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Where are the students?

Last week the students started of. After two days of learning Spark, they dove into the project. Planning happened without any sight on a velocity range. The smallest task planned for the three days left was rewarded one story point and all other tasks were compared with this one task.

For almost every new team, the first sprint will be hard, but during the next weeks they will get better in this process!

Sprint burndown

To be honest: one task was done, but only set on done by Monday and the other, biggest one of 8 story points, was already finished in the next sprint on Monday. So, ok, far from perfect, but far from dramatic as well! Let's see how they evolve and check if they truly get better during the weeks they wander around at InfoFarm. We still believe in them!

And what did they already do last week? Well they already have a front-end, integrated via web-socket with a Spark back-end. First Spark jobs are triggered with the upload and perform type recognition. You can already enjoy the basic lay-out:

Front end automated anomaly detection

This week they will tackle the outlier detection algorithms (Jenny documented very high standards or intelligent algorithms, we will see how far we realy go, since not everything is natively available in Spark: we and our students like a challenge). Moreover they will show the summary of the result too.

But there's more, the experiment continues! We want to give our students an entire real-life project setting. They are allowed to work from home for a day. Asking for the benefits, you get the typical answer: "It was nice to sleep a bit longer"I especially liked the hashtag #CatsAreAssholes concluding the comment "Colleagues (usualy) don't claw to me while typing" and "It feels a bit more comfortable wandering around with a coffee while overthinking a piece of code".

Over all a bunch of work was done during this day and as of Wednesday we rewelcome them at the InfoFarm offices. Maybe next week we'll try a joined walk in the park to overthink code or come up with different ideas.

Stay tuned for more information on this project/experiment the coming weeks.

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Data Science