Corinium

JUNE 6, 2019

Moreover, rapid and full adoption of analytics insights can hit speed bumps due to change resistance in the ways processes are managed and decisions are made. In the long run, we see a steep increase in the proliferation of all types of data due to IoT which will pose both challenges and opportunities.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: predictive maintenance, log data pipeline optimization, connected vehicles, industrial IoT, fraud detection, patient monitoring, network monitoring, and more. Data for Enterprise AI: E xperian BIS — Improving the accuracy of commercial data aggregation with data science and machine learning.

Digital Transformation 70

Digital Transformation Machine Learning Optimization Data Lake 70

Cloudera

AUGUST 28, 2018

From AI models that power retail customer decision engines to utility meter analysis that disables underperforming gas turbines, these finalists demonstrate how machine learning and analytics have become mission-critical to organizations around the world. Enterprise Machine Learning. TECHNICAL IMPACT.

Digital Transformation 65

Digital Transformation Machine Learning Consulting IoT 65

Rocket-Powered Data Science

JULY 14, 2023

The criticality of these synergies becomes obvious when we recognize analytics as the products (the outputs and deliverables) of the data science and machine learning activities that are applied to enterprise data (the inputs).

Analytics 166

Analytics Internet of Things Prescriptive Analytics Data Science 166

Cloudera

MARCH 6, 2018

The real power in machine learning and analytics is when multiple analytics disciplines are able to work together in concert, sharing data in service of solving more complex and more valuable questions. This puts the burden on the users to determine how to unify complex workflows.

Analytics 40

Analytics Metadata Recreation/Entertainment Big Data 40