Cutting-Edge Aerospace Research
Delve into the world of aerospace research with a focus on collaboration during the life cycle of satellites at The Aerospace Corporation. Explore how a single image can convey complex ideas in this dynamic field of study. Discover the long-term goals driving forward this research and join the journey of falling stars and cutting-edge innovation in the study of aerospace science.
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Presentation Transcript
Sounds of Data Silence jana@naralogics.com @jeggers
Perspective on listening 2.5% correct for listeners
But your brain is amazing! http://cdn.theatlantic.com/newsroom/img/posts/2014/05/ambiguous/29cd8b1f2.png
Human curiosity, the urge to know, is a powerful force and is perhaps the best secret weapon of all in the struggle to unravel the workings of the natural world. Sir Aaron Klug
Exercise 1: How to be curious Take on a different persona Relish don t rationalize surprises Bring a buddy, but study silently Be hyper-curious
2 ears, 1 mouth becomes
Exercise 2: 2 eyes, 1 mouth QuickBooks almost never happened Quicken use write-in candidate: for my business They convinced themselves it was a mistake for years Where are you sleeping with your eyes open?
Exercise 3: Walk in Your Datas Shoes PTCG/Manhattan Associates: Recommendations for driver to load assignments 1. Know the data source 2. Know how different people use the data 3. Know the quality of the data 4. Know the objective Most important: first take off your own shoes!
Exercise 4: Step Back from Your Data UPenn & LockMart: Detecting infections and missiles Sepsis: #10 leading cause of death, mortality rate is 40% Current diagnostic tool: vitals Innovation: watch vitals and lab data over time New diagnostic tool: missile detection system
Exercise #5: Add More Weight Intuit Quickbase: customer retention Initial test: # of apps, # of users, usage Learning: undelighted customers will leave Added: app performance metrics Once fit, up your game
Hearing the Sounds of Datas Silence 1. Be from the Curiosity State 2. 2 eyes, 1 mouth 3. Walk in your data s shoes 4. Step back from your data 5. Add more weight
