Cloud articles

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Data engineering on AWS Data engineering on Azure Data engineering on GCP Data engineering on the cloud

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My journey to AWS Certified Big Data specialty

January 10, 2020 I successfully passed my AWS Certified Big Data specialty with the overall score of 82%. Despite the fact that it will be replaced soon (April 2020) by AWS Certified Data Analytics - Specialty, I'd like to share with you my learning process and interesting resources.

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My journey to AWS Cloud Practitioner

One of goals in my 3-Levels List was to get 3 certificates: AWS Cloud Practitioner, AWS Big Data and GCP Data Engineer. I've already passed the first one and that's the reason I'm writing this blog post.

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Loading data into Redshift with COPY command

One of approaches to load big volumes of data efficiently is to use bulk operations. The idea is to take all the records and put them into data store at once. For this purpose, AWS Redshift exposes an operation called COPY.

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AWS Kinesis Firehose, event time and batch layer

Last time I wrote about sending Apache Kafka data to batch layer. This time I would like to do the same but with AWS technologies, namely Kinesis, Firehose and S3.

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Listening EMR events with AWS Lambda

I really appreciate AWS services and one of the main reasons for that is the facility to implement event-driven systems. One of the interesting use cases of these events is related to the EMR service, responsible for running Apache Spark pipelines. In this post I will try to associate an action invoked every time an EMR step completes successfully.

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AWS Lambda - does it fit in with data processing ?

Despite the recent critics (cf. "Serverless Computing: One Step Forward, Two Steps Back" link in the Read also section), serverless movement gains the popularity. Databricks proposes a serverless platform for running Apache Spark workflows, Google Cloud Platform comes with a similar service reserved to Dataflow pipelines and Amazon Web Services, ... In this post, I will summarize the good and bad sides of my recent experiences with AWS Lambda applied to the data processing.

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Doing data on AWS - overview

Open Source provides a lot of interesting tools to deal with Big Data: Apache Spark, Apache Kafka, Parquet - to quote only a few of them. However nowadays data platforms without cloud support are more and rarer. It's why this topic merits its own category and posts on this blog. To not go too quickly, the first article speaks about services you can use to work with the data on AWS.

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