The Infor Blog

Category:  Data science

Redefining business intelligence for the enterprise
June 1, 2017

Taking a networked approach, employing data science, and putting user needs first, Infor and Birst are positioned to redefine business intelligence for the next generation.

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Machine learning lets finance turn data insights into action
April 26, 2017

Machine learning can uncover valuable and actionable insights in your data streams—maybe even better than a team of data scientists.

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Is digital transformation just the next tech hype?
April 25, 2017

Weren’t we all just talking about cloud? But just like cloud, digital transformation is real and viable — and here to stay. Here’s how to start.

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With HTAP, planning and execution come together for faster insights
April 6, 2017

Hybrid transaction / analytical processing (HTAP) platforms help deliver on the promise of IoT data to provide fast insights.

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Data visualization enters a new dimension
March 20, 2017

Augmented reality and three-dimensional visualizations will help us perform the delicate dance of gleaning actionable insights from a sea of data.

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In retail, new technology is even reinventing old technology and its data
February 6, 2017

IoT technology will allow for new in-store retail experiences—and even augment the value of existing data.

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To pave the way for smart cities, data sharing in our connected communities must be a two-way street
January 26, 2017

The first wave of autonomous cars foreshadows an inevitable truce between a user’s privacy and the value of our collective data for the greater good.

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Lesson from the pitch: take data viz insights one step at a time
November 14, 2016

Analytics help to identify patterns that can lead to success. Just don’t rush to connect all the dots at once.

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Seeing the big picture on guest activity
November 7, 2016

Total revenue management and digital transformation combine to help hospitality providers understand and impact guest behaviors.

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Coloring the perception of data
October 14, 2016

Creating effective data visuals requires an understanding of color—its aesthetic elements and its relationship to the data.

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