Graphs and data visualizations are great ways of bringing data to life and communicating key insights at a simple glace. However, unless graphs, charts and dials are extremely well designed many ...

To automate data cleaning and transformation, datasets and their corresponding notebooks were extracted from Kaggle, their information was abstracted before being uploaded into a knowledge graph.

Uptake on graphs is set to continue because data management is increasingly about connected use cases. After all, many of the best AI-graph commercial use cases didn’t exist 20 years ago.

His research is on data management and machine learning for the emerging problems in large graphs. He is an IEEE senior member and an ACM distinguished speaker. Arijit is the recipient of the IBM Ph.D ...

“It’s a great algorithm,” said Erik Demaine, a computer scientist at the Massachusetts Institute of Technology. “It’s very fast, simple and easy to implement.” To put this procedure into practice, you ...

Knowledge Graphs, by contrast, represent data as a network of nodes (entities) and edges (relationships). They can handle more complex, nuanced queries based on the types of connections, the ...