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[Music]

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I'm<00:00:14.139><c> Rashmi</c><00:00:14.530><c> sham</c><00:00:14.740><c> Prasad</c><00:00:15.099><c> I</c><00:00:15.370><c> am</c><00:00:15.519><c> a</c><00:00:15.910><c> senior</c>

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I'm Rashmi sham Prasad I am a senior
 

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I'm Rashmi sham Prasad I am a senior
data<00:00:16.330><c> engineer</c><00:00:16.779><c> with</c><00:00:17.410><c> the</c><00:00:17.650><c> data</c><00:00:17.800><c> science</c><00:00:18.039><c> and</c>

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data engineer with the data science and
 

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data engineer with the data science and
engineering<00:00:18.730><c> team</c><00:00:18.910><c> at</c><00:00:19.090><c> Netflix</c>

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so<00:00:30.700><c> it</c><00:00:31.120><c> is</c><00:00:31.300><c> my</c><00:00:31.450><c> first</c><00:00:31.660><c> time</c><00:00:31.780><c> both</c><00:00:32.380><c> speaking</c><00:00:32.830><c> and</c>

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so it is my first time both speaking and
 

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so it is my first time both speaking and
attendings<00:00:33.670><c> killed</c><00:00:34.120><c> by</c><00:00:34.240><c> the</c><00:00:34.300><c> way</c><00:00:34.480><c> so</c><00:00:34.540><c> I'm</c>

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attendings killed by the way so I'm
 

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attendings killed by the way so I'm
super<00:00:35.440><c> excited</c><00:00:35.560><c> about</c><00:00:35.950><c> it</c>

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super excited about it
 

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super excited about it
we<00:00:37.090><c> actually</c><00:00:37.239><c> heard</c><00:00:37.630><c> about</c><00:00:37.690><c> it</c><00:00:38.050><c> from</c><00:00:38.350><c> our</c>

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we actually heard about it from our
 

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we actually heard about it from our
manager<00:00:38.920><c> who</c><00:00:39.220><c> is</c><00:00:39.430><c> a</c><00:00:39.460><c> regular</c><00:00:39.700><c> attendee</c><00:00:40.120><c> here</c>

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manager who is a regular attendee here
 

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manager who is a regular attendee here
so<00:00:41.260><c> that's</c><00:00:41.890><c> how</c><00:00:42.010><c> we</c><00:00:42.070><c> can</c><00:00:42.280><c> find</c><00:00:42.520><c> out</c>

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[Music]

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so<00:00:53.629><c> our</c><00:00:54.230><c> talk</c><00:00:54.530><c> basically</c><00:00:55.309><c> talks</c><00:00:55.610><c> about</c><00:00:55.940><c> how</c><00:00:56.180><c> we</c>

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so our talk basically talks about how we
 

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so our talk basically talks about how we
solved<00:00:56.629><c> a</c><00:00:56.719><c> problem</c><00:00:56.870><c> with</c><00:00:57.500><c> most</c><00:00:58.219><c> data</c>

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solved a problem with most data
 

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solved a problem with most data
engineers<00:00:59.000><c> or</c><00:00:59.180><c> analysts</c><00:00:59.539><c> run</c><00:00:59.840><c> into</c><00:01:00.170><c> on</c><00:01:00.320><c> a</c>

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engineers or analysts run into on a
 

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engineers or analysts run into on a
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day-to-day basis but there's no good
 

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day-to-day basis but there's no good
known<00:01:02.839><c> open-source</c><00:01:03.530><c> solution</c><00:01:04.040><c> out</c><00:01:04.220><c> there</c><00:01:04.280><c> and</c>

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known open-source solution out there and
 

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known open-source solution out there and
we<00:01:05.479><c> were</c><00:01:05.630><c> able</c><00:01:05.750><c> to</c><00:01:05.900><c> come</c><00:01:06.049><c> up</c><00:01:06.140><c> with</c><00:01:06.229><c> a</c><00:01:06.290><c> solution</c>

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we were able to come up with a solution
 

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we were able to come up with a solution
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for it and hope to open-source it and
 

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for it and hope to open-source it and
share<00:01:09.470><c> it</c><00:01:09.590><c> with</c><00:01:09.740><c> the</c><00:01:09.800><c> community</c><00:01:09.950><c> so</c><00:01:10.940><c> we</c><00:01:11.570><c> wanted</c>

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share it with the community so we wanted
 

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share it with the community so we wanted
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to share the details of it and at some
 

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to share the details of it and at some
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point of time also maybe get some
 

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point of time also maybe get some
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interest going in for the contributions
 

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interest going in for the contributions
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so<00:01:33.340><c> I</c><00:01:33.760><c> am</c><00:01:33.930><c> one</c><00:01:34.930><c> of</c><00:01:34.960><c> the</c><00:01:35.110><c> data</c><00:01:35.260><c> engineers</c><00:01:35.710><c> on</c><00:01:36.010><c> the</c>

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so I am one of the data engineers on the
 

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so I am one of the data engineers on the
growth<00:01:37.240><c> data</c><00:01:37.570><c> engineering</c><00:01:38.140><c> team</c><00:01:38.350><c> so</c><00:01:38.650><c> what</c><00:01:39.100><c> I</c>

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growth data engineering team so what I
 

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growth data engineering team so what I
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focus on mostly is around things that
 

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focus on mostly is around things that
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involve acquisition and experimentation
 

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involve acquisition and experimentation
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for people who are about to join Netflix
 

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for people who are about to join Netflix
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or who want to join Netflix as members
 

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or who want to join Netflix as members
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and so a lot of my work involves putting
 

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and so a lot of my work involves putting
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all of these datasets together so that
 

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all of these datasets together so that
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we can find the best possible experience
 

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we can find the best possible experience
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that we could offer users and so that
 

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that we could offer users and so that
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they can start enjoying all the movies
 

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they can start enjoying all the movies
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and TV shows that we have at Netflix so
 

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and TV shows that we have at Netflix so
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I think that's a big way in which we
 

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I think that's a big way in which we
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influence and we see that effect almost
 

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influence and we see that effect almost
immediately

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I haven't looked at all of the talks he
 

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I haven't looked at all of the talks he
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act but I'm suddenly interested in more
 

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act but I'm suddenly interested in more
of<00:02:29.670><c> the</c><00:02:29.849><c> scholar</c><00:02:30.319><c> track-based</c><00:02:31.319><c> talks</c><00:02:31.709><c> and</c>

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of the scholar track-based talks and
 

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of the scholar track-based talks and
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anything that's more data oriented so
 

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anything that's more data oriented so
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I'm going to go and check out the index
 

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I'm going to go and check out the index
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really bullish about the way ai and ml
 

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really bullish about the way ai and ml
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in general is shaping up and how that
 

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in general is shaping up and how that
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might be dictating probably the next
 

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might be dictating probably the next
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five years of how we do things in the
 

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five years of how we do things in the
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data space in general some very excited
 

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data space in general some very excited
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I think so this is my first time
 

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I think so this is my first time
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attending so in fairness like I'm
 

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attending so in fairness like I'm
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probably not the best person to evaluate
 

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probably not the best person to evaluate
which<00:03:24.200><c> are</c><00:03:24.349><c> the</c><00:03:24.500><c> best</c><00:03:24.739><c> features</c><00:03:25.250><c> I</c><00:03:25.670><c> am</c><00:03:28.569><c> like</c><00:03:29.569><c> I</c>

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which are the best features I am like I
 

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which are the best features I am like I
come<00:03:30.349><c> from</c><00:03:30.439><c> a</c><00:03:30.560><c> data</c><00:03:30.709><c> background</c><00:03:31.129><c> so</c><00:03:31.280><c> I</c><00:03:31.310><c> would</c>

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come from a data background so I would
 

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come from a data background so I would
like<00:03:32.000><c> to</c><00:03:32.150><c> see</c><00:03:32.299><c> a</c><00:03:32.329><c> lot</c><00:03:32.720><c> more</c><00:03:32.750><c> detox</c><00:03:33.680><c> I</c><00:03:34.280><c> know</c><00:03:34.519><c> we</c>

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like to see a lot more detox I know we
 

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like to see a lot more detox I know we
are<00:03:34.970><c> doing</c><00:03:35.569><c> a</c><00:03:35.750><c> mix</c><00:03:35.959><c> of</c><00:03:36.200><c> AI</c><00:03:36.470><c> and</c><00:03:36.890><c> ml</c><00:03:37.220><c> and</c><00:03:37.519><c> Scala</c>

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are doing a mix of AI and ml and Scala
 

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are doing a mix of AI and ml and Scala
and<00:03:38.720><c> data</c><00:03:39.079><c> and</c><00:03:39.500><c> so</c><00:03:40.189><c> as</c><00:03:40.579><c> a</c><00:03:40.790><c> data</c><00:03:41.090><c> person</c><00:03:41.329><c> I</c><00:03:41.569><c> would</c>

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and data and so as a data person I would
 

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and data and so as a data person I would
like<00:03:41.900><c> to</c><00:03:42.049><c> see</c><00:03:42.200><c> more</c><00:03:42.379><c> data</c><00:03:42.560><c> talk</c><00:03:42.859><c> so</c><00:03:43.129><c> but</c><00:03:43.730><c> I'm</c>

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like to see more data talk so but I'm
 

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like to see more data talk so but I'm
looking<00:03:44.329><c> forward</c><00:03:44.659><c> to</c><00:03:44.689><c> enjoy</c><00:03:44.930><c> the</c><00:03:45.049><c> rest</c><00:03:45.170><c> of</c><00:03:45.290><c> the</c>

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looking forward to enjoy the rest of the
 

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looking forward to enjoy the rest of the
conference<00:03:45.980><c> to</c><00:03:46.189><c> see</c><00:03:46.400><c> you</c><00:03:46.879><c> know</c><00:03:47.000><c> what</c><00:03:47.180><c> I</c><00:03:47.209><c> can</c>

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conference to see you know what I can
 

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conference to see you know what I can
get<00:03:47.510><c> out</c><00:03:47.569><c> of</c><00:03:47.780><c> it</c><00:03:47.930><c> and</c><00:03:48.079><c> obviously</c><00:03:48.170><c> the</c><00:03:48.500><c> videos</c>

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get out of it and obviously the videos
 

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get out of it and obviously the videos
and<00:03:48.980><c> all</c><00:03:49.099><c> of</c><00:03:49.250><c> their</c><00:03:49.430><c> for</c><00:03:49.700><c> reference</c><00:03:50.569><c> whenever</c>

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and all of their for reference whenever
 

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and all of their for reference whenever
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