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About a year ago one of Liliana's clients, a financial institution, came up with an idea for a "self-service data science platform" - a platform that would allow business users to work with variety of data in a rapid, agile environment. To choose the right technical solution her team has spent a lot of time on an evaluation of existing options via practical proof of concepts as well as reading available documentation and talking to the vendors. Whilst they’re still no experts, they now have a very broad view of all major options available, with their pros and cons, similarities and differences.
This talk would be helpful to anybody who is at the beginning of their cloud journey and is trying to decide which of AWS, GCP and Azure might be best fit for their use-case (spoiler: there is not "one size fits all"!). It might also help people who have experience with one of the clouds and are trying to translate familiar landscape to the world of a different vendor.
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Liliana is a software engineer with over 10 years experience working with Java, primarily in the (big) data space. She spent most of her career in financial institutions, and at the moment she is just about to embark into next step of the journey - becoming a CTO of a company she is co-founding.