The challenges of integrating time-series data into data lakes can be overcome by using the right architecture and providing the appropriate metadata.
In a market where companies routinely get late-stage funding of $100 million or more, DataBricks again shows the strong investor interest in AI data platforms.
In this week's real-time analytics news: A machine learning scholarship program train the next generation of ML leaders, a virtual ML-for-good hackathon, and …
IoT platforms are being used to perform multiple functions to keep critical services running and facilities operational.
Many enterprises are realizing that the price tag of moving to the cloud can get pretty high, and are looking to implement cost controls.
The GridGain Data Lake Accelerator is designed for real-time performance and comprehensive
AnalyticsXtreme offers 100X faster data lake access and speeds up machine learning on both real-time and historical
How one big retail chain moved its data warehouse to a Hadoop
With data-driven companies, project bottlenecks are often the size and shape of your own data team. Here's how data-as-a-service might help unplug
What are the challenges you need to tackle to keep your data lake from becoming an unwieldy “data