Alation

MARCH 29, 2022

Reports required a formal request of the few who could access that data. The 1980s ushered in the antithesis of this version of computing — personal computing and distributed database management — but also introduced duplicated data and enterprise data silos. The request model started to fray.

Business Intelligence 96

Business Intelligence Reporting Data mining Data-driven 96

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 55

Machine Learning Data Science Statistics Deep Learning 55

Jet Global

DECEMBER 23, 2020

An evolving toolset, shifting data models, and the learning curves associated with change all create some kind of cost for customer organizations. For nearly two decades, Microsoft has been managing a portfolio of ERP solutions for small and mid-sized enterprises (SMEs).

Cost-Benefit 52

Cost-Benefit Data Warehouse Reporting Recreation/Entertainment 52

Domino Data Lab

APRIL 3, 2019

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). for DG adoption in the enterprise. Rinse, lather, repeat.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109