Domino Data Lab

OCTOBER 7, 2020

Statistics developed in the last century are based on probability models (distributions). This approach provides an automatic and objective strategy for decision making under defined assumptions about the data. This model for data analytics has proven highly successful in basic biomedical research and clinical trials.

Statistics 145

Statistics Testing Predictive Modeling Big Data 145

Domino Data Lab

JULY 28, 2021

Data science is a field that uses math and statistics as part of a scientific process to develop an algorithm that can extract insights from data. All models are not made equal. At this stage, data scientists begin writing code for computation and model-building.

Data Science 110

Data Science Statistics Predictive Analytics Recreation/Entertainment 110

Smarten

APRIL 19, 2024

Assisted Predictive Modeling and Auto Insights to create predictive models using self-guiding UI wizard and auto-recommendations The Future of AI in Analytics The C=suite executive survey revealed that 93% felt that data strategy is critical to getting value from generative AI, but a full 57% had made no changes to their data.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

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.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

Alation

APRIL 14, 2022

Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth. And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business.

Metadata 59

Metadata Data Governance Data-driven Modeling 59

IBM Big Data Hub

MAY 17, 2024

Poorly run implementations of traditional or generative AI technology in commerce—such as deploying deep learning models trained on inadequate or inappropriate data—lead to bad experiences that alienate both consumers and businesses.  The applications of AI in commerce are vast and varied.

B2B 64

B2B Interactive Optimization Data-driven 64

IBM Big Data Hub

OCTOBER 16, 2023

Machine learning in marketing and sales According to Forbes , marketing and sales teams prioritize AI and ML more than any other enterprise department. Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO).

Machine Learning 48

Machine Learning Marketing Forecasting Modeling 48

O'Reilly on Data

SEPTEMBER 11, 2019

2 in frequency in proposal topics; a related term, “models,” is No. Terms that relate to data engineering, data management, and data analytics dominate the top tiers of proposal topics. For example, even though ML and ML-related concepts —a related term, “ML models,” (No. The term “ML” is No.

IoT 25

IoT Big Data Data Warehouse Uncertainty 25

IBM Big Data Hub

FEBRUARY 14, 2024

Energy Companies in the energy sector can increase their cost competitiveness by harnessing AI and data analytics for demand forecasting, energy conservation, optimization of renewables and smart grid management. AI platforms can use machine learning and deep learning to spot suspicious or anomalous transactions.

Cost-Benefit 82

Cost-Benefit Insurance Machine Learning Unstructured Data 82