Pipeline development cycles are shortened from months to weeks or days. SQL’s widespread adoption lets data users self-serve pipelines for fresh analytics. No Java, Python, Spark or Airflow ...

SQL has dominated data querying for decades. Newer query languages offer more elegance, simplicity, and flexibility for modern use cases. For the last three decades, databases and Structured Query ...

According to Databricks, the new service will enable data engineers and analysts to easily create batch and real-time streaming pipelines using SQL and Python ... will streamline the process of taking ...

With Apache Spark Declarative Pipelines, engineers describe what their pipeline should do using SQL or Python, and Apache Spark handles the execution.

Data science and machine learning professionals have driven adoption of the Python programming language, but data science and machine learning are still lacking key tools in business and has room ...

using SQL, Python, or Scala. When the user is finished with her pipeline, she names the output file, specifies whether the pipeline is read-only or can overwrite itself, and presto – she’s presented ...

As the largest health provider in the world, the NHS holds an unparalleled amount of health data, which scientists ... The tools are built in Python, SQL, and Docker, with additional statistical ...

Google is extending differential privacy capabilities to the Python language, with an open source tool, called PipelineDP, for creating pipelines that aggregate data containing personal ...