IBM Big Data Hub

JULY 6, 2023

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.

Machine Learning 56

Machine Learning Data Science Statistics Deep Learning 56

Domino Data Lab

JULY 22, 2019

The data governance, however, is still pretty much over on the data warehouse. Toward the end of the 2000s is when you first started getting teams and industry, as Josh Willis was showing really brilliantly last night, you first started getting some teams identified as “data science” teams. All righty.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

APRIL 3, 2019

Probably the best one-liner I’ve encountered is the analogy that: DG is to data assets as HR is to people. Also, while surveying the literature two key drivers stood out: Risk management is the thin-edge-of-the-wedge ?for Most of the data management moved to back-end servers, e.g., databases. We keep feeding the monster data.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84