The Web is full of “data-driven apps.” Almost any e-commerce application is a data-driven application. There’s a database behind a web front end, and middleware that talks to a number of other databases and data services (credit card processing companies, banks, and so on).
But merely using data isn’t really what we mean by “data science.”
A data application acquires its value from the data itself, and creates more data as a result. It’s not just an application with data; it’s a data product.
Data science enables the creation of data products. One of the earlier data products on the Web was the CDDB database. The developers of CDDB realized that any CD had a unique signature, based on the exact length (in samples) of each track on the CD.
Data Science Real-time Project
- Gracenote built a database of track lengths, and coupled it to a database of album metadata (track titles, artists, album titles). If you’ve ever used iTunes to rip a CD, you’ve taken advantage of this database. Before it does anything else, iTunes reads the length of every track, sends it to CDDB, and gets back the track titles.
- If you have a CD that’s not in the database (including a CD you’ve made yourself), you can create an entry for an unknown album. While this sounds simple enough, it’s revolutionary: CDDB views music as data, not as audio, and creates new value in doing so. Their business is fundamentally different from selling music, sharing music, or analyzing musical tastes (though these can also be “data products”). CDDB arises entirely from viewing a musical problem as a data problem.
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