O'Reilly on Data

MAY 21, 2019

Here are some typical ways organizations begin using machine learning: Build upon existing analytics use cases: e.g., one can use existing data sources for business intelligence and analytics, and use them in an ML application. Metadata and artifacts needed for audits. Use ML to unlock new data types—e.g., images, audio, video.

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238

CIO Business Intelligence

JUNE 23, 2022

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Common security, governance, metadata, replication, and automation enable CDP to operate as an integrated system. We live in a hybrid data world.

IT 77

IT Data Architecture Unstructured Data Big Data 77

Domino Data Lab

APRIL 3, 2019

That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Note that data warehouse (DW) and business intelligence (BI) practices both emerged circa 1990. Fun fact: in 2011 Google bought remnants of what had previously been Motorola.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Alation

FEBRUARY 20, 2020

While this requires technology – AI, machine learning, log parsing, natural language processing,metadata management, this technology must be surfaced in a form accessible to business users – the data catalog. 7] Harvard Business Review, Category Creation Is the Ultimate Growth Strategy, Eddie Yoon, September 26, 2011.

Machine Learning 52

Machine Learning Marketing Reporting ROI 52