Showing posts with the label r-vs-sas

Featured Post

8 Ways to Optimize AWS Glue Jobs in a Nutshell

  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 Top R Vs SAS Differences

Statistical analysis should know by every software engineer. R is an open source statistical programming language. SAS is licensed analysis suite for statistics. The two are very much popular in Machine learning and data analytics projects. SAS is an Analysis-suite software and R is a programming language. 1. R Language R supports both statistical analysis and Graphics R is an open source project. R is 18th most popular Language R packages are written in C, C++, Java, Python and.Net R is popular in Machine learning, data mining and Statistical analysis projects. a). R Advantages R is flexible since a lot of packages are available. R is best suited for data related projects and  Machine learning . Less cost since it is open source language. R Studio is the best tool to develop R programming modules. Ref: (read more advantages) b). R Disadvantages R language architecture model is out of date. So may not use it for critical applications. R is not suitable for Serve