First, we’ll define and demystify these terms. Second, I’ll share some key business use cases that cannot be solved with traditional relational data catalogs. Finally, I’ll wrap it up by getting ...

Data Fabric Forrester analyst Noel Yuhanna was among the first individuals to define the data fabric back in the mid-2000s. Conceptually, a big data fabric is essentially a metadata-driven way of ...

Anaconda created a stir over a year ago when it began charging large commercial users a fee for access to its popular collection of Python tools. The change, it said, was necessary to offset the costs ...

One factor driving information overload is just how many sources exist, with 26% of U.S. workers reporting using eleven or more accounts, resources, tools, and applications each day. From emails, ...

The technology lab for the world’s largest company was pitted against an existing demand forecasting system that was developed by JDA Software. That system was no slouch, but Walmart’s internal ...

To get the low down on this high tech, we tapped the knowledge of the smart folks at Nexla, a developer of tools for managing data and converting formats. Nexla CTO and co-founder Jeff Williams and ...

Similarly, the number of people actively searching for data and analytics positions in late 2021 decreased dramatically as openings proliferated, according to the UK recruiter Harnham. “Vacancies are ...

“The United States government is mandating their agencies to it, but industry as well as going to need to be doing this migration. The migration is not going to be easy [and] it’s not going to be pain ...

Stonebraker–who led the teams that created several databases (Ingres, Postgres, Vertica, VoltDB, SciDB) over the years and also won a Turing Award for his work–is known for out-of-the-box thinking and ...

But just having an open lakehouse isn’t enough, just like having the world’s most advanced smartphone isn’t enough. One would also like to have a variety of pre-built apps, AI models, third-party data ...

Data scientists spend about 45% of their time on data preparation tasks, including loading and cleaning data, according to a survey of data scientists conducted by Anaconda. The company also analyzed ...

3. Lack of Processing Capacity Not only do users need powerful GPUs to train GenAI models, but they also need them for inference. The huge demand for high-end GPUs from Nvidia has outstripped supply ...