4 mistakes to avoid when building lakehouse based solutions on AWS
Author: Igor Royzis Mistake #1 Dumping all your data in S3 without a well designed data lake partitioning that supports your organization’s needs We’ve all heard the saying “store all data all the time in your data lake” or something of that nature. Well, it’s true, this approach may give organizations immediate access to all […]
Accelerating Data and Analytics Success in the Public Sector
Kevin Mead Data and Analytics in Government More government entities are launching data and analytics initiatives to improve planning, operations, citizen engagement, and services delivered. It is indisputable that access to timely, accurate data enables more informed decisions that deliver better outcomes. So why doesn’t every government take advantage of their data? Some struggle to […]
AWS Data & Analytics Architecture Best Practices
Author: Igor Royzis “Best practice is a procedure that has been shown by research and experience to produce optimal results and that is established or proposed as a standard suitable for widespread adoption” – Merriam-Webster Dictionary Data, Analytics, Web & Mobile on AWS Here is how your architecture would look like on AWS if you […]
Database migration to AWS
Author: Igor Royzis History of AWS relational databases – or how we got here Early 2000’s, everyone is happily buying servers, installing and configuring on-premise relational databases, both commercial (SQL Server, Oracle) and open source (Postgres, MySQL). Life is good. Need more storage? Buy more disk space. Need more compute power? Buy more memory. Cannot […]
