Single Instance, Our ETL system was running on a single EC2 node and we are vertically scaling as and when the need arose.The following are the 3 critical reasons for undergoing a technology transfer, Technology Selection: Kettle vs AWS Glue vs Airflow Deep down in my heart I know if not now, the next customer deployment - i.e larger than the current one is designed to fail. Yet our system rand successfully to cater the needs of my ever-demanding customers. If he has no supporting DevOps and infrastructure team around, that 16 hours shoot north to 18 hours or may be more. Those issues are sufficient for a caring data engineer to keep himself awake for almost 16 hours a day. Stored procedures are the de-facto choice when it comes to data munging, Pls get rid of them.Further, the legacy systems make it almost impossible for the IT team to even simplify the periodical backup(data) process.Delivering reports and analytics from OLTP databases is common even among the large corporations - Significant numbers of companies fail to deploy a Hadoop system or OLTP to OLAP scheme despite having huge funds because of the issues #1 and #2.Assuming software engineers can solve everything and there is no need for a data engineering speciality among the workforce.Low or no funding to invest in tools(and right people) to make life easy for every stakeholder including the paying customer, e.g ETLs, Data Experts, etc.Creating a wow factor is the primary, secondary, and tertiary concern to acquiring new labels, and seldom focusing on the nuances of technology to achieve excellence in delivery Small companies aspire for acquiring major enterprises in their customer list often trivialize the technology problem and treat them as people issues because 0. Those ETL tools came with a conditional free version where the best-of-the-class attorneys fail to understand the conditions. ![]()
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