Cloudera

AUGUST 6, 2018

In recent years, we have heard a great deal about how new and sophisticated understanding of how to interpret the onslaught of data produced in the modern age could help us turn the corner on major social and environmental problems. While we have been using data to improve philanthropy for years, a great deal has changed very quickly.

Machine Learning 49

Machine Learning Internet of Things Cost-Benefit Data-driven 49

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. The term “AI,” meanwhile, is No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

datapine

NOVEMBER 19, 2019

No matter if you need to conduct quick online data analysis or gather enormous volumes of data, this technology will make a significant impact in the future. An exemplary application of this trend would be Artificial Neural Networks (ANN) – the predictive analytics method of analyzing data.

Technology 279

Technology Internet of Things IT IoT 279

Domino Data Lab

MAY 8, 2019

For example, common practices for collecting data to build training datasets tend to throw away valuable information along the way. The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. 2018-06-21). ML model interpretability and data visualization.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Sisense

JUNE 9, 2021

Like pretty much everything else in the world, football has become more data-driven than ever, so when the 24 teams set out to win the championship on 11 June , you can bet your bottom Euro that each team’s tactics, formation, and training will be shaped by a mountain of data. We can’t wait!

Analytics 98

Analytics Data-driven Internet of Things Measurement 98

Smart Data Collective

APRIL 2, 2019

The use of digital and machine learning processes has helped foster a revival among the titans of energy through connecting and modernizing older systems, incorporating innovative technologies, and leveraging data in new ways. Relying on multiple systems and data sources can hinder visibility during projects, field work, and turnarounds.

Machine Learning 83

Machine Learning Internet of Things Digital Transformation IoT 83

datapine

NOVEMBER 27, 2019

Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 1) Data Quality Management (DQM). We all gained access to the cloud.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

IBM Big Data Hub

FEBRUARY 9, 2024

But the most impactful developments may be those focused on governance, middleware, training techniques and data pipelines that make generative AI more trustworthy , sustainable and accessible, for enterprises and end users alike. iii] “AI models haven’t had that kind of data before.

Cost-Benefit 105

Cost-Benefit Modeling Data-driven Enterprise 105