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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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Old School Guide Data Analyst Responsibilities

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The results of your analysis may be super meaningful and obvious to you, but they won’t be to anyone else. That’s because you know what questions you were looking to answer when you set out to do the analysis in the first place.


Your Role-You know exactly what data the dataset includes and excludes. Plus you wrote the queries that ultimately produced the visualization or report you’re looking at. That’s a lot of contexts that you need to share in order for other people to understand what the numbers mean.


Sharing Results-When sharing the results of your analysis, write out the conclusions you are drawing from the data and what business actions you think should be taken as a result of the analysis (e.g. our conversion decreased with this latest release and we should rollback). Not only do other folks perhaps not have the context to interpret the data correctly, they probably don’t find it as fascinating as you do and may not have the time to derive meaning from the data.




Communication Skills-Not to hammer on it too much, but communication skills are so important for this role. Around half of the analyst’s time needs to be spent on communications. It takes quite a bit of time to explain and summarize the results and conclusions you’ll draw from your data. 


If the results of your analysis are sleeping in people’s inboxes, you’re not doing it right. Sometimes you may be the only person in the organization who knows about a problem or opportunity, and it’s your responsibility to make sure the organization is responding appropriately to what you’ve learned. Sometimes you gotta be the squeaky wheel. Don’t underestimate the value of your work.


Your Time-If analysis work is something you repeatedly run out of time to do, try getting it added to your official job description and dedicating a certain number of hours per week or per month to it. Block it off on your calendar.


Data Value-You’s going to be collecting lots of interesting data, but it won’t be very valuable unless someone uses it! You’ll need at least one person on your team who is very curious about what that data might reveal. I call these people analysts. Very often the analyst is a developer, product manager, or someone on the product or marketing team.


Analytics-Not only will these folks be dying to see the results of the business questions they set out to answer, they will be continuously thinking up new questions. Analysts love digging into the data you collected in the first phase of the project and will have a lot of ideas of what new things you can collect in the next phase. 


In other words, you need people on your team who enjoy the practice of analytics. Skills-Don’t worry, there are lots of people out there who do:): Having a technical background will be a huge asset for this person as they will quickly learn how to build queries to get the results they need.


This role is absolutely critical for your success because if you don’t have people who want to learn from your data, you won’t be able to extract any value from it.


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