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Showing posts with the label data engineer career path

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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 Essential IT Skills for Data Engineers

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Data engineers need the following skills. These skills help you get nice job in any analytics company. Photo Credit: Srini Five Top Skills Need Skill-1 Experience working with big data tools such as MapReduce, Pig, Spark, Kafka and NoSQL data stores such as MongoDB, Cassandra, HBase, etc. Skill-2 Expertise in multi-structured data modeling, reporting on NoSQL & structured database technologies such as HBase and Cassandra, SQL. Skill-3 Experience with languages such as Python, Perl, Ruby, Java, Scala, R etc. Skill-4 Strong data & visual presentation skills and ability to explain insights using tools like tableau, D3 charts or other tools. Skill-5 Basic knowledge and experience of statistical analysis tools such as R.