Remove Data Discovery Remove ETL Remove Explainability
article thumbnail

Amazon AI Introduces DataLore: A Machine Learning Framework that Explains Data Changes between an Initial Dataset and Its Augmented Version to Improve Traceability

Marktechpost

DATALORE uses Large Language Models (LLMs) to reduce semantic ambiguity and manual work as a data transformation synthesis tool. Second, for each provided base table T, the researchers use data discovery algorithms to find possible related candidate tables. These models have been trained on billions of lines of code.

article thumbnail

Data platform trinity: Competitive or complementary?

IBM Journey to AI blog

The concepts will be explained. Data lakehouse: A mostly new platform. While traditional data warehouses made use of an Extract-Transform-Load (ETL) process to ingest data, data lakes instead rely on an Extract-Load-Transform (ELT) process. This adds an additional ETL step, making the data even more stale.

article thumbnail

IBM watsonx Platform: Compliance obligations to controls mapping

IBM Journey to AI blog

Through the integrated suite of tools offered by watsonx.governance™, users can expedite the implementation of responsible, transparent and explainable AI workflows tailored to both generative AI and machine learning models. Furthermore, watsonx.ai