There are still a lot of obstacles to building machine learning models and one of those is that in order to build those models, developers often have to move a lot of data back and forth between their ...

Cloud computing is rapidly expanding, with next-gen action on the horizon, app developers building data apps and infrastructure emerging. Meanwhile, everyone is talking about next-level generative ...

One key to efficient data analysis of big data is to do the computations where the data lives. In some cases, that means running R, Python, Java, or Scala programs in a database such as SQL Server or ...

Google is abandoning its homegrown SQL variant as the recommended default query language for its BigQuery service in favor of a new standard-compliant dialect in the works for the managed data ...

Google is integrating its Gemini 1.0 Pro large language model with its AI and machine learning platform, Vertex AI, to help enterprises unlock new capabilities of large language models (LLMs), ...

Google LLC today introduced speed-boosting capabilities for its BigQuery cloud data warehouse that it says will enable enterprises to run analytics workflows four to five times faster in some cases.

Microsoft's drive to put Azure SQL Data Warehouse on more equal footing with SQL Server is finally paying off. Azure SQL Data Warehouse gets less press than its online transaction processing brethren, ...

We recently looked at the idea of the data lake, so now it’s time to head downstream and look at data warehouses. We’ll define data warehouses, look at the data types they comprise, the storage they ...

AI is shaping every field by making skills (such as coding or data visualization) accessible to everyone, which weren’t available in the past. An AI operator who can run the right prompts can perform ...