IBM Big Data Hub

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. appeared first on IBM Blog.

Data science 60

Data science Big data Analytics Mining 60

ARMA International

SEPTEMBER 13, 2021

Some technology trends such as real-time data analytics are on-going, while others are more recent, such as blockchain. AI using machine learning (ML) involves processing samples of data to learn. Then using what was learnt learning to run data analytics on vast amounts of content from many sources. Data Analytics.

Digital transformation 59

Digital transformation Blockchain IT Computer and Electronics 59

ARMA International

SEPTEMBER 22, 2021

Some technology trends such as real-time data analytics are on-going, while others are more recent, such as blockchain. For example, once a health record has met the regulatory requirements, the record can be anonymized and kept for years for such purposes as medical research and predictive analytics. Artificial Intelligence.

Digital transformation 52

Digital transformation Content services IT e-Discovery 52

Robert's Db2

DECEMBER 30, 2016

Noticing these characteristics, developers might start expressing a preference for the data associated with their new applications being stored on the platform with the industrial-strength qualities of service. A friend of mine who is a long-time DB2 for z/OS DBA has a good nickname for the system he supports: the "super-server."

Analytics 48

Analytics Access Cloud Data structuring 48