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    Will Facebook be good for podcasting? + Amazon buys Art19
    2021-07-02 (duration 55m)
    52:44 floor is lava, on Netflix. It's
    Create Premium Content in Apple Podcasts + Growing a Niche Audience
    2021-06-18 (duration 49m)
    05:40 have a Netflix subscription, you
    Big changes coming to Apple Podcasts and Spotify?
    2021-03-26 (duration 52m)
    44:29 Netflix startup. And it was
    44:21 Netflix. And I heard about him
    Dynamic Descriptions + Making an NPR Podcast in Just 3 Days
    2021-03-12 (duration 53m)
    31:36 Netflix, right? People talk
    31:36 about having a Netflix
    31:44 subscribe to Netflix cost money.
    2021 Podcast Predictions + Visual Soundbites Just Got a Whole Lot Better
    2020-11-06 (duration 57m)
    55:59 friends. But like, Netflix watch
    54:37 Netflix is trying to solve that
    53:35 what Netflix did. And I think it
    The Future of Podcasting with Adam Curry
    2020-10-23 (duration 59m)
    11:32 Netflix, etc. And so here was
    21:55 Netflix for this, I had Hulu for
    Podcasters React to "The Social Dilemma" + IAB Certified Stats
    2020-09-25 (duration 45m)
    [from description] ...ipts to the RSS Feed, and our reaction to watching "The Social Dilemma" on Netflix.If you're an app developer or podcast host, here's Buzzsprout's spec document...
    [from content:encoded] ...ipts to the RSS Feed, and our reaction to watching "The Social Dilemma" on Netflix.If you're an app developer or podcast host, here's Buzzsprout's spec document...
    25:13 Netflix documentary, or is it a
    25:45 this, if you don't have Netflix,
    25:47 kids that has Netflix and watch
    Find Out If You're In The Top 50% Of Buzzsprout Podcasts
    2020-08-28 (duration 43m)
    31:49 what, uh, you know, Netflix and
    Spotify Introduces Podcast Charts + Stitcher Sells For $325 Million
    2020-07-17 (duration 39m)
    01:22 this is the first time I'm hearing this. So I guess you could have tagged me in support. So I could have read read these notes. honest, I, so my wife and I have shifted to the crown. So we've that's become our new daily daily bend is we'll watch episodes of the crown, which is fantastic. It's on Netflix, if you don't live in the US. And it's not on your Netflix, you can use Nord VPN or some other kind of IP generator so you can watch the US version, but it's really good. And it's kind of HGTV related because they live in a big palace. With lots of tapestries and stuff like that,
    08:44 Yeah, Kevin, and I've talked about this before offline, where even if you have a Netflix in a space, you know, one group one thing that's dominant, the existence of a Hulu and then later on a Disney plus and all these other things, actually makes it so Netflix has to pay creators good money for their shows. And for whoever's making these shows, well, when they have the option, when they actually can just start shopping among two or three groups, they get quite a bit better deal. And so, there's been tons of examples of Netflix paying a lot more money or net, or somebody else paying a lot more just because a show is able to be shopped between a few different places. And so now with Sirius XM, and Spotify, you could imagine a future where some of the biggest shows instead of going exclusive to Spotify, for kind of something on Spotify as terms, they might be able to, if they decide that's the path they want to go down, they can kind of shop between two or three big players and make sure that they are paid the fair market value of what they've created.
    19:01 So, I mean, that's a great podcast to listen to, if you want to hear about how good YouTube is at discovering your likes, or what you'd be interested in and keep you locked into the platform and increase your watch time by just bringing you down these rabbit holes of content. Same thing happens with Spotify very effectively in the music world. Again, it's not as concerning because it's just like this song. If you like the song, you might like this one. It's not necessarily Oh, if you have a tendency to believe this conspiracy theory, then you'll like this conspiracy theory. So it's not necessarily as concerning or dangerous. But applying that in the podcasting world is something that has been a struggle, right, it's a slightly different nut to crack because it's it's not that interests don't align as much in the podcasting world is that podcasts are long form content. And so if you see like Netflix struggles with this, because Netflix is more long form content. In order for me to kind of get hooked into something, it's very easy in the YouTube world when the vast majority of videos are like five to 10 minutes. Less, even with music again, like if I listen to a song and it doesn't happen to be something that I love right away? Well, songs are like three minutes, it's not that big of a deal. When you're recommending a TV show, or a movie, or a podcast, you're talking about a much bigger commitment. And so while I might like podcasts x, so then the algorithm thinks I'm gonna like podcast Why? I might not like podcast why in the first two or three minutes, and therefore I'm not willing to sit through 45 minutes to figure out if I really like it or not. And so discoverability in the podcast world is a much tougher nut to crack. I'm interested to see what Spotify can do it, but it's been a struggle. As long as podcasts have been around and get Netflix has the same problem in the, you know, recommending TV shows or movies. You might really like a TV series that Netflix keeps recommending to you. But it doesn't get good until episode three or four. And it's like I'm not gonna sit through three episodes to figure out why Netflix thinks I'm gonna like this.
    SiriusXM Buys A Podcast Host, Spotify Signs Kim Kardashian, and Ximalaya Threatens Chinese Podcasters
    2020-06-19 (duration 45m)
    01:39 So there's a new? Well, it's actually not a new company, but a pivot from an existing company to this new app called pod hero, which is trying to, at least on the surface, seem like it's bridging the gap between luminary, which is an app that's trying to be the Netflix of podcasts where you pay for a subscription, you get exclusive content, trying to bridge the gap between that and Patreon, where it's like purely listener supported. But you have to do a lot of extra work to make that happen. So they they walked through this, they're approaching a medium article that I'll link in the show notes. But it just, it raises the question yet again. podcasters trying to either supplement the costs of putting their podcasts together, or trying to make a little side hustle out of it. What's the best way to do that? And is asking your podcast listeners to directly support your podcast content, a viable option?
    19:15 Yeah, I agree with that. I think it's, that is a benefit for sure. I mean, I'm a little bit bummed that I don't want. Maybe I'm just being a spoiled child. But I don't want to have three or four different apps that I have to load up on my phone to listen to different shows. So I'm not excited about this big push and trend towards exclusive content, I don't want to have to listen to I mean, I was never a huge Joe Rogan fan in the in the beginning, but there were times when he had people on the show that I wanted to hear that show. Now the idea that I'm gonna have to load up Spotify just to hear that one episode. It's probably means I'm not gonna listen to that show anymore. And the same thing if Apple moved into that space, if XM starts doing it, it's kind of like where we are. Right now in the in the TV and movie world, it's like, I don't know if you want to watch Seinfeld, but who has Seinfeld right now? Is it Hulu as Seinfeld? Is it Netflix? Is it amazon prime? I don't know. But I have to, you know, now there's these other services that are coming out like the new Apple TV supposedly just tells, you know, if you search for Seinfeld here, you can listen, you can watch it on stars or Hulu. And it's like, Well, great. I don't have stars or Hulu, so I can't watch it right now. It would be nice if we could figure out some sort of technology that all these things could work together in the podcasting space. But one of the things I like the most is that there's this big market, we talked about the beginning the show of all these independent podcast apps, so you can find the one that matches your habits and your style. But now more and more, it seems like the industry is moving in a direction where I'll be able to use that app for, you know, 60 or 70% of the podcasts I listened to but there's more and more that are going to be outliers that I'm not going to be able To listen to and that app. And again, we'll tease it even further. Like we've all just started listening to the rabbit hole, The New York Times podcast, The New York Times is creating really great shows. But are they going to be able to remain open and independent? Or are they going to get brought into one of these, you know, silos where now I have to listen to the New York Times podcasts in the New York Times podcast app, or a Spotify gonna license that content? Or is luminary going to license that content? Or is Apple going to license that content? And now you're locked into their player if you want to listen to it?
    Joe Rogan Moves To Spotify (And What It Means For Independent Podcasters)
    2020-05-22 (duration 58m)
    03:17 Yeah. So I think it's good just to lay out the exactly what we know about the deal so far. So Joe Rogan came out said podcast is moving to Spotify. September by September, they're gonna have the entire 11 year backlog of episodes. That's all gonna be on Spotify. And then by the end of the year, so sometime a little bit before 2021, the show and the video so everything on YouTube will be exclusive to Spotify. And that's a pretty big deal. We're talking millions of views on YouTube millions of downloads per episode. Joe Rogan experience is considered by many to be The number one podcast in the world, maybe not everyone's favorite podcast in the world, but it's definitely the largest, he has the most downloads per episode. So it's a really big win for Spotify to be able to do that. This is coming from somebody who, for years said, you know, it's all smoke and mirrors over there, Spotify, you don't make enough money when you stream with them. And the deal that at least the details of the deal that we've seen, make it like you make a ton of money and you move to Spotify. If you're Joe Rogan. It's a multiple year licensing deal. So Spotify is not buying the Joe Rogan experience. They're just going to be the exclusive provider of the show for multiple years. We don't know how many multiple years so it's more like when Netflix licenses friends than when they create their own show or buy a show. That money side of it is somewhere north of 100 million dollars. I saw the Wall Street Journal posted. And then I've seen another source that said, it's probably going to be closer to 200 million by the time that it all pans out. So it's a lot of money. And it definitely signaling a huge change for the podcasting industry.
    Uniform Cycle Recap + What File Format Should I Upload To Buzzsprout?
    2019-10-25 (duration 39m)
    05:25 Netflix
    Big Money and Spotify Concerns
    2019-07-04 (duration 33m)
    05:32 Netflix
    05:43 Netflix
    07:28 Netflix
    Apple Podcasts News from WWDC
    2019-07-02 (duration 37m)
    04:56 Netflix,
    Indie Horror Movies - With Dani Thompson
    2021-06-06 (duration 43m)
    18:27 Netflix that I really want to
    Playing Chess: Queen Bashes Bishop
    2021-05-02 (duration 38m)
    15:58 program on Netflix. I did see
    Making The Most Of Your Life: Who Wants To Live Forever
    2021-03-28 (duration 48m)
    30:47 on Netflix.
    Video Game Consoles: Hands Off My Joystick
    2021-03-21 (duration 39m)
    16:13 got the Netflix is built in 4k,
    TV Nostalgia: Strike First, Strike Hard, Strike Nostalgia
    2021-02-28 (duration 39m)
    30:38 everyone's got Netflix, I'm sure
    Unemployable Entrepreneur
    2021-04-10 (duration 18m)
    12:05 Netflix
    Yule Monsters and Good Saint Nick
    2020-12-16 (duration 55m)
    37:08 Netflix
    Cape Town: Corona Aesthetics and Theater
    2020-11-15 (duration 34m)
    24:12 probably has much greater production values to be able to compete with the Netflix offerings that audiences now have access to.
    Cape Town: Still standing home
    2020-09-27 (duration 31m)
    17:02 You can see movies on Netflix and so on.
    17:13 And B) the production values were so poor, um, that if people had access to Netflix, why would they watch a piece of theater online?
    Athens: Go vegan, go local
    2020-09-20 (duration 28m)
    18:06 I was, watching a series on Netflix.
    17:58 I didn't even watch like a movie on Netflix.
    Istanbul: Survival Mode
    2020-09-13 (duration 30m)
    13:39 Now I can just have a dinner and watch something on Netflix or whatever.
    The Past, Present, And Future Of The FLUFL: Barry Warsaw Shares His History With Python
    2020-07-13 (duration 51m)
    [from content:encoded] Summary Barry Warsaw has been a member of the Python community since the very beginning. His contri...
    49:22 I have two actually, that I'm really into these days. One is a show on Netflix called midnight Gospels. And it is it hits all my buttons. You know it's trippy and weird and animated and just bizarre but but underneath all of the weird animation, it just gets into some really deep philosophical topics. So I've been loving that one. I've been savoring those episodes. And the other thing I absolutely obsessed with these days I love the show called the expanse which I think was on amazon prime and I think the fifth season is coming out at some point. Probably next year but my brother turned me on to the audible books you know, the the books on they're not on tape anymore but you know the the through audible you know, I listen, I put them on my phone, I listen to them in the car and it's just absolutely fantastic. I'm, I'm like looking for excuses to drive places now so that I can listen to it. Listen to those books. It's really good.
    Open Source Product Analytics With PostHog
    2020-06-08 (duration 49m)
    45:40 So go on Netflix and special shout out to rob see kind of the open source equivalent of that. those are those are great options. If you know, like I said, you have kind of a website where you care more about things like sessions and clicks and you know, how long are people spending on my site and on average, you know, What is the most popular article on my website? And where are my visitors coming from in the world? And those kind of questions, they tend to be a lot better at asking it, you know, post or could be possibly overkill for these use cases. So yeah, you know, there's a bunch of ways that those tools will be better.
    18:45 You know, it's super important, I think, you know, talk to any markets here and they love talking about and, in fact, my girlfriend is a senior marketing manager. And, you know, she loves talking about things like first starch, last touch. It's so crucial To especially, you know, kind of marketing, then that filters down into the product, right? You want to know how people first found you whether that, you know, if you're doing paid ads, for example, you want to know, okay is my Facebook campaign working. But if your KPI is someone goes to your website, you know, sees an ad goes to your website then downloads an app and signs up on the app, you know, you want to be able to kind of track people across all of that, ideally, because then you can say, okay, the kinds of users that do, for example, slack knows that if you join, like a couple of channels, it knows that you're basically hooked for life. And Netflix has something similar, right? Well, if you watch a couple of movies, you're going to be hooked for life basically, or for a long time. If that's your KPI that lives in your mobile app. And you're spending a ton of money getting people you know, from Facebook, onto your website, you want to be you want to make sure that the types of campaigns that bring people to website are the types of campaigns that then eventually lead people to do whatever that action is in your app. So they're marrying the two up is it is a massive challenge. But if you get it right, especially in big organizations, it can be so powerful, because it just allows you to, if you're doing paid marketing spend much more effectively, or if you're doing content marketing to
    15:12 Joe, so, you know, if you sign up for an account on, you know, you deploy to Heroku, AWS, whatever it is, we give you a super simple snippet, you put that in in your website, and you start collecting from the word go. That's the super basic kind of version. And that will allow us to do quite a bit of analytics. And we start collecting events straight off. We have libraries for most popular kind of libraries and languages that we have, you know, React Native iOS, Android, we have Python, Ruby, go, etc, etc. So you can start collecting events from the back end as well. The thing that's most challenging, and this is challenging with with all of the kind of product focus on Netflix, is that you need to marry up what happens, you know what the users are doing the front end with what users are doing, the back end does, maybe you don't need analytics in the back end, in which case it's about easier. But you basically need to send something that uniquely identifies the user. So you know, a user ID, so you can work you. So you can kind of like, make sure that all the events that one user does does correctly get grouped under one user. And that's kind of how you does, this tends to be a little bit of challenging and we've, we've made it as easy as possible. But it's a challenge, whether you use your amplitude or mixpanel, or post or then the next step is, you know, in post August, you start, you start creating some dashboards. So you've got all this data, we pre create some of the dashboards for you. But you know, we have kind of like a graph interface that is really powerful, allows you to do all sorts of analytics, you know, things like stickiness, like retention, it allows you to filter by kind of any property that you send, or we send a bunch of properties automatically, you know, so that allows you to create really powerful dashboards really, really quickly
    Easy Data Validation For Your Python Projects With Pydantic
    2020-05-18 (duration 47m)
    45:28 I do I am in terms of books, I would thoroughly recommend flash boys by Michael Lewis. I know it's not that recent, but it's an awesome book. In fact, everything by Michael Lewis, I'm a massive fanboy of him. Then in a more computing specific context, there's algorithms to live by by Brian Christian and Tom Griffis, which is a awesome book. Not it's much better than its title suggests terms of TV. I've really enjoyed sex education on Netflix. If you're bored at home at the moment, I would certainly recommend it is extremely funny. And then in terms of tech, I found recently a website called n which creates a tunnel from a port on your local machine to the public Internet, which is awesomely helpful when developing and you want to show something to someone or if you want to have an HTTPS connection to a local port. That was that was a really nice to find really useful tool.
    Build The Next Generation Of Python Web Applications With FastAPI
    2020-04-20 (duration 58m)
    [from content:encoded] ...navirus Tracker API Terminals from browser: termpair XPublish Uber’s Ludwig Netflix Dispatch Colombia Berlin Germany Explosion AI Python Type Annotations Django Rest Framework Fla...
    43:52 So for example, recently, I saw these, someone built the Coronavirus tracker API. With Coronavirus API data, I was like, Oh, that's, I think that that's very cool that it can help someone build something that is useful for us like, as a society right now and be able to like, get like accurate information easily and like handle it and deal with it with code, which is the thing that we can, like provide them the tool that we can use to to help. So I think that that's a very cool use case. Another one is that Chad's me, the creator of PIP x, created this application called turn pair that allows you allows you to a handle your terminal from the browser and like see the terminal session live in the browser. And it's all built with the fast API and WebSockets. And I think that was like a very, a very cool application that I hadn't thought about like that. You could actually do that. Then it's like all built with us API that was the one was very cool to another one is Expo bridge, which is for publishing X ray X ray a as an API, which is like kind of distributed NumPy integrated with us. And then like they publish that as an API through fast API. I think that's a very, very cool use case. Also, like some of the applications built by Uber and windows and Netflix, they are using fast API in some way, I will share the links with you there. I think that's it's very cool to see the this very known companies also using these tools and like seeing that it's useful for all the levels of organizations and when is
    Security, UX, and Sustainability For The Python Package Index
    2019-08-19 (duration 51m)
    [from content:encoded] Summary PyPI is a core component of the Python ecosystem that most developer’s have interacte...
    50:17 So, last week, or the week before, I watched a documentary on Netflix called the Great hack, which was particularly interesting to me, because I live in the UK. And it talked about Brexit and Cambridge Analytica and and what's sort of been happening, I haven't followed that probably as closely as I should have. So yeah, anybody out there who's kind of interested in documentaries, it's certainly very, very interesting and very topical at the moment with regards to the current political climate.
    Data Management Trends From An Investor Perspective
    2020-06-08 (duration 54m)
    [from content:encoded] ...p Podcast Interview Soda Toro Great Expectations Alation Collibra Amundsen DataHub Netflix Metacat Marquez Podcast Episode LDAP == Lightweight Directory Access Protocol Anodot Data...
    24:28 Yeah, you're right. It's interesting to see that elation and cleaver have been around for the wot a while they're closed source enterprise oriented products. And there's been this new emergence of open source projects from Lyft, LinkedIn, Netflix and then other large businesses like Airbnb and Uber have built their own and publicly talked about it but not open sourced it just yet. The ways we look at the different types of technologies is first you know, closed source versus open source. You know, we are agnostic to that approach, but then also What data sources do they ingest from the stack they use and the functionality that they support? You know, there's a broad range of functionality everything from looking at sample rows, data profiling, freshness, metrics, ownership, top users and queries and lineage in addition to the fundamentals of understanding schemas and metadata. And then in terms of stacks you know, you have Amundson, which is Python node and uses databases like Neo for j s and elastic well, meta cat is job in elastic only based and then finally, in terms of data sources, you know, this is how it could get implemented in environment. For those that are using airflow for dag orchestration Amundson is has a Python library to integrate at that point. Other solutions like LinkedIn data hub tied directly into presto and MySQL and Oracle via API calls or Kafka events. So it really depends On a few factors, as I noted the breadth of the functionality that you're hoping to get from your data catalog, the stack that you are familiar with and comfortable with adopting. And finally, what are your data sources and your perspective of how best to integrate a data catalog if you're not using airflow Amundson may not be the best choice for you. A lot of businesses are using airflow, so it's a great option. It just really depends on your local environment. And I think that's why we see so many different offerings in the space today.
    Enterprise Data Operations And Orchestration At Infoworks
    2020-05-04 (duration 45m)
    05:14 You know, this is a great question. You know, if you look at the usage of data and how people are managing their data assets, you can, you know, really segment the world into two sets of companies that are the bond digital companies like the Google, Facebook, Amazon, Netflix and Zynga and so on, where they have a foundational platform on which they are essentially always building out a 360 degree view of their business. On the other side, you have all these other companies who are in various stages of data maturity, where the approach is to do use case by use case, you know, sort of a build out. So they are gathering data for every use case. And as a result, there is a fragmentation of the data assets within the company and to gather a 360 degree view of the business it becomes, you know, pretty challenging. In this world, I mean, you know, it's not built on a foundation platform so much. It's built on point tools. And there is a lot of glue code that dominates the world. And that becomes also very challenging. The data gets fragmented, teams get fragmented, the skill sets gets fragmented. So these are some fundamental challenges that many companies are facing when they have to deal with, you know, data that represents the business, you know, you can call it big data, because the amount of data is also large, the complexity is pretty large. And and how do you sort of manage all of this becomes very critical.
    Building Real Time Applications On Streaming Data With Eventador
    2020-04-20 (duration 50m)
    [from content:encoded] Defined Functions Change Data Capture Podcast Episode AWS Kinesis Uber AthenaX Netflix Keystone Ververica Rockset Podcast Episode Backpressure The intro and outro musi...
    27:04 Yeah, and that's a really, that's a really good point to make is that, you know, once you start, if you want to build this, you know, this kind of real time architecture in your company, in many cases you can, you'll have the talent to do it. engineering talent is prevalent these days. And you know, and ultimately, these applications are business critical. You're building something that business really needs to compete, and it's market space. And data is king, right? So the thought is like, well, I'll just go build this stuff. And you know, I'll use Kafka and I'll use Flink, and I'll build this stuff myself. And you know, companies have you've seen Uber build Athena x, you've seen Keystone by Netflix, and there's others, but those companies have put massive resource and massive time and energy into building this platform. And ultimately, like it just lets the customer self serve and the development customer self serve and build apps. And that's great. I think that if you're, you know, not Uber, or you're not, you know, one of these gigantic companies monoliths, then you probably do need to think about vendors in this space us or someone else to help glue together a lot of these pieces, because, you know, like I said earlier Stream Processing from a is a different mental state than then database engineering to some degree, the same thing with kind of like even if you're coming from the Hadoop Distributed batch data landscape, these are very similar, but also very different kind of mind shifts and how you deal with streaming data. How late data is, you know, you think about, you know, late data, how you think about schemas in a in a schema list world, how do you mix those two things? You know, obviously, sequel requires strongly typed data and a fixed schema, that's also pretty common for people just to jam whatever JSON into Kafka. How do you reconcile those two events? How do you get a strongly typed schema out of a JSON blob that people are throwing into Kafka? So you know, these are these are and then how do you support all that all day, all night? The whole time? And I think on a planet scale, and I think that you know, in those cases, you do need a good partner. You do need someone who's very good with support and understands the underlying technology stack To help you keep these things running, you know, I said earlier that, you know, a lot of these are production of business critical applications. And once you start to compete with your, in your market space with, you know, real time apps, and you know, maybe you're running machine learning models, or, or maybe you're just building really, really cool dashboards that customers, you know, the customers are attracted to. So they're buying more of your product, once you start getting those things up and running, you can't just back away from them their production jobs and they're in it's very important to your business. So getting again, getting a good partner that understands that stack and the nuances within the stack, I think is a pretty key and core thing. And then understanding that, you know, I should be able to the state of the art, I think for you know, the kind of the, the end state that's great for companies that is that they can self serve data, they can look at a stream of data, they can inspect it, they can pick the pieces they want, they can build their own filters and aggregations and then they can self serve it to whatever application they're building. Like that's the holy grail, I think. And you see and that's why you know, Athena x and the other platform rebuilt This is so that, you know, the data engineering folks, typically there's a few of them, even in big companies are can keep up with the demand from the business in terms of building real time apps. And I think that's a really nice goal for us from a design aspect for event to door. And I think, you know, companies should be looking and thinking in that way as well, because there's only going to be more applications being built on streaming data going forward. And, you know, how are you going to keep up? And so that's, that's why support and the right platform, I think matter a ton.
    The Life Of A Non-Profit Data Professional
    2020-03-31 (duration 44m)
    28:07 Yeah. So I was sitting around as we record about two weeks ago now and just looking at kind of the state of affairs in the state of the crisis and where experts were saying it was going to trend to and having been in the nonprofit vertical for so long, I knew that, you know, not only was the virus going to impact it, and you know, the public health crisis. But as we look to all of the other impacts of this crisis, as it unfolds on the market crashes, a very big impact as well, because usually the first thing to dry up during this time is funding to nonprofits. And it's these community facing organizations that are really going to fill in those critical infrastructure gaps that are left as we go. And so making sure that our food banks, our animal shelters, our homeless populations, and so many other key areas of our society are already served by these organizations that they still have a path to receive these services in this new and changing way that we interact with each other was really a focus. So when I took a look at, you know, all the things that are really unique and special about the Salesforce nonprofit community, one of the main things that we do is called a community sprint and the Salesforce nonprofit team called have been holding these community sprints for a number of years. And typically these are in person to day events where a whole bunch of professionals I think the last one that I was out with somewhere around 250 professionals all fly in from around the country. We sit in a conference room, we break it apart into small groups, so similar to a hackathon and we just work on issues and then we donate all that code back to the community and back to Salesforce. Salesforce is a nonprofit platform, which is called the nonprofit success pack. So all of that is open and available to any nonprofit that's on the Salesforce platform. So really, what I was looking to do was say, Hey, we need to have a sprint and we need to have multiple Sprint's that can be done virtually, so that we can start to bring these technology professionals together and start to give our time back to these community organizations during this time. So we need to instead of, you know, taking these off the calendar, we need to ramp up our efforts at this time. But more than that, it's you know, not just about the Salesforce community, and it's not just about, you know, what we can do on this side of the fence. It's really a call to all technology professionals to stop and say, you know, during this time of self isolation, instead of just clearing out the Netflix queue, or, you know, getting to those video games that you're looking to, you know, spend a little bit extra time on or whatever it is that you're doing to, you know, kill all this extra time, turn your focus to the community who do you know, in the community that could use a little bit of help, so whether that's helping somebody set up a zoom in an afternoon, you know, I had multiple conversations, we're just setting up zoom so that people can meet face to face have a conference call. These are things that we take for granted on a daily basis. A lot of these technologies and just allowing that business continuity can mean the difference between the life and death of some of these organizations. So, you know, turn the focus around. So even if it's not specifically within the confines of you know what we're doing within the Sprint's, just take a look at the community and see what you can do and don't take the technology background that you have for granted. And make sure that you're using it in this time is really our message.
    Solving Data Lineage Tracking And Data Discovery At WeWork
    2019-12-16 (duration 1h1m)
    13:17 Yeah, sure. So, as Julian mentioned, we work airflo has quickly become an important component of our data platform that's powering billing as well as space inventory. So internally, nationally, we've prioritized adding airflo support for Marquez. So the integration allows us to capture metadata for workflows, managed and scheduled by airphone. Enabling, you know, data scientists and data engineers to better debug problems as they come up. One answer that a lot of our data scientists and analysts really care about is that also common question, but really hard to answer is why is my my was my workflow failing and allowing you know One solution to this and one key feature of Marquez is the data lineage graph, that it's maintained on the back end. So the integration allows us to checkpoint the run state of a workflow, understand the run arguments to the pipeline itself. And conveniently, a pointer to the workflow definition and version control. The some of the other integrations that we've been focusing on is with iceberg, so it's a really exciting project that was open source by Netflix. And it now I think it's incubating in the incubating as an Apache project. And iceberg is is a table extraction on that table extraction for data sets that are stored across multiple partitions in a in a file system. So with with that, you know, iceberg does allow us to begin to version files in s3 and capture metadata around around file systems.
    Data Orchestration For Hybrid Cloud Analytics
    2019-10-22 (duration 42m)
    38:43 Yeah, absolutely. So last year is an open source project. And so actually we have a lot of information openly available on our on our site and you know, it's free, you're down to download Community Edition. We also have we are putting together a Data orchestration summit that is planned for November the seventh and it's it's a great lineup of speakers. We have thought leaders from, from Netflix from O'Reilly DBS bank, Walmart coming into present. And we actually have a special offer, I think as well. So you can use the code podcast for 25% off on our registration. And the data orchestration summit will help you understand not just about Alex, you a little bit more about Alex, you but the other data engineering tools that are out there that can improve the efficiency and help these unsung heroes that are the data engineers.
    Keeping Your Data Warehouse In Order With DataForm
    2019-10-15 (duration 47m)
    [from content:encoded] ...nalytics and AI platforms. Attendees will hear from companies including Walmart, Netflix, Google, and DBS Bank on how they leveraged technologies such as Alluxio, Presto, Spark, Tensorf...
    00:11 Hello, and welcome to the data engineering podcast the show about modern data management. When you're ready to build your next pipeline, or you want to test out the project to hear about on the show, lean somewhere to deploy it, so check out our friends at live node. With 200 gigabit private networking, scalable shared block storage and a 40 gigabit public network you get everything you need to run a fast, reliable and bulletproof data platform. If you need global distribution they've got that coverage to with worldwide data centers, including new ones in Toronto and Mumbai. For your machine learning workloads. They just announced dedicated CPU instances. Go to data engineering slash Linux that's LINODE today to get a $20 credit and launch a new server and under a minute, and don't forget to thank them for their continued support of this show. This week's episode is also sponsored by data coral They provide an AWS native server lists data infrastructure that installs and your VPC data coral helps data engineers build and manage the flow of data pipelines without having to manage any of their own infrastructure. Data corals customers report their data engineers were able to spend 80% of their work time invested in data transformations rather than pipeline maintenance. Roku Murthy founder and CEO of data core Oh builds data infrastructures at Yahoo and Facebook scaling from mere terabytes to petabytes of analytic data. He started data Cora with the goal to make sequel the universal data programming language. Visit the data engineering slash data coral today to find out more. Are you working on data analytics or AI using platforms such as presto, spark or TensorFlow, check out the data orchestration summit on November 7 at the Computer History Museum in Mountain View, California. This one day conference is focused on the key data engineering challenges and solutions around building analytics and AI platforms. Attend We'll hear from companies including Walmart, Netflix, Google and DBS bank on how they leverage technology such as a luck, CO, presto, spark and TensorFlow. And you will also hear from creators of open source projects including Alexia presto, airflow and iceberg many of whom you've heard on this show. Use discount code podcast for 25% off of your ticket and the first five people to register get free tickets. Register now is early bird tickets are ending this week. attendees will take away learnings swag, a free voucher to visit the museum but a chance to win the latest iPad Pro. You listen to this show to learn and stay up to date with what's happening in databases, streaming platforms, big data and everything else you need to know about modern data management. For even more opportunities to meet listen and learn from your peers you don't want to miss out on this year's conference season. We have partnered with organizations such as diversity Caribbean global intelligence Alexia and data Council. Upcoming events include the combined events of the data architecture summit and graph forum, the data Oracle summit ended data Council in New York City. Go to data engineering slash conferences today to learn more about these and other events and to take advantage of our partner discounts to save money when you register. Your host is Tobias Macey. And today I'm interviewing Lewis Hammons about data form a platform that helps analysts manage all data processes and your cloud data warehouse. So Louis, can you start by introducing yourself?
    Navigating Boundless Data Streams With The Swim Kernel
    2019-09-18 (duration 57m)
    49:03 So what's hard is that the real world is not the cloud native world. So we've all seen tablets, examples of Netflix, and Amazon and everybody else doing cool things with data they do. But you know, if you're an oil company, and you have a regarded See, you just don't know how to do this. So, you know, we can come at this, with whatever skill sets we have, what we find is that the real world large enterprises have today are still acres behind the cloud native folk. And that's a challenge. Okay, so getting to be able to understand what they need, because they still have lots of assets, which is generating tons of data is very hard. Second, this notion of edge is continually confusing. And I mentioned previously that, that I would never I've chosen IOTHS, for example, that as your name, because it's not about IoT, or maybe it is, but you may give you two examples. One is traffic lights, say physical things, it's pretty obvious that you're, what the notion of edge is its physical edge. But the other one is this, we build a real time model for millions 10s of millions of headsets for a large mobile carrier in memory, and devolve all the time, right in response to continue to receive signals from these devices,
    The Alluxio Distributed Storage System
    2019-02-19 (duration 59m)
    [from content:encoded] Summary Distributed storage systems are the foundational layer of any big data stack. There are a v...
    26:26 Tobias Macey: Yeah, and another possible approach to that would be to rely on other metadata storage systems were particularly for Hadoop where you have something like the hive meta store, or the iceberg table format that's being worked at in Netflix and with other people, where you can potentially interface with those metadata storage systems that are already doing the work of parsing the records within those more high level storage formats, and then be able to use that to determine which subset of files have the information you need to then retrieve into a look. Yeah,
    Data Serialization Formats with Doug Cutting and Julien Le Dem
    2017-11-22 (duration 51m)
    20:58 So yeah, I can give a little bit of the history. I think strafed protocol buffer and Avro preceded parking and parking kind of build the tried to be complimentary to them, like one of the things they define is the ideal, and how you define your type system. And Avro is definitely better at all the parts about whole kind of pipelines type of codes when you need to understand the schema and do transformations, and makes this easier to deal with schema evolution and understanding the schema and be more self describing and passing the schema schema along with the data. And so parquet is trying to not redefine the ideal, but just define a columnar format that you can can become complimentary to those things, right. So you can reuse your same you have the seamless replacement when you can use your same ADL that you're using with arrow, for example, that describe your type system. And use these columnar representation on disk when it's convenient, right when it's the right use case. So maybe you are using ever before. And you can still use Avro as your model, but you can swap with the arrow fight format, which is reoriented when it's useful. And you can swap to park a column now representation when it's better for a sequel analysis. So that's one in and so in the history of market versus RC, I think back in the day there was these need for a column narrow presentation on on these for Hadoop, right? So I this use case when I was at Twitter was trying to make Hadoop more like vertical. And there was this need, and you know, there was a little bit of overlap on people working on those columnar format. And then you start talking about it when it's ready, right. So you kind of publicize it and you say, hey, look, it's open source, we're trying to build that we think there's a need for it. So it's a little unfortunate that you know, bad today, I connected with an Impala team that was trying to do something as well. And later on, we connected with other teams and kind of grow the park a community that there was these parallel efforts. So you know, their representation of nested data structures is different. So Parker uses a Dremel model. And, or sees using a different model, where they're going to have very similar characteristics, because they're trying to solve the same problem. I think parquet has been better at integrating in the ecosystem. Like from the beginning, I was really aware that I didn't want to build another proprietary file format, you know, same problem that if you're importing a database, your data, then you can use it only in your database, I really wanted it to become like a standard for the ecosystem. So from the beginning, from the community building point, have you I spent a lot of work kind of making sure people's opinion were integrated into design, like the drill Apogee drill team had some needs for new types. And we integrated their needs, the entire team was coming with a c++ native code execution engines. So the market format is very language agnostic, and we merged our designs early on to create parking. And so it's been very open and making sure like people would come and get what they need. So a team at Netflix did the work of integrating with crystal, and they had some special needs, because they were using Amazon and s3 at the time. So we made we did the work to make sure it would work well for their use case, as well. And just being often and at some point, you reach a critical mass, and I more people start using it, because that's what you know, they see it starting as their email teams and projects using it, that didn't make sense for people to reuse the same format instead of inventing their own. So I think that was part of their success of 4k was to be very open and very inclusive in the community early on. And you know, sparks equal started using parky. And we didn't even have to help them, right, they just decided to do it. And indeed it and once you were done, they talked about it. So you know, the effort you put early on to be inclusive, it paid off pretty well. And now Park is pretty much supported everywhere. And but i don't think i think you know, technically, the characteristic of Paki are going to be very similar to RC. But what makes it more valuable, I think and again, you know, being the party guy, I'm biased. But I think that's something that was important to me early on, to make sure that we were making something standard that we, you know, we keep the flexibility of Hadoop, which is the beauty of the ecosystem is, there are all those tools you can use. And you're not like siloed in one tool because of the strategy or you pick. And so the last part is talking about arrow. So it's kind of the next step. So we talked about serialization format. And so our role and parky as a storage layer on top of Hadoop in HDFS and arrow it thinking about, you know, the same problematic but in main memory, because the access patterns and the characteristics, you know, the latency of accessing main memory computing to accessing this different. So when you are storing data in memory, you similarly there are benefits to using columnar or presentation in memory that is zero. But the trade offs are different, right, the latency of accessing memory versus disk is different. You want to optimize more for the throughput of the CPU than in arcade, you want to optimize more for the speed of getting it off of disk. So there are different trade offs that weren't a different format. And so that's where arrow is more from in memory processing. And you know, as technology has evolved, we used to have, you know, late domain memory, and more disks. And now there's more and more main memory, and there are more tears showing up, because now we used to have spinning disks, now you FSS DS, with flash memory, and you also of envy me, which is non volatile memory, which is flash, but in the dim slots. And so you have different characteristics of the latency of accessing the data, the throughput of reading the data are different, right. So you have different trade offs, and also the cost of storage. So the how much main memory versus how much envy me versus how much is the versus how much is being destroyed you have. And so those different trade offs will apply, right, you have more range of where you store the data, and how fast you can access it and process it.
    EP4: Ladies, we got this.Technology For Midlife Madness
    2019-10-25 (duration 37m)
    12:00 Netflix.
    12:03 Netflix.
    16:36 Netflix
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