Data lakes and data warehouses are achieving a measure of success in modern data architectures, but the emergence of the data lakehouse offers new challenges and opportunities for database ...

To serve the data analytics and applications for business growth and operational needs, data lakes are being widely adopted as the data infrastructure because of their scalability and flexibility.

Google announced the preview launch of BigLake, a data lake storage engine that makes it easier for enterprises to analyze data in their data warehouses/lakes.

Data lakes were built for big data and batch processing, but AI and machine learning models need more flow and third party connections. Enter the data hub concept that'll likely pick up steam.

While businesses are racing to implement Artificial Intelligence (AI), many overlook a critical factor in success: the quality and structure of the data feeding these models. The reality is that a ...

Companies can use data lakes as a centralized repository to incorporate complex data analytics and machine learning models, transforming raw data into actionable insights.

Microsoft Sentinel data lake is the next step in that journey—built to help security leaders break through the limitations of traditional SIEMs by putting security data at the center of the security ...