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8 Ways to Optimize AWS Glue Jobs in a Nutshell

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  Improving the performance of AWS Glue jobs involves several strategies that target different aspects of the ETL (Extract, Transform, Load) process. Here are some key practices. 1. Optimize Job Scripts Partitioning : Ensure your data is properly partitioned. Partitioning divides your data into manageable chunks, allowing parallel processing and reducing the amount of data scanned. Filtering : Apply pushdown predicates to filter data early in the ETL process, reducing the amount of data processed downstream. Compression : Use compressed file formats (e.g., Parquet, ORC) for your data sources and sinks. These formats not only reduce storage costs but also improve I/O performance. Optimize Transformations : Minimize the number of transformations and actions in your script. Combine transformations where possible and use DataFrame APIs which are optimized for performance. 2. Use Appropriate Data Formats Parquet and ORC : These columnar formats are efficient for storage and querying, signif
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7 top initial steps you need before you start HR predictive analytics

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Top criteria you need before you start analytics in the Human Resource department. I am sure you need many approvals to start analytics in HR.
hr analytics

The risks involved to start analytics in the Human Resource department

  1. You must comply with the legal requirements in which you operate as it relates to the use of people data. The reason is the analytical insights should reflect the cultural and social marks of your organization.
  2. You need to get involved all stakeholders involved and what the cost of what you're doing is relative to the benefit of doing it.
  3. Use analytics through accountable processes, one of which should be acknowledging that using predictive analytics with the workforce has the potential for negative impact, not just positive impact, Walzer said.
  4. Engage the legal department to make sure you understand any implications before you've done something, not after the fact.
  5. Assess whether the use of analytics involves sensitive areas, which it often will, Walzer said. But, she added, these are often accommodated by using reasonable safeguards.
  6. Know what data you just shouldn't collect. 
  7. One example is prescription drug use of employees. "Many employers have access to it through third-party health care providers, but the idea that you're going to bring it in poses a lot of liability to the organization

References

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