Database

Engineering Data Quality

Garbage in, garbage out – we have all heard about the importance of data quality. Having high quality data is essential for all types of use cases, whether it is reporting, anomaly detection, or for avoiding bias in machine learning applications. But where does high quality data come from? How can one assess data quality, …

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Changing Your Database Mindset From Tables to Documents

Did you grow up with relational SQL databases? Are document-based databases (NoSQL) a bit of a mystery to you? This presentation compares terms and concepts, explains the benefits of document-based databases, and presents the 3 key ways you need to change your mindset to successfully use document-based databases.

Continuous Integration & Delivery for Databases

This talk looks at the common problems faced with making database changes through continuous delivery. It covers the major tools used to address database changes, and the advantages and disadvantages to each. Then it discusses how database migrations can effectively address schema changes over time, for both SQL and NoSQL databases. Finally, it explores solutions …

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Data Necromancy: Bring Your Data Strategy Back from the Dead

Our story begins squeezed into the corner of this room: the data team. Analytics requirements were pushed out of the critical path for launches, slowly and then all at once. The data team is fighting against prioritization, cooperation, and, soon, relevance. This is sadly the state of many organizations, to a lesser or greater degree. …

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Database Design for Beginners

Ruby on Rails migrations were a revelation when Rails came out, as it provided a way to manage your database schema, but also included many wonderful defaults that made all Rails developers pretty good at database schema design! But these defaults are just the beginning.