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 ...

Even as large language models have been making a splash with ChatGPT and its competitors, another incoming AI wave has been quietly emerging: large database models. Even as large language models have ...

NoSQL entered the scene nearly six years ago as an alternative to traditional relational databases. The offerings from the major relational vendors couldn’t cut it in terms of the cost, scalability, ...

Snowflake has thousands of enterprise customers who use the company's data and AI technologies. Though many issues with generative AI are solved, there is still lots of room for improvement. Two such ...

One of the biggest challenges facing organizations today is making sure that the right information gets to the right people. It requires attention, diligence, and planning to ensure that data is used ...

Enterprises are creating huge amounts of data and it is being generated, stored, accessed, and analyzed everywhere – in core datacenters, in the cloud distributed among various providers, at the edge, ...

“Tabular data” is a broad term that encompasses structured data that generally fits into a specific row and column. It can be an SQL database, a spreadsheet, a .CSV file, etc. While there has been ...

Last month, Microsoft announced Data Amp, a online event focusing on its Data Platform and AI initiatives. Data Amp is taking place today, and with it come a slew of announcements. Python has emerged ...

Big data is less predictable than traditional data, and therefore requires special consideration when building models. Here are some things to keep in mind. Image: iStock/z_wei Data modeling is a ...