When you think of data, you typically think of lines of code and numbers. But data science can be used for some truly spectacular things, and you could play a game of Two Truths and a Lie with some of these.
- An AI-generated text prediction model was trained to write a Harry Potter novel.
- The earliest case of data visualization being used to influence public policy was around getting better sanitary conditions for British soldiers.
- AI-powered bees are being developed by the Wyss Institute in Boston to be used in crop pollination, climate monitoring, and surveillance, among other things.
- The City of Chicago used R to predict which restaurants were likely to commit violations in sanitation inspections, based on factors such as time since last inspection, the number of nearby sanitation complaints, and the type of facility being inspected. Prioritizing these outlets for review, they were able to discover violators one week earlier on average.
- An AI-powered software was created that could predict the results of the Oscars with 90% accuracy.
- Many businesses make heavy use of Python, but Dropbox was built almost exclusively on the programming language when it was started up in 2008. So integral was Python to Dropbox that in 2013 they managed to convince Guido van Rossum, Python’s creator, to join their staff. He agreed, on the condition that he wouldn’t be put in a managerial or leadership role. Facts about data science’s usage As data changes the world, businesses are recognizing that it’s a force to be reckoned with.
- Between the dawn of time and 2003, five exabytes of data had been created at Google. By 2010, this amount of data was being created every two days, and by 2021 it was being created every 40 minutes.
- There are approximately 400,000 bytes of data for every grain of sand on earth.
- The amount of marketing budget firms allocate towards marketing analytics increased by 198% in 2020. In 2019 it was reported that only 27% of organizations were able to make full use of their data to generate actionable insights, with the growing data skills gap cited as a primary reason.
By
Thiruthamizhi S
06 December 2021