In an era where data is a strategic asset, organizations often falter not because they lack data—but because their ...

Who needs rewrites? This metadata-powered architecture fuses AI and ETL so smoothly, it turns pipelines into self-evolving ...

Committed to addressing the challenges of outdated documentation and fragmented data processes, it aims to streamline data model design, change management, and integration, ensuring transparency ...

This streamlines data estates, facilitates collaboration, enables the creation of generative AI (genAI) models that can access your data estate’s semantic meaning, and ensures everything is ...

Data scientists today face a perfect storm: an explosion of inconsistent, unstructured, multimodal data scattered across silos – and mounting pressure to turn it into accessible, AI-ready insights.

Ajay Kumar Kota continues to set new benchmarks in the dynamic realm of data architecture, dashboard development, and ...

Asia Banu Shaik has spent the better part of two decades engaging in this field, utilizing her experience in data architecture and engineering to enable modernization initiatives. In her previous ...

Data Collection and Preparation: Data preparation is an important step in training an AI model and includes organizing data into a format that can be used to create effective AI models.