On Thu, Jun 25, 2015 at 10:49 AM, Pavel Velikhov <[email protected]> wrote:
> > On 25 Jun 2015, at 17:10, Ihe Onwuka <[email protected]> wrote: > > > On Wed, Jun 24, 2015 at 12:30 PM, Pavel Velikhov <[email protected] > > wrote: > >> >> A lot of people are content with MongoDB to store the JSONs. So a killer >> use-case needs to look beyond dumb storage of JSONs. Maybe focus on the >> preparation/transformation/cleaning/merging stuff. >> >> >> > >> > But the biggest factor was probably that the move to minicomputer >> architecture created a discontinuity that forced people to consider change. >> You need to do two things: convince people that the new technology is >> better (or at least, is cool), and give them a big kick up the backside to >> get them out of their comfort zone. >> > >> > Michael Kay >> > Saxonica >> > >> > > The data prep/transformation/cleaning/merging stuff is currently the > domain of R and Python. > > > You must be talking about “data science” that is used internally in the > organization. I’m talking more about data-driven Web sites, that have a big > data component in their products. > In this case folks would never use R, they use all sorts of other stuff, > including Python. > > I'm talking generally to be honest but with data science as a prime example but there are several others e.g web scraping. There is a marked preference for other tools to do what XQuery etc are good at - hence there is a people issue.
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