Data Engineering - A Big Data Missing Piece

Speaker: Ryan Brush

We have everything we need to jump in and solve a data-centric problem at scale: the datasets, the infrastructure, the requirements. We plan and execute the project, produce the results...and then don't come close to meeting our users' needs. A flurry of follow ups are then scheduled to to address this as deadlines loom.

This talk explores the practice of data engineering to address these gaps. Whether it's machine learning or identifying particular care needs or troubleshooting data problems at scale, we can more quickly understand and improve such shortcomings. The end is a system that can be adapted to new needs with speed and confidence that we couldn't achieve otherwise.

[guilloutube]

Nice way to apply basic statistics in data engineering

[joshuagilbert]

Thanks for the information, I look forward to other videos