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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

5 Key Ideas on SAS Banking Analytics

SAS is providing solutions for banking. Getting away with financial crime just got harder. The latest SAS Financial Crimes Suite arms institutions to detect potential suspicious activity more efficiently than ever.
A new customer due diligence solution within the suite more accurately detects changes in a customer’s risk profile. Enhanced anti-money laundering and case management capabilities also make it easier to have a complete view of threats across an institution’s financial crimes investigation unit.

“A comprehensive view of potential threats will help in efforts to thwart criminals from successful attempts of hiding illicit funds,” says James Wester, global payments research director at IDC Financial Insights.

 “A technology infrastructure with customer risk rating and high-performance analytics will help speed detection and investigation in all channels.”.

SAS Analytics Suite for Banking Crimes

  1. Today’s rigorous regulatory environment requires banks to move quickly with confidence. SAS Financial Crimes Suite uses a visual scenario designer to recommend optimal detection models. The designer instantly assesses the impact of potential scenarios and risk-rating changes.
  2. In-memory architecture speeds analysis of real-time testing environments, reducing guesswork through improved model efficiency. 
  3. To identify potential money launderers and people funneling money to terrorists, institutions must constantly assess customer activity. The SAS Customer Due Diligence does this by weighing all customer data to set baseline expectations. 
  4. Data management features easily integrate key customer attributes from external sources and detect incriminating relationships. 
  5. The regulatory reporting interface controls both workflow and investigations. Context-aware analytics intercept and assess events for possible risk. The resulting baseline customer score can be automatically updated with a new risk rating based on behavior changes
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