Without data, enterprise AI isn't going to be successful. Getting all the data in one place and having the right type of data tools, including connections to different types of databases is a critical ...

The deep learning-based approaches to Tabular Data Learning (TDL), classification and regression, have shown competing performance, compared to their conventional counterparts. However, the latent ...

In the age when data is everything to a business, managers and analysts alike are looking to emerging forms of databases to paint a clear picture of how data is delivering to their businesses. The ...

Real-world data is often costly, messy, and limited by privacy rules. Synthetic data offers a solution—and it’s already widely used: SDV (Synthetic Data Vault) is an open-source Python library that ...

Neo4j Inc. today announced a new serverless offering that dramatically simplifies the deployment of its graph database offering, making it easier to use with artificial intelligence applications. Most ...

Ego-centric searches are essential in many applications, from financial fraud detection to social network research, because they concentrate on a single vertex and its immediate neighbors. These ...

Abstract: The unprecedented success of deep learning has revolutionized the imputation mechanism of missing values in tabular data, typically caused by data corruption and sensor noise. One promising ...

Databricks, the analytics and AI giant, has acquired data management company Tabular for an undisclosed sum. (CNBC reports that Databricks paid over $1 billion.) According to Tabular co-founder Ryan ...