For a simplistic view of data processing architectures, we can draw an analogy with the structure and functions of a house. The foundation of the house is the data management platform that provides ...

Using workarounds to pipe data between systems carries a high price and untrustworthy data. Bharath Chari shares three possible solutions backed up by real use cases to get data streaming pipelines ...

Machine learning workloads require large datasets, while machine learning workflows require high data throughput. We can optimize the data pipeline to achieve both. Machine learning (ML) workloads ...

As the volume, variety, and velocity of data continue to grow, the need for intelligent pipelines is becoming critical to business operations. Provided byDell Technologies The potential of artificial ...

There’s a reason that companies are leveraging the power of data everywhere they can. In fact, data is predicted to be part of “every decision, interaction and process,” by 2025, according to a ...

Organizations today flourish or fade by data. As market research, product development and service delivery all go digital, the role of data grows to constitute the entire business, as it already does ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Cory Benfield discusses the evolution of ...