2019 Artificial Inteligence Business Analytics Machine Learning 
Cloudera
MAY 27, 2021
An authoritarian regime is manipulating an artificial intelligence (AI) system to spy on technology users. The public at large doesn’t know how algorithms work, so when technology acts in unexpected ways, it frustrates users. It’s not the machine’s fault. Big data and AI amplify the problem.
CIO
MARCH 27, 2024
Le aziende italiane investono in infrastrutture, software e servizi per la gestione e l’analisi dei dati (+18% nel 2023, pari a 2,85 miliardi di euro, secondo l’Osservatorio Big Data & Business Analytics della School of Management del Politecnico di Milano), ma quante sono giunte alla data maturity?
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Cloudera
FEBRUARY 8, 2021
billion in 2019, and is projected to reach $225.16 In addition, moving outside the vehicle, existing fragmented approaches for data management associated with the machine learning lifecycle are limiting the ability to deploy new use cases at scale. billion by 2027, registering a CAGR of 17.1% from 2020 to 2027.
Cloudera
NOVEMBER 16, 2020
million in 2019 to $7.9 from 2019 to 2024. The sizable impact from fraud on the insurance market is increasingly being addressed by fraud detection, prevention, and mitigation technology tools and services, creating a substantial fraud detection market. million by 2024, a CAGR of 25.8%
CIO
APRIL 15, 2022
According to CIO’s State of the CIO 2022 report, 35% of IT leaders say that data and business analytics will drive the most IT investment at their organization this year. And 20% of IT leaders say machine learning/artificial intelligence will drive the most IT investment.
Altexsoft
JULY 3, 2020
The hospitality industry evolved into various businesses that propose different customer experiences by adopting new technologies, practices, and cultural trends. Machine learning allowed hotels and rental services to personalize offers and services. The adoption of, say, IoT devices gave us new ways to collect and process data.
Altexsoft
JANUARY 26, 2022
They commonly prepare data and build machine learning (ML) models. A big chunk of their work includes helping businesses get better insights and make predictions based on data. Such specialists use Python and programming languages for statistical analysis like R and SAS.
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