Data lakes stink. That's because lots of them turn to data swamps, and swamps stink. What's the difference between a data lake and a data swamp? A data lake is built on top of cost efficient ...

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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 ...

Data is the most valuable asset for modern businesses. For any organization to extract valuable insights from data, that data needs to flow freely in a secure and timely manner across its different ...

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 ...

A headless data architecture means no longer having to coordinate multiple copies of data and being free to use whatever processing or query engine is most suitable for the job. Here’s how it works.