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Business intelligence data mining News
July 31, 2017
Think before you act on artificial intelligence technologies to ensure that your efforts to become a "cognitive business" lead you in the right direction.
May 23, 2017
Hiring a data scientist is hard enough given the shortage of candidates, but the subtle mix of skills required by the job can make hiring one even harder.
May 18, 2017
Deep learning may share some characteristics of traditional machine learning, but experienced users say it's really in a class by itself when it comes to predictive-model design and output.
March 08, 2017
Data scientists at companies such as LinkedIn and Cisco are applying aspects of the scientific method to data mining and analysis initiatives to try to make sure they get valid results.
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Ad hoc analysis is the term commonly used in businesses to describe a product (analytical report, statistical analysis or model, or other report or summary of data) produced one time to answer a single, specific business question. Continue Reading
A data scientist is a professional responsible for collecting, analyzing and interpreting large amounts of data to identify ways to help a business improve operations and gain a competitive edge over rivals. Continue Reading
Machine learning tools are becoming a more common component of advanced analytics applications, especially in big data environments. But they have to be focused on real business issues. Continue Reading
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In this video, Sumit Sarkar from Progress Software discusses the benefits of a marketing data lake and explains how companies can determine what data to feed into a data lake. Continue Reading
The SAS Enterprise Miner data mining tool helps users develop descriptive and predictive models, including components for predictive modeling and in-database scoring. Continue Reading
KNIME offers open source data analytics, reporting and integration tools, as well as commercial software that can help build more efficient workflows. Continue Reading
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More data almost always makes deep learning projects more effective. One data science manager says there's essentially no limit to the amount of data he wants to have access to for his team's projects. Continue Reading
Experienced users of machine learning tools share how their organizations are using the technology to solve a variety of analytics problems in their businesses and for customers. Continue Reading
In this episode of the Talking Data podcast, find out how data science teams at Cisco and LinkedIn navigate the process of doing advanced analytics work in an accessible way. Continue Reading
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Having data scientists build analytical models doesn't do much for an organization if the models don't help generate business benefits. Here are some ways to make sure they do. Continue Reading
Big data environments based on technologies such as Hadoop and Spark are being deployed more widely -- and the same goes for advanced analytics tools that can help organizations make effective use of the data flooding into those systems. In fact, ... Continue Reading
Many modern consumers and workers are always tuned-in to the digital world. They have laptops, tablets and smartphones that chirp and beep away with incoming messages. Those devices are also sending out information -- tweets and texts, yes -- but ... Continue Reading