In the ever-evolving landscape of modern business operations, the seamless integration of data is a main factor for organizations aiming to get insights from diverse sources for analytical, artificial intelligence (AI), and machine learning (ML) workloads. Traditionally, the Extract, Transform, Load (ETL) process has been the cornerstone for preparing and consolidating data into a centralized repository.
Author: Dima Hamed
With over 7 years of experience, Dima Hamed is a data engineer and database administrator with a proven track record of excellence. Holding certifications as a data engineer from AWS, Google, and Azure, Dima is an expert in designing cloud-based data solutions and possesses excellent knowledge in data cleansing, validation, and structuring, as well as designing and maintaining ETL processes, data systems, and administering databases. She excels at interpreting data, analyzing results, and visualizing information to present business insights.
Simplifying Log Analysis: Streaming RDS Audit Logs to Redshift Using AWS Kinesis Data Firehose
In this article, we will provide a detailed guide on configuring the streaming of RDS audit logs to Amazon Redshift using the Amazon Kinesis Data Firehose. This integration empowers organisations to centralise and analyse their RDS audit logs, enabling proactive monitoring, compliance adherence, and security threat detection.
Automating Email Attachment Analysis: How AWS Glue and Redshift Can Help Businesses Make Better Use of Valuable Data
As businesses grow, so does the amount of data generated. One source of data that is often overlooked is email attachments. Email attachments can contain valuable data that can be analyzed and used to improve business operations. In this article, we’ll demonstrate how to automatically upload email attachments to S3 and then load them into Redshift for further analysis.