watch out: It’s not as easy as you might think

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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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Demystifying machine learning

Businesses need more than a machine learning engine or framework to successfully extract the valuable and actionable insights from their data—and not all machine learning solutions are created equal

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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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Your analytics team needs a liberal arts major

Whether you are a company director, an educator or a parent, you need to think about how to create a diverse workforce in the short and long term

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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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Making intelligent data hubs a reality

Beyond buzzwords and analyst-speak, putting data into practice

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Navigating time in knowledge graphs

The temporal benefits of cognitive knowledge graphs can affect almost any business problem, including basic issues of data management such as data quality, data cleansing, and integration

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Introducing Pandas DataFrame for Python data analysis

The open source library gives Python the ability to work with spreadsheet-like data for fast data loading, manipulating, aligning, and merging, among other functions

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How web annotation will transform content management

W3C standard annotation is a fundamental upgrade to the web that will bridge information silos and enable far easier content sharing and reuse

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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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