Building an analytics architecture for unstructured data and multimodal AI brandpost By Ganesh Kumar Gella, Sr. Director, Engineering, Google BigQuery Generative AI Initiatives Jun 11, 2025 5 mins ...

The tide is changing for analytics architectures. Traditional approaches, from the data warehouse to the data lake, implicitly assume that all relevant data can be stored in a single, centralized ...

Big data is a moving target, and it comes in waves: before the dust from each wave has settled, new waves in data processing paradigms rise. Streaming, aka real-time / unbounded data processing ...

This project involves: Data Architecture: Designing a Modern Data Warehouse Using Medallion Architecture Bronze, Silver, and Gold layers.; ETL Pipelines: Extracting, transforming, and loading data ...

A technical paper titled “Darwin: A DRAM-based Multi-level Processing-in-Memory Architecture for Data Analytics” was published by researchers at Korea Advanced Institute of Science & Technology (KAIST ...

Data Warehouse and Analytics Project Welcome to the Data Warehouse and Analytics Project repository! 🚀 This project demonstrates a comprehensive data warehousing and analytics solution, from building ...

Azure Synapse uses a massively parallel processing architecture ideal for enterprise data warehousing, while Databricks leverages Spark’s in-memory processing for real-time analytics and AI ...

That's because advances in big data analytics and complex events processing (CEP) can come together to provide deep and real-time, pattern-based insights into large-scale IT operations.