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Something Would Free Data Scientists from Heavy Coding Work

  • SQL code becomes complicated in complex situations which makes it hard to debug and optimize.
  • Writing complicated SQL statements is a very inconvenient process.
  • Introducing esProc SPL as a tool for structured data processing which is both simple and versatile.
  • SPL is a proprietary file format that is portable.
  • SPL supports big data processing, in-memory computation and can perform parallel processing.
  • Python has many limitations, Python struggles with datasets larger than the available memory.
  • SPL supports a wide range of high-performance algorithms and thus can achieve a dramatic skyrocketing on computational performance.
  • Python does not have any big data processing capabilities and is time-consuming in processing big data.
  • SPL comprehensively offers debugging capabilities including Set breakpoint, Run to cursor, Step over, etc.
  • Both SQL and Python are not satisfactory enough for data processing.

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