know.bi blog

Build a dashboard with AWS Athena and Quicksight in less than an hour

Feb 28, 2018 10:00:00 AM / by Hans Van Akelyen posted in cloud, analytics, amazon, aws

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Quickly move from data to insight

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5 Key Components For Your Cloud Analytics Project

Feb 9, 2018 10:00:00 AM / by Bart Maertens posted in data engineering, cloud, cloud etl, business intelligence, analytics, amazon, aws, analytical database, column store

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Why move your BI to the cloud? 

As discussed in a previous post, there are many reasons to move your BI to the cloud.
Security, being able to work from anywhere and delivering faster, with more resource flexibility and at a lower cost are just a few.  

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Getting Started with AWS DMS

Dec 27, 2017 9:30:00 AM / by Willem Dullaart posted in cloud, amazon, aws, database migration service, dms

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What is Amazon DMS

Every day, more and more companies are moving towards cloud computing, with Amazon Web Services (AWS) undoubtedly being the biggest player. Having all the possible AWS services available at your fingertips is great, but you still need to migrate your existing infrastructure and data into the (AWS) cloud. At re:Invent 2015, Amazon announced “AWS Database Migration Service”, aiming to make the process of moving data into databases on AWS a lot easier.

AWS DMS supports most open-source and commercial databases such as PostgreSQL, MySQL, MariaDB, Oracle, Microsoft SQL Server, and of course their own Aurora, Redshift, DynamoDB and S3 services. Both homogeneous (e.g. Postgres to Postgres) and heterogeneous migrations (e.g. Oracle to MySQL) are supported. Either the source or target database is required to be in the AWS cloud. DMS regularly gets updated with new features and supported engines.

DMS Overview

At the highest level, you have three components to take care of when starting a migration using DMS:

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