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Salam noted that organizations are offloading computational horsepower and data from on-premises infrastructure to the cloud. This provides developers, engineers, datascientists and leaders with the opportunity to more easily experiment with new data practices such as zero-ETL or technologies like AI/ML.
This has created many different data quality tools and offerings in the market today and we’re thrilled to see the innovation. People will need high-quality data to trust information and make decisions. The Lineage & Dataflow API is a good example enabling customers to add ETL transformation logic to the lineage graph.
Stefan is a software engineer, datascientist, and has been doing work as an ML engineer. He also ran the data platform in his previous company and is also co-creator of open-source framework, Hamilton. To a junior datascientist, it doesn’t matter if you’re using Airflow, Prefect , Dexter.
Data Science focuses on analysing data to find patterns and make predictions. Data engineering, on the other hand, builds the foundation that makes this analysis possible. Without well-structured data, DataScientists cannot perform their work efficiently.
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