Artificial Inteligence Big Data Business Analytics Survey 
TechCrunch
MAY 9, 2022
By handling large amounts of data to analyze and benchmark lines of business, BI promises to help identify, develop, and otherwise create new revenue opportunities. Pervasive BI remains elusive, but statistics on the category reveal that about a third of employees use BI tools for analytics to inform strategy.
TechCrunch
AUGUST 2, 2022
xCash flows freely where it concerns enterprise analytics — the global big data and business analytics segment could be worth nearly $700 billion by 2030, depending on which analyst you place your faith in. Unsupervised, Pecan.ai
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CTOvision
JUNE 3, 2014
SAN JOSE, Calif. , June 3, 2014 /PRNewswire/ – Hadoop Summit – According to the O’Reilly Data Scientist Salary Survey , R is the most-used tool for data scientists, while Weka is a widely used and popular open source collection of machine learning algorithms. Product Availability.
Gorilla Logic
MAY 19, 2021
Monetize data with technologies such as artificial intelligence (AI), machine learning (ML), blockchain, advanced data analytics , and more. CIO.com notes that it took employers an average of 109 days to fill roles in machine learning and AI, compared to 44 days to fill jobs in general. .
Altexsoft
SEPTEMBER 6, 2018
Data science and artificial intelligence are hot media topics. An expert talking about the capabilities of predictive analytics for business on a morning TV show is far from unusual. Articles covering AI or data science in Facebook and LinkedIn appear regularly, if not daily. Big data analysis.
CTOvision
OCTOBER 18, 2013
With the continuous development of advanced infrastructure based around Apache Hadoop there has been an incredible amount of innovation around enterprise “Big Data” technologies, including in the analytical tool space. H2O by 0xdata brings better algorithms to big data. This is great for analysts!
Altexsoft
FEBRUARY 8, 2021
Supply chain practitioners and CEOs surveyed by 6river share that the main challenges of the industry are: keeping up with the rapidly changing customer demand, dealing with delays and disruptions, inefficient planning, lack of automation, rising costs (of transportation, labor, etc.), Optimization opportunities offered by analytics.
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