AI News

MARCH 12, 2025

Key components of data security platforms Effective DSPs are built on several core components that work together to protect data from unauthorised access, misuse, and theft. Data discovery and classification Before data can be secured, it needs to be classified and understood. The components include: 1.

Data Discovery 263

Data Discovery Categorization Automation Machine Learning 263

Marktechpost

MARCH 22, 2024

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.

Machine Learning 135

Machine Learning Explainability Categorization ETL 135

Flipboard

OCTOBER 25, 2023

Why it’s challenging to process and manage unstructured data Unstructured data makes up a large proportion of the data in the enterprise that can’t be stored in a traditional relational database management systems (RDBMS). Understanding the data, categorizing it, storing it, and extracting insights from it can be challenging.

ML 166

ML Metadata Data Extraction AI 166

Pickl AI

JUNE 13, 2024

Summary: Feeling overwhelmed by your data? Data classification is the key to organization and security. This blog explores what data classification is, its benefits, and different approaches to categorize your information. Discover how to protect sensitive data, ensure compliance, and streamline data management.

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Categorization Automation Data Discovery Algorithm 52

AWS Machine Learning Blog

AUGUST 22, 2024

For each summary presented to the clinical expert, they were asked to categorize it as either good, acceptable, or bad. The evaluation questions also collected feedback on the number of hallucinations and inaccurate or not helpful information.

Generative AI 112

Generative AI Auto-complete Software Development Automation 112

Pickl AI

JUNE 11, 2024

Bar Charts Categorical data, like eye colour or customer preference for a product brand, thrives with bar charts. These charts visually represent each category’s frequency or proportion of data points. However, use colour judiciously, considering colour blindness and ensuring colour choices effectively represent the data.

Data Analysis 52

Data Analysis Categorization Data Science Data Discovery 52

Pickl AI

OCTOBER 14, 2024

Median: The middle value in a dataset, helping to understand the data’s distribution. Mode: The most frequent value, useful in categorical data. Applications Descriptive Data Analysis is widely used in business reporting and dashboards. Clustering: Grouping similar data points to identify segments within the data.

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Data Analysis Data Mining Data Discovery Machine Learning 52