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Lynn's Journey - BigQuery for data analysis in the healthcare industry

“Expect to spend 20-25% of your professional time learning for the duration of your career.”

Q: What Google tools have you used?

A: So many! My favorite Google Cloud services are CloudRun, BigQuery, Dataproc. Favorite Tools are Cloud Shell Editor, SSH-in browser for Compute Engine and Big Query Execution Details.
Q: Which tool has been your favorite to use? Why?

A: I love to use the open source Variant Transforms tool for VCF [or genomic] data files. This tool gets bioinformaticians working with BigQuery quickly. Researchers use the VariantTransforms tool to validate and load VCF files into BigQuery. VariantTransforms supports genome-scale data analysis workloads. These workloads can contain hundreds of thousands of files, millions of genomic samples, and billions of input records.
Q: Please share something you have built in the past using Google tools.

A: I have been working with teams around the world to build, scale, and deploy multiple genomic-scale data pipelines for human health. Recent use cases are data analysis in support of Covid or cancer drug development.
Q: What advice would you give someone starting in their developer journey?

A: Expect to spend 20-25% of your professional time learning for the duration of your career. All public cloud services, including Google Cloud, evolve constantly. Building effectively requires knowing both cloud patterns and services at a deep level.