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 167

ML Metadata Data Extraction AI 167

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 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 130

Data Quality Metadata ETL Big Data 130

Pickl AI

JULY 6, 2023

These work together to enable efficient data processing and analysis: · Hive Metastore It is a central repository that stores metadata about Hive’s tables, partitions, and schemas. Thus, making it easier for analysts and data scientists to leverage their SQL skills for Big Data analysis.

Big Data 52

Big Data Data Analysis ETL Metadata 52

Snorkel AI

JULY 5, 2023

We thought we’d structure this more as a conversation where we walk you through some of our thinking around some of the most common themes in data centricity in applied AI. Is more data always better? Even larger, more established organizations struggle with data discovery and usage. So there are a lot of factors.

Large Language Models 52

Large Language Models Metadata Machine Learning AI 52

Snorkel AI

JULY 5, 2023

We thought we’d structure this more as a conversation where we walk you through some of our thinking around some of the most common themes in data centricity in applied AI. Is more data always better? Even larger, more established organizations struggle with data discovery and usage. So there are a lot of factors.

Large Language Models 52

Large Language Models Metadata Machine Learning AI 52

Snorkel AI

JULY 5, 2023

We thought we’d structure this more as a conversation where we walk you through some of our thinking around some of the most common themes in data centricity in applied AI. Is more data always better? Even larger, more established organizations struggle with data discovery and usage. So there are a lot of factors.

Large Language Models 52

Large Language Models Metadata Machine Learning AI 52