Marktechpost

MARCH 12, 2024

Even among datasets that include the same subject matter, there is no standard layout of files or data formats. This obstacle lowers productivity through machine learning development—from data discovery to model training. Database metadata can be expressed in various formats, including schema.org and DCAT.

Metadata 118

Metadata Machine Learning ML Data Discovery 118

Flipboard

OCTOBER 25, 2023

But most important of all, the assumed dormant value in the unstructured data is a question mark, which can only be answered after these sophisticated techniques have been applied. Therefore, there is a need to being able to analyze and extract value from the data economically and flexibly.

ML 166

ML Metadata Data Extraction AI 166

IBM Journey to AI blog

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 130

Metadata Data Quality Data Discovery Data Scientist 130

IBM Journey to AI blog

JANUARY 18, 2023

The concepts will be explained. Data lakehouse: A mostly new platform. Data fabric promotes data discoverability. Here, data assets can be published into categories, creating an enterprise-wide data marketplace. This enables access to data at all stages of its value lifecycle.

Data Platform 130

Data Platform ETL Metadata Data Discovery 130

IBM Journey to AI blog

OCTOBER 30, 2024

The enhanced metadata supports the matching categories to internal controls and other relevant policy and governance datasets. Integrated vectorized embedding capabilities streamline data preparation for various applications such as retrieval augmented generation (RAG) and other machine learning and generative AI use cases.

Prompt Engineering 238

Prompt Engineering Prompt Engineer ETL Machine Learning 238