Summary Object storage is quickly becoming the unifying layer for data intensive applications and analytics. Modern, cloud oriented data warehouses and data lakes both rely on the durability and ease of use that it provides. S3 from Amazon has quickly become the de-facto API for interacting with this service, so the team at MinIO have built a production grade, easy to manage storage engine that replicates that interface. In this episode Anand Babu Periasamy shares the origin story for the MinIO platform, the myriad use cases that it supports, and the challenges that they have faced in replicating the functionality of S3. He also explains the technical implementation, innovative design, and broad vision for the project.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With 200Gbit private networking, scalable shared block storage, and a 40Gbit public network, you’ve got everything you need to run a fast, reliable, and bullet-proof data platform. If you need global distribution, they’ve got that covered too with world-wide datacenters including new ones in Toronto and Mumbai. And for your machine learning workloads, they just announced dedicated CPU instances. Go to dataengineeringpodcast.com/linode today to get a $20 credit and launch a new server in under a minute. And don’t forget to thank them for their continued support of this show! 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 O’Reilly Media, Dataversity, Corinium Global Intelligence, and Data Council. Upcoming events include the O’Reilly AI conference, the Strata Data conference, the combined events of the Data Architecture Summit and Graphorum, and Data Council in Barcelona. Go to dataengineeringpodcast.com/conferences to learn more about these and other events, and take advantage of our partner discounts to save money when you register today. Your host is Tobias Macey and today I’m interviewing Anand Babu Periasamy about MinIO, the neutral, open source, enterprise grade object storage system.

Interview

Introduction How did you get involved in the area of data management? Can you explain what MinIO is and its origin story? What are some of the main use cases that MinIO enables? How does MinIO compare to other object storage options and what benefits does it provide over other open source platforms?

Your marketing focuses on the utility of MinIO for ML and AI workloads. What benefits does object storage provide as compared to distributed file systems? (e.g. HDFS, GlusterFS, Ceph)

What are some of the challenges that you face in terms of maintaining compatibility with the S3 interface?

What are the constraints and opportunities that are provided by adhering to that API?

Can you describe how MinIO is implemented and the overall system design?

How has that design evolved since you first began working on it?

What assumptions did you have at the outset and how have they been challenged or updated?

What are the axes for scaling that MinIO provides and how does it handle clustering?

Where does it fall on the axes of availability and consistency in the CAP theorem?

One of the useful features that you provide is efficient erasure coding, as well as protection against data corruption. How much overhead do those capabilties incur, in terms of computational efficiency and, in a clustered scenario, storage volume? For someone who is interested in running MinIO, what is involved in deploying and maintain

Highlights  With a head-to-head comparison between the Apple Music Video and YouTube Music Video charts, we’ll expand your understanding of chart behavior through a chart velocity analysis. Mission   Good morning, it’s Rutger here at Chartmetric with your 3-minute Data Dump where we upload charts, artists, and playlists into your brain so you can stay up on the latest in the music data world.We’re on the socials at “chartmetric” — that’s Chartmetric, no “S.” Follow us on LinkedIn, Instagram, Twitter, or Facebook, and talk to us! We’d love to hear from you.DateThis is your Data Dump for Friday, Sept. 13th, 2019.Apple vs. YouTube Music Video VelocityLooking at Apple Music Video and YouTube Music Video charts, pure chart rank can tell us a lot — but not everything.And that’s where chart velocity comes in. Chart velocity measures a track’s — or in this case, a music video’s — behavior on a chart within a predetermined time period.For the Apple Music Video and YouTube Music Video charts, we track 7-Day Velocity, or how a given music video has performed on each chart in the last week — irrespective of its pure position.It could be No. 1, or it could be No. 150 — what we’re looking at here is time-constrained growth trends, which can expand our understanding about how contextual factors might be influencing those micro-trends.For Apple, Post Malone’s “Sunflower” leads with a Velocity of a bit more than three, even though its pure chart rank is No. 42.Lil Nas X’s “Old Town Road” is next up at two, even though its pure chart rank is No. 28.Both songs were released about a year ago, give or take, which makes sense if you consider that Apple isn’t a music video platform, so major hits just kind of linger.However, YouTube features the actual newest viral videos.And that’s probably why YouTube’s Velocity leaders are totally different, as is the correlation between their Velocity scores and their pure chart ranks.On YouTube, Polo G’s “Effortless” leads with a bit more than seven, in terms of Velocity rank.The music video is ranked 11th overall.At second is Tainy, Anuel AA, and Ozuna’s “Adicto,” which is ranked No. 6 overall with a 2.6 Velocity score.Here’s the interesting thing: Polo G’s music video has jumped some 50 spots, and “Adicto” had an 18 spot fluctuation. On Apple Music, the change was nine and 13 spots, respectively. Couple that with the fact that Apple’s top velocity music videos are near catalogue material and YouTube’s top velocity music videos are decidedly frontline, and you get a sense of what Velocity is measuring on each respective platform.Note, for instance, that songs from Post Malone’s new album, which was released just a week ago, are in every Top 10 spot on the Apple Music Daily Track chart.On YouTube, only two are — “Sunflower” and “Circles.”As such, on Apple, music videos can continue to climb the charts, irrespective of release date and according to new album marketing drivers.On YouTube, music videos climb the charts according to freshness and virality.Or so it seems.Outro That’s it for your Daily Data Dump for Friday, Sept. 13th, 2019. This is Rutger from Chartmetric.Free accounts are available at chartmetric.com And article links and show notes are at: podcast.chartmetric.comHappy Friday, have a great weekend, and we’ll see you next week!

Send us a text In this episode of Making Data Simple, our guest is Jayson Gehri, Marketing Director for the IBM Hybrid Data Management portfolio. Host Al Martin turns to Jayson to provide marketing insights, specifically regarding the technology sector. Together, they cut through the jargon and explain some of the most important marketing concepts that you should be considering. Connect with Jayson Gehri LinkedIn Show Notes 02:52 - Check out this article offering their thoughts on the state of Data and AI.  04:57 - Get a sneak peak on what the new Tesla truck may look like, thanks to these renderings.  14:26 - Here's a profile on Edward Bernays. 18:55 - Here are 8 Keys to a Strong Marketing Strategy. 21:16 - Learn more about the Maldives here. Connect with the Team Host Al Martin - LinkedIn and Twitter. Producer Liam Seston - LinkedIn. Producer Rachit Sharma - LinkedIn.  Producer Lana Cosic - LinkedIn. Producer Meighann Helene - LinkedIn.

Content Manager Eric Hausken - LinkedIn. Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

With the growing popularity of machine learning and artificial intelligence, creating a data science program is a key initiative at most companies today. However, it’s not always clear to executives how they can deliver a return on investments in data science. To explain this, we invited an expert who has spent most of his career in the data science trenches and has a clear-minded perspective on how to deliver ROI with data science.

Alan Jacobson is the chief data and analytics officer (CDAO) of Alteryx, driving key data initiatives and accelerating digital business transformation for the Alteryx global customer base. As CDAO, Jacobson leads the company’s data science practice as a best-in-class example of how a company can get maximum leverage out of its data and the insights it contains, responsible for data management and governance, product and internal data, and use of the Alteryx Platform to drive continued growth.

Prior to joining Alteryx, Alan held a variety of leadership roles at Ford Motor Company across engineering, marketing, sales and new business development; most recently leading a team of data scientists to drive digital transformation across the enterprise. As an Alteryx evangelist at Ford, Alan spent many years leveraging the Alteryx Platform across the company and witnessed first-hand the impact a culture of analytics can have on the bottom line and what it takes to succeed as a data-driven enterprise.

Summary Data professionals are working in a domain that is rapidly evolving. In order to stay current we need access to deeply technical presentations that aren’t burdened by extraneous marketing. To fulfill that need Pete Soderling and his team have been running the Data Council series of conferences and meetups around the world. In this episode Pete discusses his motivation for starting these events, how they serve to bring the data community together, and the observations that he has made about the direction that we are moving. He also shares his experiences as an investor in developer oriented startups and his views on the importance of empowering engineers to launch their own companies.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With 200Gbit private networking, scalable shared block storage, and a 40Gbit public network, you’ve got everything you need to run a fast, reliable, and bullet-proof data platform. If you need global distribution, they’ve got that covered too with world-wide datacenters including new ones in Toronto and Mumbai. And for your machine learning workloads, they just announced dedicated CPU instances. Go to dataengineeringpodcast.com/linode today to get a $20 credit and launch a new server in under a minute. And don’t forget to thank them for their continued support of this show! Listen, I’m sure you work for a ‘data driven’ company – who doesn’t these days? Does your company use Amazon Redshift? Have you ever groaned over slow queries or are just afraid that Amazon Redshift is gonna fall over at some point? Well, you’ve got to talk to the folks over at intermix.io. They have built the “missing” Amazon Redshift console – it’s an amazing analytics product for data engineers to find and re-write slow queries and gives actionable recommendations to optimize data pipelines. WeWork, Postmates, and Medium are just a few of their customers. Go to dataengineeringpodcast.com/intermix today and use promo code DEP at sign up to get a $50 discount! 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 O’Reilly Media, Dataversity, Corinium Global Intelligence, and Data Council. Upcoming events include the O’Reilly AI conference, the Strata Data conference, the combined events of the Data Architecture Summit and Graphorum, and Data Council in Barcelona. Go to dataengineeringpodcast.com/conferences to learn more about these and other events, and take advantage of our partner discounts to save money when you register today. Your host is Tobias Macey and today I’m interviewing Pete Soderling about his work to build and grow a community for data professionals with the Data Council conferences and meetups, as well as his experiences as an investor in data oriented companies

Interview

Introduction How did you get involved in the area of data management? What was your original reason for focusing your efforts on fostering a community of data engineers?

What was the state of recognition in the industry for that role at the time that you began your efforts?

The current manifestation of your community efforts is in the form of the Data Council conferences and meetups. Previously they were known as Data Eng Conf and before that was Hakka Labs. Can you discuss the evolution of your efforts to grow this community?

How has the community itself changed and grown over the past few years?

Communities form around a huge variety of focal points. What are some of the complexities or challenges in building one based on something as nebulous as data? Where do you draw inspiration and direction for how to manage such a large and distributed community?

What are some of the most interesting/challenging/unexpected aspects of community management that you have encountered?

What are some ways that you have been surprised or delighted in your interactions with the data community? How do you approach sustainability of the Data Council community and the organization itself? The tagline that you have focused on for Data Council events is that they are no fluff, juxtaposing them against larger business oriented events. What are your guidelines for fulfilling that promise and why do you think that is an important distinction? In addition to your community building you are also an investor. How did you get involved in that side of your business and how does it fit into your overall mission? You also have a stated mission to help engineers build their own companies. In your opinion, how does an engineer led business differ from one that may be founded or run by a business oriented individual and why do you think that we need more of them?

What are the ways that you typically work to empower engineering founders or encourage them to create their own businesses?

What are some of the challenges that engineering founders face and what are some common difficulties or misunderstandings related to business?

What are your opinions on venture-backed vs. "lifestyle" or bootstrapped businesses?

What are the characteristics of a data business that you look at when evaluating a potential investment? What are some of the current industry trends that you are most excited by?

What are some that you find concerning?

What are your goals and plans for the future of Data Council?

Contact Info

@petesoder on Twitter LinkedIn @petesoder on Medium

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Closing Announcements

Thank you for listening! Don’t forget to check out our other show, Podcast.init to learn about the Python language, its community, and the innovative ways it is being used. Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes. If you’ve learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story. To help other people find the show please leave a review on iTunes and tell your friends and co-workers Join the community in the new Zulip chat workspace at dataengineeringpodcast.com/chat

Links

Data Council Database Design For Mere Mortals Bloomberg Garmin 500 Startups Geeks On A Plane Data Council NYC 2019 Track Summary Pete’s Angel List Syndicate DataOps

Data Kitchen Episode DataOps Vs DevOps Episode

Great Expectations

Podcast.init Interview

Elementl Dagster

Data Council Presentation

Data Council Call For Proposals

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

Support Data Engineering Podcast

Highlights  TikTok is the new game, but it’s already the 2nd quarter. Let’s dive into one of our newest features, TikTok Top Track and Trending Videos charts.Mission   Good morning, it’s Jason here at Chartmetric with your 3-minute Data Dump where we upload charts, artists and playlists into your brain so you can stay up on the latest in the music data world.We’re on the socials at “chartmetric”, that’s Chartmetric, no “S ”- follow us on LinkedIn, Instagram, Twitter, or Facebook, and talk to us! We’d love to hear from you.DateThis is your Data Dump for Thursday, August 15th, 2019. TikTok Top Tracks and Trending VideosIf you are involved in music marketing at all, or you have a Gen Z-er in your life, you know about TikTok.Owned by Beijing-based Internet company ByteDance, TikTok is arguably the newest place to be when it comes to music discovery, and it’s hard not to be when you take over the giant lip-sync app that was Musical.ly.Earlier this year, ByteDance hit over 1B downloads across their suite of apps, 100M of them in the US and 250M of them in India, according to CNN.Some of its biggest stars are just regular people: teens dancing, moms decorating cookies, people playing practical jokes on each other….but it’s all frequently set to music.So who’s winning that never-ending game for eyes and ears on TikTok?As of yesterday, the top track used was none other than Lil Nas X and Billy Ray Cyrus’s “Old Town Road (remix)”, with 9.3M videos using the now record-breaking track.One thing to note about TikTok as a music platform is that-at least in its current state-it’s not the neatest from a metadata perspective. It’s more about the users’ creativity.As users are free to record and upload video and audio like YouTube, songs can be uploaded with no identifying song name or artist to keep track.Or in Lil Nas X’s case, duplicates. There were two original track copies of “Old Town Road” in the 28th and 34th positions on the top tracks chart yesterday, with 2.3 and 2M videos respectively. So if you include remixes, the track is definitely the top one on the Chinese platform with over 13.6M TikTok videos with the yeehaw anthem.And while there is a Trending Video chart, where Mariah Carey’s 2009 track “Obsessed” is currently the soundtrack for the #1 and #2 videos, you don’t have to go to the trending chart to find non-Top 40 tracks.For example, Why Mona’s 2017 moody electronic cover of the Spice Girls’ “Wannabe” took the #2 spot yesterday with 9.2M videos, due to its viral dance that many users uploaded the song with.In 4th place with 7.6M videos is Sean Kingston’s 2007 track “Beautiful Girls”, where lots of TikTok-ers are do a cute hand dance or some Fortnite moves.Or in 135th place with 791K videos is none other than ABBA, with their 1986 track “Gimme! Gimme! Gimmie!”, because it has a nice “reveal” type of drop into its chorus. Users like to provide some kind of visual surprise or fun moment when it hits.So if you’ve got a catalog track ripe for memes, let her rip, because the world awaits its next hashtag!Outro That’s it for your Daily Data Dump for Thursday, August 15th, 2019. This is Jason from Chartmetric.Our new TikTok Top Tracks and Trending Video charts are now live, check them out with a free account at chartmetric.com Article links and show notes are at: podcast.chartmetric.comHappy Thursday, we’ll see you tomorrow!

Highlights  In Part 3 of the music "trigger cities" mini-series, we explore the music tastes of Mexico City, São Paulo, Buenos Aires, Rio de Janiero, Bogotá, Lima and Santiago.Mission   Good morning, it’s Jason here at Chartmetric with your 3-minute Data Dump where we upload charts, artists and playlists into your brain so you can stay up on the latest in the music data world.We’re on the socials at “chartmetric”, that’s Chartmetric, no “S ”- follow us on Instagram, Twitter, Facebook or LinkedIn, and talk to us! We’d love to hear from you.DateThis is your Data Dump for Wednesday, July 17th, 2019.Latin America "Trigger" CitiesIn case you missed them, we have been working on a written mini-series called “trigger cities”, it’s a concept that Chartmetric’s Partner and Advisor, Chaz Jenkins, an international marketing guru coined many years ago.It’s the idea that in the streaming environment, our algorithms on YouTube, Spotify and all platforms are connected with the tastes of huge cities around the world who also love the same apps.Lauv, the uber-successful independent artist first saw playlist success with his 2017 hit “I Like Me Better” in Southeast Asia! Lauv...is not Asian, but SE Asians adore great pop love songs.Reggaeton from the likes of huge superstars like Colombia’s J Balvin and Puerto Rico’s Bad Bunny are now on top playlists like Spotify’s Today’s Top Hits, a primarily English-language playlist...but their come-up was based on Latin American listeners supporting them more than any other region.So in the interest of knowing what the local markets are like, we wrote about  seven different metropolitan areas in Latin America: Mexico City, São Paulo, Buenos Aires, Rio de Janiero, Bogotá, Lima and Santiago.Five speak Spanish, two speak Brazilian Portuguese, and all love the YouTube.It’s a known fact that Latin America turns to the Google platform more than anything else to listen to music, and the numbers are quite impressive: Bogotá, despite having less than half (10.7M) of Mexico City’s population, took the #1 spot in YouTube views in one week last month with 26.5M views across 1.6M+ artists. The Mexican capital, however, was not far behind with 24.8M, and the two cities seem to be leading YouTube’s consumption in the region, with Lima a distant #3 with 17.1M views.On Spotify, Mexico City-as Spotify’s proclaimed “World’s Music-Streaming Mecca”-took the top spot in the same week with 2.3B non-unique monthly listeners (and this is admittedly odd metric, check the show notes for a link to the explanation), far outstripping Santiago in the #2 spot with 1.5B non-unique monthly listeners (MLs).When it comes to genres, we compiled genre tags on Shazam chart occurrences in these seven cities and found what sounds each city was most curious about when they flipped out their phones.“Urbano latino”-which is primarily reggaeton and Latin trap and the most popular in Santiago, Lima and Bogotá-didn’t show up at all in Brazil, with Brazilian-native genres such as “Sertanejo” (Brazilian country music) asserting their unique identity in the region, with Pop/Rock/Dance all showing strongly in the past month for both cities.This is contrary to the idea that all of Latin America loves reggaeton...just not true.On Instagram, who do you think are the ten most followed artists in the region?Well there’s Selena Gomez, Justin Bieber, Ariana Grande and Beyoncé…...there’s also Maluma and Daddy Yankee...But do you know pop queen Anitta, local icon Ivete Sangalo, comedian-entertainer Whindersson Nunes or the Beyoncé-inspired Ludmilla? They’re all Brazilian, showing how much Brazilians love IG, and also how much they love their own country’s artists.So there’s a taste of Part 3 of our trigger cities mini-series, please do check it out on Medium or LinkedIn and let us know what you think! If you’re into Southeast Asia, we wrote about that too (Medium or LinkedIn). We hope they’re useful insights as you target social media campaigns, forge international collaborations or plan out a tour!Outro That’s it for your Daily Data Dump for Wednesday, July 17th 2019. This is Jason from Chartmetric.Free accounts are at chartmetric.comAnd article links and show notes are at: podcast.chartmetric.comHappy Wednesday, and we’ll see you Friday! 

Have you ever thought it would be a great idea to have a drink or two, grab a microphone, and then air your grievances in a public forum? Well, we did! This episode of the show was recorded in front of a live audience (No laugh tracks! No canned applause!) at the Marketing Analytics Summit (MAS) in Las Vegas. Moe, Michael, and Tim used a "What Grinds Our Gears?" application to discuss a range of challenges and frustrations that analysts face. They (well, Moe and Tim, of course) disagreed on a few of them, but they occasionally even proposed some ways to address the challenges, too. To more effectively simulate the experience, we recommend pairing this episode with a nice Japanese whiskey, which is what the live audience did! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Highlights  Brazilian Bossa Nova legend João Gilberto died over the weekend at the age of 88. We remember “O Mito” and just how timeless he is.Mission   Good morning, it’s Rutger here at Chartmetric with your 3-minute Data Dump where we upload charts, artists and playlists into your brain so you can stay up on the latest in the music data world.Our social media handle is “chartmetric”, that’s Chartmetric, no “S ”- follow us on all your favorite platforms at Instagram, Twitter, Facebook or LinkedIn, and let us know what you think about this or any episode, get the latest and greatest from us daily...we’d also love to get your feedback!DateThis is your Data Dump for Wednesday, July 10th, 2019.Remembering Bossa Nova Great João GilbertoJoão Gilberto, the father of Bossa Nova, died in Rio De Janeiro over the weekend, and we’d be remiss if we didn’t honor his monumental legacy.Gilberto was born in 1931 in the Brazilian state of Bahia, received his first guitar when he was 14, and you might say the rest is history.In 1965, he and American jazz saxophonist Stan Getz won three Grammy Awards for their album Getz/Gilberto, which features their famous recording of “The Girl From Ipanema.”With any legacy artist like Gilberto, whose catalog consists of, well, catalog (as opposed to frontline) recordings, numbers tend to flatline without those big new release marketing drivers.Gilberto’s repertoire has seen a significant uptick in interest across platforms not only in the last week, which is to be expected anytime a music great passes into the next frontier — but within the last two months as well.On Spotify, Gilberto’s follower increase has hovered steadily around a 100 since January, but since May 25, it’s shot up to around 600.While his monthly listeners fell some 5 or 600,000 from early April to early May, by the end of May, they had increased some 3 or 400,000.His Spotify Popularity Index, as a result, lifted some five points from 65 to 70 between May 23 and July 8.On every social platform, save for the Facebook wildcard, interest spikes are understandably, if unfortunately, localized around the news of his death.His Wikipedia views, for example, jumped from around 300 to nearly 70,000.There’s a similar increase on YouTube, where daily views leapt from around 66,000 to 1.2 million.Given his holy status in his home country of Brazil, Sao Paulo and Rio De Janeiro are his top cities by Spotify monthly listeners at 13.6 and 7.3 percent, respectively.On YouTube, however, Paris, France, and Santiago, Chile, are his top cities, both at around 8 percent.As far as countries go, USA, at 15 percent, is his biggest fan behind Brazil, at 17 percent of daily YouTube views.So, while Gilberto is definitely a Brazilian deity in the music world, it’s clear his impact has been global and that it will remain so for many, many years to come.Outro That’s it for your Daily Data Dump for Wednesday, July 10th, 2019. This is Rutger from Chartmetric.Free accounts are at chartmetric.comAnd article links and show notes are at: podcast.chartmetric.comHappy Wednesday, and we’ll see you on Friday!

Highlights  On Part 1 of our streaming manipulation series, we took you on a wild ride into depths of playlist fixing. Today, on Part 2, we’re zeroing in on fake artists.Mission   Good morning, it’s Rutger here at Chartmetric with your 3-minute Data Dump where we upload charts, artists and playlists into your brain so you can stay up on the latest in the music data world.DateThis is your Data Dump for Monday, July 1st, 2019.Enter the World of Streaming Manipulation, Part 2 - Fake ArtistsFor Part 1 of our streaming manipulation series, we covered some funny business in the playlisting world. On Part 2, we’re scratching a different part of streaming’s underbelly: fake artist accounts.Last November, Pop Buzz and others covered a mysterious account uploading ostensibly unreleased Ariana Grande tracks under the name Zandhr.As it turned out, the tracks had been available online for some time, but that didn’t change the fact that a streaming account reportedly not linked to Ariana Grande, according to the BBC, was uploading her intellectual property to potentially profit off of.While the Zandhr account has since been taken down, our data suggests the fake artist accrued 9.5K Spotify followers and almost 30K monthly Spotify listeners, in addition to landing an “Ariana Grande - Every Song” playlist with some 20K+ followers of its own.Playboi Carti found himself in a similar predicament when three different fake accounts — Lil Kambo, Unocarti, and Unocompac — started uploading his tracks, with some pitch-shifting his songs in an attempt to disguise the illegitimate uploads.While both Lil Kambo and Unocarti’s profiles appear to have been taken down, the former amassed a 50K+ playlist reach from 37 playlists and the latter almost a 20K playlist reach from 19 playlists.Unocompac, meanwhile, appears to still have at least one Playboi Carti song up, enjoying 14K Spotify followers and a 30K playlist reach from 54 playlists.The best — or worst — part is that Unocompac’s artist gallery on Spotify includes three out-of-focus nighttime shots of a white suburban teenager posing and throwing up fake gang signs.Shaking my damn head.While this all might seem rather innocuous, as most of these accounts never amass more than a couple of thousand followers, it’s important to remember ...One, fake artist accounts effectively steal intellectual property and income from the legitimate artists they’re “impersonating.”And two, fake artist accounts devalue the work of all legitimate artists who have put their blood, sweat, and tears into making and marketing their art. While this phenomenon probably isn’t something to worry about in the short-term, how it’s handled now will determine how big of a problem it becomes in the long-term.With so many metadata errors, artist-song mismatches, and unclaimed blackbox royalties as a result, the last thing artists need is an army of mysterious impersonators gaming the system. OutroThat’s it for your Daily Data Dump for Monday, July 1st, 2019. This is Rutger from Chartmetric.Free accounts are at chartmetric.comAnd article links and show notes are at: podcast.chartmetric.comHappy Monday, and we’ll see you tomorrow!

Highlights  Fake streams! Playlist manipulation! Fake artists! There’s a lot of buzz about it, but what does this look like in the data?Mission   Good morning, it’s Jason here at Chartmetric with your 3-minute Data Dump where we upload charts, artists and playlists into your brain so you can stay up on the latest in the music data world.DateThis is your Data Dump for Friday, June 28th, 2019.Enter the World of Streaming ManipulationLast week’s streaming code of conduct was signed by more than 20 major companies across the industry to combat streaming fraud, which is good for artist compensation and more forthcoming to the fans.How can we think about this prickly topic from a music data perspective? And when we say “this”, it’s not just fake streams. It’s also playlist manipulation and fake artist accounts.For sure, we are in very murky waters, and there is little actual data on the phenomenon.Recently American indie label Hopeless Records estimated 3-4 percent of global streams could be fraudulent.But a 2015 MBW article mentions how 60% or more Twitter followers on top artist accounts could also be fake.Granted, these are different types of fraudulent behavior, but it’s also a huge delta to try to account for.What we can do though is search for red flags in the music data available to us.For example: if we look at playlist manipulation, here’s one way to look at the data to try to identify potentially iffy behavior:We scanned the playlist charts looking for abnormally high 28-day follower increases, and found a non-editorial hip-hop genre playlist with a 262% increase in followers in the past month.While that could just be great marketing, currently having 110K followers-an impressive number-its max artist monthly listeners, however, is only ~470, which doesn’t seem to match up.This means that the only artist on the playlist that gets a lot of its unique listeners from here is getting less than 1% of its supposed followers actually listening to them.Again, possible, especially since the playlist has about 100 current tracks on it, but it’s ranked in the first third of the playlist, so it’s not likely.That artist, which only has a little over 200 followers, is playlisted among high-profile artists like Eminem, Kanye West and Cardi B, presumably to draw traffic, which would be smart marketing if done legitimately, but if so many followers are not streaming the actual tracks...it smells a little fishy.If that weren’t enough, there’s a three-piece pop band with only 16 followers, and two other rap artists who have 4 and 17 Spotify followers, respectively.All three have their listed label as a series of numbers, then “Records DK” or “DK2”, which is a default label for the distributor DistroKid, if left untouched.DistroKid is one of the most popular digital distributors available to independent artists and an official partner distributor with Spotify.If that still isn’t enough, all the playlist album artwork looks like carbon copies of official Spotify playlist album art. Again, good marketing tactic...or borderline deception?So while it’s admittedly an analytical leap, it is very possible that a playlist curator is buying illegitimate playlist followers to make themselves look good, they dupe unknowing artists into thinking they are getting amazing exposure, and the curator gets paid accordingly and in our opinion, unfairly.We could be completely 100% wrong on this, but the point is, there are certain ways you can look at the music data to try to suss out what’s likely real, and what at least should raise some red flags.We’ll try to unpack some other types of illegitimate activity from a data perspective next week.Outro That’s it for your Daily Data Dump for Friday, June 28th, 2019. This is Jason from Chartmetric.Do you know how NPR does their ask for donations every so often? That’s what we’re about to do now! But we’re just asking for an Apple Podcasts rating.Rutger and I put at least a few hours a day into each episode, researching, writing, editing, recording, editing again, publishing to multiple platforms, checking analytics...and it’d be really cool for us to get some feedback on how we’re doing: the good/bad/ugly. So it’d only takes a few thumb swipes out of your day, and you’d be sending us so much joy: we’d appreciate it.As always, free accounts are at chartmetric.comAnd article links and show notes are at: podcast.chartmetric.comHappy Friday, have a great weekend, and see you on Monday!

HighlightsFollow us down to the trigger cities of Southeast Asia where their Shazam, Spotify, and YouTube charts have some big implications for tour strategy and catalog exploitation.Mission   Good morning, it’s Rutger here at Chartmetric with your 3-minute Data Dump where we upload charts, artists and playlists into your brain so you can stay up on the latest in the music data world.DateThis is your Data Dump for Thursday, June 27th, 2019.Trigger Cities in Southeast Asia On our blog this week, Jason did an epic analysis of Southeast Asia’s trigger cities, revealing what implications their Shazam, Spotify, and YouTube charts have for tour strategy and catalog exploitation.We’re just scratching the surface of it here.First, Shazam. From Singapore’s 41 pop genre tags to Jakarta’s 40 to Kuala Lumpur’s 37 down to Bangkok’s 30, an overwhelming Southeast Asian love of pop music in the past month would be an understatement.However, the region doesn’t appear to care much about querying hip-hop or rap, as the genre only makes a 10th place appearance in Jakarta.On Spotify, K-pop group BLACKPINK is currently the hottest act throughout the region, having 2.11M monthly listeners in the past month.Our good friend Lauv (remember him from our June 3 episode?) slides into #2 with 2.10M monthly listeners.With the exception of BLACKPINK, all other artists have US or UK origins.Given Spotify’s northern European origins and that its most popular artists are also of Western origin, this makes sense.Ho Chi Minh City, Vietnam, however, seems to exist in its own silo. More commonly known as Saigon, locals prefer Korean acts, sharing a love of K-pop boy band SEVENTEEN with Bangkok.But the city’s #1 most listened-to artist on Spotify is their “queen of V-pop,” Mỹ Tâm. An outlier here, however, is Ho Chi Minh City’s third most listened to artist on Spotify: Nashville’s Landon Austin.Austin’s covers are apparently catnip for Southeast Asia’s love of non-controversial pop, because his top five cities by Spotify monthly listeners are all in Southeast Asia.Should Austin be touring the region like a madman, then?Based on the available data, it sure looks like it, but we can’t rule out the possibility of bots and bought streams — for which a lot more research still has to be done.On YouTube, BLACKPINK and BTS, two of Korea’s biggest international acts, consistently appear in the top 10 artists by YouTube daily video views.Aggregating the top 10 artists of each of the six Southeast Asian cities for YouTube daily views, the #6 most viewed artist is Brad Kane. If you missed our May 16 podcast episode on Quezon City, Kane was the titular character’s original singing voice for the 1992 Disney animated film Aladdin, which has just been re-released as a live action film starring Will Smith.The fact that the New York City actor, singer, and producer’s rendition of “A Whole New World” has stirred up so much engagement 27 years later in Southeast Asia says something about how locals consume music … not necessarily to support the artist, but for their own karaoke endeavors!So, if you’re looking to exploit catalog records, this might be the perfect spot.But don’t count out domestic artists.Three Southeast Asian artists make the region’s top 10 most viewed: Bangkok trap rapper YOUNGOHM (at #4 with 1.1M daily views), Indonesian singer Nella Kharisma (at #7 with 637K daily views), and Bangkok punk rock band Labanoon (at #9 with 589K daily views).One distinct takeaway with these domestic artists is that their YouTube support comes exclusively from their home countries. Since all three are proudly delivering content in their mother tongues, they are likely limiting their global market appeal, but it’s also why they resonate so well with their fellow country people.As Jason puts it, looking at a certain market’s music data raises our awareness about who the fans are, what their specific cultural histories have been, and how they are now living as a reflection of it.  Well said, but something to consider beyond the computer screen is the fact that digital behavior doesn’t always correspond directly to behavior in the real world.Which is why, before you completely tailor your tour or marketing strategy to your streaming data, make sure you’ve considered all avenues of information.Spotify numbers don’t always translate to ticket sales.OutroThat’s it for your Daily Data Dump for Thursday, June 27th, 2019. This is Rutger from Chartmetric.If you want to read Jason’s piece in full and look at some pretty charts, it’s up on our blog at blog.chartmetric.io.Free accounts are at chartmetric.comAnd article links and show notes are at: podcast.chartmetric.com.Happy Thursday, and see you tomorrow!

HighlightsWe’re on the road! We’re at A2IM’s Indie Week in New York City, Day 1 is over and my feet hurt.Mission    Good morning, it’s Jason here at Chartmetric with your 3-minute Data Dump where we upload charts, artists and playlists into your brain so you can stay up on the latest in the music data world.DateThis is your Data Dump for Tuesday, June 18, 2019.A2IM Indie Week, Day 1Hi all, Jason reporting from New York City and this will admittedly be a quick one.Day 1 of Indie Week is over, wanted to first share some thoughts before we call it a night.In talks today with various labels, distributors, agencies and so on involved with different sectors of the music business, three takeaways were as follows:People might not always need super-charged, crazy data ninja magic insights...they simply want to know that they got on a playlist.Sometimes there’s so much going with multiple artists on a label roster or they have 30 Spotify or Apple for Artists tabs open, all with multiple tracks on playlists in different territories…...and you just want to know with a simple notification that a certain track made a playlist. We hear you, and simple can also be best.Stream count does not always equal revenue in other categories, like merchandise or branding opportunities or ticket sales.Dependent on genre or the way an artist engages with their fans, they may not be creating crazy streaming numbers on the typical music platforms, but they’ll still be selling out multiple shows or merch items.Maybe they resonate more on physical, or YouTube or terrestrial radio or TikTok, but the streaming playlist world isn’t the end all, be all.On the same token, just because an artist is highly touted with ba-jillion streams, doesn’t necessarily mean they do as well in other revenue categories.So make sure you’re taking all types of data into account, not just spins...any maybe what you really need to be tracking still has yet to find a quality, scalable data solution.Sharing data insights with your artists can help encourage desired behavior.Maybe your artist doesn’t like social media. Maybe they don’t want to tour in a particular part of town. Maybe they don’t want to work on a collaboration with another artist who could widen your fan base...these are all understandable things that from an artist’s perspective, might not be very obvious moves and might feel too “businessey” for them to buy into as a creative being.But most artists today I’d argue are quite data-savvy, and if you shared a certain chart of how that one Tweet you did get them to do helped get them 10 or 100 more followers for them to connect with down the road, all the better. Or that even though they just want to tour stateside...what if they saw their last EP over-indexed by 35% in monthly listeners in Jakarta, Indonesia in the past month...maybe it’s time to renew that passport?All this to say: of course you’re sharing your coolest data insights with your marketing team or promotion person or what have you….but consider being more proactive with sharing them with your artist, because they might just appreciate it!OutroThat’s it for your Daily Data Dump for Tuesday, June 18, 2019. This is Jason from Chartmetric.Free accounts are at chartmetric.comAnd article links and show notes are at: podcast.chartmetric.com.Happy Tuesday, we’ll see you tomorrow from Indie Week! Peace.

Send us a text How did companies like Facebook and Airbnb get so big so fast? What can we learn from them? Why is data so important for growth? Nancy Hensley, Director of Strategy & Growth for IBM Hybrid Cloud, has the answers in this episode of Making Data Simple. Learn how you can use growth hacking strategies to build your business and why growth hacking isn't just for startups. Show Notes 00:25 Connect with Al Martin on Twitter (@amartin_v) and LinkedIn (linkedin.com/in/al-martin-ku) 00:36 Connect with Nancy Hensley on Twitter (@nancykoppdw) and LinkedIn (linkedin.com/in/nancyhensley) 03:30 Explore The Growth Hacker: The next VP of Marketing by Andrew Chen here: http://bit.ly/104Xa0r  03:55 Read Hacking Growth by Sean Ellis & Morgan Brown here: http://growthhacker.com/ 04:55 Visit the Jagermeister website for more information on their company and product: https://www.jagermeister.com/en-CA (must be legal age) 22:15 Find Hooked: How to Build Habit-Forming Products by Nir Eyal here: http://amzn.to/2geOTlp 31:50 Find Rework by Jason Fried here: http://amzn.to/2xIU08B Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Summary Some problems in data are well defined and benefit from a ready-made set of tools. For everything else, there’s Pachyderm, the platform for data science that is built to scale. In this episode Joe Doliner, CEO and co-founder, explains how Pachyderm started as an attempt to make data provenance easier to track, how the platform is architected and used today, and examples of how the underlying principles manifest in the workflows of data engineers and data scientists as they collaborate on data projects. In addition to all of that he also shares his thoughts on their recent round of fund-raising and where the future will take them. If you are looking for a set of tools for building your data science workflows then Pachyderm is a solid choice, featuring data versioning, first class tracking of data lineage, and language agnostic data pipelines.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With 200Gbit private networking, scalable shared block storage, and a 40Gbit public network, you’ve got everything you need to run a fast, reliable, and bullet-proof data platform. If you need global distribution, they’ve got that covered too with world-wide datacenters including new ones in Toronto and Mumbai. And for your machine learning workloads, they just announced dedicated CPU instances. Go to dataengineeringpodcast.com/linode today to get a $20 credit and launch a new server in under a minute. And don’t forget to thank them for their continued support of this show! Alluxio is an open source, distributed data orchestration layer that makes it easier to scale your compute and your storage independently. By transparently pulling data from underlying silos, Alluxio unlocks the value of your data and allows for modern computation-intensive workloads to become truly elastic and flexible for the cloud. With Alluxio, companies like Barclays, JD.com, Tencent, and Two Sigma can manage data efficiently, accelerate business analytics, and ease the adoption of any cloud. Go to dataengineeringpodcast.com/alluxio today to learn more and thank them for their support. Understanding how your customers are using your product is critical for businesses of any size. To make it easier for startups to focus on delivering useful features Segment offers a flexible and reliable data infrastructure for your customer analytics and custom events. You only need to maintain one integration to instrument your code and get a future-proof way to send data to over 250 services with the flip of a switch. Not only does it free up your engineers’ time, it lets your business users decide what data they want where. Go to dataengineeringpodcast.com/segmentio today to sign up for their startup plan and get $25,000 in Segment credits and $1 million in free software from marketing and analytics companies like AWS, Google, and Intercom. On top of that you’ll get access to Analytics Academy for the educational resources you need to become an expert in data analytics for measuring product-market fit. 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 O’Reilly Media, Dataversity, and the Open Data Science Conference. Go to dataengineeringpodcast.com/conferences to learn more and take advantage of our partner discounts when you register. Go to dataengineeringpodcast.com to subscribe to the show, sign up for the mailing list, read the show notes, and get in touch. To help other people find the show please leave

IoT has created a tidal wave that data savvy organizations can turn into profitable business solutions. Most IoT data comes from sensors, which are now attached to almost every device imaginable, from factory floor machines and agricultural fields to your cell phone and toothbrush. But IoT is forcing companies to rethink their data architectures to ingest, process, and analyze streaming data in real-time.

To help us understand the impact of IoT on data architectures, we invited Dan Graham to our show for a second time. Dan is a former product marketing manager at both IBM and Teradata, renowned for combining deep technical knowledge with industry marketing savvy. During his tenure at those companies, he was responsible for MPP data management systems, data warehouses, and data lakes, and most recently, the Internet of Things.

Summary In recent years the traditional approach to building data warehouses has shifted from transforming records before loading, to transforming them afterwards. As a result, the tooling for those transformations needs to be reimagined. The data build tool (dbt) is designed to bring battle tested engineering practices to your analytics pipelines. By providing an opinionated set of best practices it simplifies collaboration and boosts confidence in your data teams. In this episode Drew Banin, creator of dbt, explains how it got started, how it is designed, and how you can start using it today to create reliable and well-tested reports in your favorite data warehouse.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With 200Gbit private networking, scalable shared block storage, and a 40Gbit public network, you’ve got everything you need to run a fast, reliable, and bullet-proof data platform. If you need global distribution, they’ve got that covered too with world-wide datacenters including new ones in Toronto and Mumbai. And for your machine learning workloads, they just announced dedicated CPU instances. Go to dataengineeringpodcast.com/linode today to get a $20 credit and launch a new server in under a minute. And don’t forget to thank them for their continued support of this show! Understanding how your customers are using your product is critical for businesses of any size. To make it easier for startups to focus on delivering useful features Segment offers a flexible and reliable data infrastructure for your customer analytics and custom events. You only need to maintain one integration to instrument your code and get a future-proof way to send data to over 250 services with the flip of a switch. Not only does it free up your engineers’ time, it lets your business users decide what data they want where. Go to dataengineeringpodcast.com/segmentio today to sign up for their startup plan and get $25,000 in Segment credits and $1 million in free software from marketing and analytics companies like AWS, Google, and Intercom. On top of that you’ll get access to Analytics Academy for the educational resources you need to become an expert in data analytics for measuring product-market fit. 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 O’Reilly Media, Dataversity, and the Open Data Science Conference. Go to dataengineeringpodcast.com/conferences to learn more and take advantage of our partner discounts when you register. Go to dataengineeringpodcast.com to subscribe to the show, sign up for the mailing list, read the show notes, and get in touch. To help other people find the show please leave a review on iTunes and tell your friends and co-workers Join the community in the new Zulip chat workspace at dataengineeringpodcast.com/chat Your host is Tobias Macey and today I’m interviewing Drew Banin about DBT, the Data Build Tool, a toolkit for building analytics the way that developers build applications

Interview

Introduction How did you get involved in the area of data management? Can you start by explaining what DBT is and your motivation for creating it? Where does it fit in the overall landscape of data tools and the lifecycle of data in an analytics pipeline? Can you talk through the workflow for someone using DBT? One of the useful features of DBT for stability of analytics is the ability to write and execute tests. Can you explain how those are implemented? The packaging capabilities are beneficial for enabling collaboration. Can you talk through how the packaging system is implemented?

Are these packages driven by Fishtown Analytics or the dbt community?

What are the limitations of modeling everything as a SELECT statement? Making SQL code reusable is notoriously difficult. How does the Jinja templating of DBT address this issue and what are the shortcomings?

What are your thoughts on higher level approaches to SQL that compile down to the specific statements?

Can you explain how DBT is implemented and how the design has evolved since you first began working on it? What are some of the features of DBT that are often overlooked which you find particularly useful? What are some of the most interesting/unexpected/innovative ways that you have seen DBT used? What are the additional features that the commercial version of DBT provides? What are some of the most useful or challenging lessons that you have learned in the process of building and maintaining DBT? When is it the wrong choice? What do you have planned for the future of DBT?

Contact Info

Email @drebanin on Twitter drebanin on GitHub

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Links

DBT Fishtown Analytics 8Tracks Internet Radio Redshift Magento Stitch Data Fivetran Airflow Business Intelligence Jinja template language BigQuery Snowflake Version Control Git Continuous Integration Test Driven Development Snowplow Analytics

Podcast Episode

dbt-utils We Can Do Better Than SQL blog post from EdgeDB EdgeDB Looker LookML

Podcast Interview

Presto DB

Podcast Interview

Spark SQL Hive Azure SQL Data Warehouse Data Warehouse Data Lake Data Council Conference Slowly Changing Dimensions dbt Archival Mode Analytics Periscope BI dbt docs dbt repository

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

Support Data Engineering Podcast

Summary The database market continues to expand, offering systems that are suited to virtually every use case. But what happens if you need something customized to your application? FoundationDB is a distributed key-value store that provides the primitives that you need to build a custom database platform. In this episode Ryan Worl explains how it is architected, how to use it for your applications, and provides examples of system design patterns that can be built on top of it. If you need a foundation for your distributed systems, then FoundationDB is definitely worth a closer look.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With 200Gbit private networking, scalable shared block storage, and a 40Gbit public network, you’ve got everything you need to run a fast, reliable, and bullet-proof data platform. If you need global distribution, they’ve got that covered too with world-wide datacenters including new ones in Toronto and Mumbai. And for your machine learning workloads, they just announced dedicated CPU instances. Go to dataengineeringpodcast.com/linode today to get a $20 credit and launch a new server in under a minute. And don’t forget to thank them for their continued support of this show! Alluxio is an open source, distributed data orchestration layer that makes it easier to scale your compute and your storage independently. By transparently pulling data from underlying silos, Alluxio unlocks the value of your data and allows for modern computation-intensive workloads to become truly elastic and flexible for the cloud. With Alluxio, companies like Barclays, JD.com, Tencent, and Two Sigma can manage data efficiently, accelerate business analytics, and ease the adoption of any cloud. Go to dataengineeringpodcast.com/alluxio today to learn more and thank them for their support. Understanding how your customers are using your product is critical for businesses of any size. To make it easier for startups to focus on delivering useful features Segment offers a flexible and reliable data infrastructure for your customer analytics and custom events. You only need to maintain one integration to instrument your code and get a future-proof way to send data to over 250 services with the flip of a switch. Not only does it free up your engineers’ time, it lets your business users decide what data they want where. Go to dataengineeringpodcast.com/segmentio today to sign up for their startup plan and get $25,000 in Segment credits and $1 million in free software from marketing and analytics companies like AWS, Google, and Intercom. On top of that you’ll get access to Analytics Academy for the educational resources you need to become an expert in data analytics for measuring product-market fit. 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 O’Reilly Media, Dataversity, and the Open Data Science Conference. Go to dataengineeringpodcast.com/conferences to learn more and take advantage of our partner discounts when you register. Go to dataengineeringpodcast.com to subscribe to the show, sign up for the mailing list, read the show notes, and get in touch. To help other people find the show please leave a review on iTunes and tell your friends and co-workers Join the community in the new Zulip chat workspace at dataengineeringpodcast.com/chat Your host is Tobias Macey and today I’m interviewing Ryan Worl about FoundationDB, a distributed key/value store that gives you t

HighlightsTechnique Tuesday: The Game of Thrones album drops on Friday and we delve into its tracks’ playlist distributionMission   Good morning, it’s Jason here at Chartmetric with your 3-minute Data Dump where we upload charts, artists and playlists into your brain so you can stay up on the latest in the music data world.DateThis is your Data Dump for Tuesday April 30th 2019.Technique Tuesday: For The Throne albumLast Friday, HBO’s Game of Thrones worked with Sony’s Columbia Records to release the 14-track album For The Throne, featuring music inspired by the massive series across pop, rap, Latin, rock and folk genres.Three of the tracks were released earlier in the month as teasers to the full-length album, and a few days in, it’s a great time to take a pulse of how its performing in the market.We’ll do that by examining how the popularity among its tracks are distributed via their playlisting distribution.The fan reaction on Spotify and Apple Music seem to be strong: if measured by total current playlists that the tracks are included on, For the Throne was on ~650 playlists on Spotify and ~130 on Apple Music.To put that in perspective, it beats out the Greatest Showman soundtrack, which is on ~600 playlists on Spotify, but it wasn’t quite enough for others.For example, the Spiderman: Into the Spider-verse soundtrack which was released in December of last year is currently on ~2200 Spotify playlists and Queen’s Bohemian Rhapsody is on an astonishing ~8900, though that soundtrack benefits from Queen’s tracks pre-existing for decades before they were included in the film’s album.It’s worth noting that these albums are just like normal album releases in that they usually depend on a leading track to market the rest of the collection.For For The Throne, that track is “Power is Power” by SZA, The Weeknd and Travis Scott, which is on 436 Spotify playlists, including the #17 position on Today’s Top Hits, while the next most playlisted track on the album is “Too Many Gods” by A$AP Rocky and Joey Bada$$ at 128 playlists, which is a decent dropoff.The Greatest Showman soundtrack, which is unique among this group as it showcases the fact that its parent film is actually a musical, also shows a fairly well-distributed playlist dropoff among its three most playlisted tracks as they go from ~320, to ~290, then to ~150 playlists.With the Spiderman soundtrack however, the dropoff is much higher, as Post Malone and Swae Lee’s massively popular “Sunflower” track is on ~1,850 playlists while the next track is only on ~200.Now if a soundtrack is nothing more than a marketing device for its main product, maybe popularity distribution among its tracks is not such a big deal for the TV or film producers, but for the artists involved, it at least shows how much traction the actual music has, as the artists likely got involved for the exposure more than anything else.The editorial playlist support is strong on Spotify, with 56 of those lists containing the album tracks, to include Today’s Top Hits at 23M followers, Teen Party at 3.9M and New Music Friday at 3.1M.Apple Music’s editorial support however is much weaker, with only one A-List playlist listing any of the album’s tracks, and only three of their A&R-focused  “Breaking” playlists (such as Breaking Alternative or Breaking Latino) doing the same.So while the marketing support from the actual platforms can be touch and go, it should at least be comforting for For The Throne’s artists, to know that its fans on Spotify at least are getting their GoT fix via their earbuds, in between episodes.OutroThat’s it for your Daily Data Dump for Tuesday April 30th 2019. This is Jason from Chartmetric.Free accounts are at app.chartmetric.com/signupAnd article links and show notes are at: podcast.chartmetric.com.Happy Tuesday, see you tomorrow! 

Summary Kubernetes is a driving force in the renaissance around deploying and running applications. However, managing the database layer is still a separate concern. The KubeDB project was created as a way of providing a simple mechanism for running your storage system in the same platform as your application. In this episode Tamal Saha explains how the KubeDB project got started, why you might want to run your database with Kubernetes, and how to get started. He also covers some of the challenges of managing stateful services in Kubernetes and how the fast pace of the community has contributed to the evolution of KubeDB. If you are at any stage of a Kubernetes implementation, or just thinking about it, this is definitely worth a listen to get some perspective on how to leverage it for your entire application stack.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With 200Gbit private networking, scalable shared block storage, and a 40Gbit public network, you’ve got everything you need to run a fast, reliable, and bullet-proof data platform. If you need global distribution, they’ve got that covered too with world-wide datacenters including new ones in Toronto and Mumbai. And for your machine learning workloads, they just announced dedicated CPU instances. Go to dataengineeringpodcast.com/linode today to get a $20 credit and launch a new server in under a minute. And don’t forget to thank them for their continued support of this show! Alluxio is an open source, distributed data orchestration layer that makes it easier to scale your compute and your storage independently. By transparently pulling data from underlying silos, Alluxio unlocks the value of your data and allows for modern computation-intensive workloads to become truly elastic and flexible for the cloud. With Alluxio, companies like Barclays, JD.com, Tencent, and Two Sigma can manage data efficiently, accelerate business analytics, and ease the adoption of any cloud. Go to dataengineeringpodcast.com/alluxio today to learn more and thank them for their support. Understanding how your customers are using your product is critical for businesses of any size. To make it easier for startups to focus on delivering useful features Segment offers a flexible and reliable data infrastructure for your customer analytics and custom events. You only need to maintain one integration to instrument your code and get a future-proof way to send data to over 250 services with the flip of a switch. Not only does it free up your engineers’ time, it lets your business users decide what data they want where. Go to dataengineeringpodcast.com/segmentio today to sign up for their startup plan and get $25,000 in Segment credits and $1 million in free software from marketing and analytics companies like AWS, Google, and Intercom. On top of that you’ll get access to Analytics Academy for the educational resources you need to become an expert in data analytics for measuring product-market fit. 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 O’Reilly Media, Dataversity, and the Open Data Science Conference. Go to dataengineeringpodcast.com/conferences to learn more and take advantage of our partner discounts when you register. Go to dataengineeringpodcast.com to subscribe to the show, sign up for the mailing list, read the show notes, and get in touch. To help other people find the show please leave a review on iTunes and tell your fri