Spreadsheets as both a programming model and a structured data representation are inescapable in the business world. Their sustained success isn’t a coincidence, but they’ve got serious problems, particularly when it comes to preserving the integrity of the data they store. Relational databases can give you lots of integrity guarantees, but at a serious usability penalty to the nontechnical user. The SQL versus NoSQL versus NewSQL debate has brought this trade-off between structure and ease of use to the forefront in the systems world, but not a lot of attention has been paid to end-user data.
In the past five years, Alexander Rasmussen has spent a lot of time trying to get high-integrity data out of spreadsheets and into databases. Alexander explores common data integrity problems when dealing with spreadsheet data, investigates whether those integrity problems are inescapable, and shares ongoing work to mitigate them.
Alex Rasmussen is the vice president of engineering at Freenome, an AI genomics company with a unique approach to detecting cancer at its earliest stages and helping physicians optimize the next generation of precision therapies. He holds a PhD from the University of California, San Diego, where his dissertation focused on highly efficient large-scale data processing systems. While at UCSD, he led the TritonSort project, which set several world records in large-scale sorting.
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