Datacast-logo

Datacast

Technology Podcasts

Datacast follows the narrative journey of founders, operators, and investors in the data and AI infrastructure space to unpack the careers that they have built. James Le hosts the show.

Location:

United States

Description:

Datacast follows the narrative journey of founders, operators, and investors in the data and AI infrastructure space to unpack the careers that they have built. James Le hosts the show.

Language:

English

Contact:

5852868783


Episodes

Episode 117: Vector Databases, The Embeddings Revolution, and Working in China with Frank Liu

5/28/2023
Show Notes indoor localization and navigationnormal lifethe pandemic storyZillizthe notion of vector databasesMilvusTowheeopen-source projectZilliz CloudFrank's Contact Info LinkedInTwitterGitHubWebsiteZilliz's Resources WebsiteTwitterLinkedInGitHubYouTubeZilliz Cloud DatabaseMilvusDocsGitHubTowheeDocsGitHubMentioned Content Articles and Presentations A Gentle Introduction to Vector DatabasesMy Experience Living and Working in China, Part IMy Experience Living and Working in China, Part IIMaking ML More Accessible for Application DevelopersUnderstanding Neural Network EmbeddingsBuilding An Open-Source Platform for Generating Embedding VectorsPeople Yann LeCunYangqing JiaSoumith ChintalaBook A Short History of Nearly EverythingNotes My conversation with Frank was recorded back in August 2022. The Zilliz team has had some important announcements in 2023 that I recommend looking at: The landing page of Zilliz CloudThe beta launch of Milvus 2.3The development of GPTCacheThe OSS Chat demo applicationAbout the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Duration:01:09:35

Episode 116: Distributed Databases, Open-Source Standards, and Streaming Data Lakehouse with Vinoth Chandar

5/11/2023
Show Notes Madras Institute of TechnologyComputer Sciencehigh-bandwidth content distributionlarge-scale parallel processing with shell pipesOracleLinkedInVoldemortUberUber's case for incremental processing on Hadoopthe initial design and implementation of Hudithe evolution of HudiApache Software Foundationestablishing standards for open-source data projectsvaluable leadership lessonsConfluentksqlDBthe vision for Apache Hudi as a Streaming Data Lake platformthe Hudi roadmapengaging an open-source communityOnehouseOnehouse's commitment towards opennessVinoth's Contact Info LinkedInTwitterOnehouse's Resources WebsiteTwitterLinkedInAboutProductBlogCareersApache Hudi's Resources User DocsTechnical WikiRoadmapGitHubTwitterSlackMentioned Content Articles and Presentations Voldemort : Prototype to ProductionUber's Case for Incremental Processing on HadoopHoodie: An Open Source Incremental Processing Framework From UberThe Past, Present, and Future of Efficient Data Lake ArchitecturesHighly Available, Fault-Tolerant Pull Queries in ksqlDBApache Hudi - The Data Lake PlatformIntroducing OnehouseAutomagic Data Lake InfrastructureOnehouse Commitment to OpennessPeople Leslie LamportJeff DeanMichael StonebreakerBook Zero To OneNotes My conversation with Vinoth was recorded back in August 2022. The Onehouse team has had some announcements in 2023 that I recommend looking at: The Launch Announcement of OnetableThe $25M Series A Funding AnnouncementOnehouse Availability in AWS MarketplaceOnehouse Product Demo on building a data lake for GitHub analytics at scaleWalmart's recent study on different open-source data lakehouse formatsThis discussion around the Hudi 1.x visionAbout the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Duration:01:32:18

Episode 115: Product-Led Sales, Community-Led Category Creation, and Unlocking Revenue Data with Alexa Grabell

5/2/2023
Show Notes VanderbiltEngineering ScienceKPMGDataminrStanford Graduate School of BusinessMonte CarloPocusProduct-Led SalesProduct-Qualified LeadsSales-Assistthe Product-Led Sales communityevolving a category, a community, and a product all at onceAlexa' Contact Info LinkedInTwitterPocus' Resources WebsiteTwitterLinkedInYouTubeAboutProductBlogCareersCommunityNewsletterMentioned Content Blog Posts What is Product-Led Sales?The Myth of "No Sales" at PLG CompaniesWhen To Add A Sales Team to Your PLG CompanyPart 1Part 2Part 3What Is The Sales-Assist Role?Introducing Pocus' PLS PlatformProduct-Led Sales Community Wisdom Highlights 2021Notes on Community-Led Category Creation with Pocus' Co-Founder, Alexa GrabellSneak Peek at Pocus' PLS PlatformAnnouncing $23M to Transform How GTM Teams Use Data to Drive RevenueYear One: The Product-Led Sales Platform is Here to StayPeople Kyle PoyarMelissa RossAaron GellerNotes My conversation with Alexa was recorded back in July 2022. The Pocus team has had some announcements in 2023 that I recommend looking at: The launch announcement of Pocus' Revenue Data PlatformThe Product-Led Sales Playbook Volume 2The Unlocking Revenue podcastThe Playbook Library for product-led go-to-marketAbout the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Duration:01:08:16

Episode 114: Building Data Products and Unlocking Data Insights with Carlos Aguilar

4/19/2023
Show Notes Cornell UniversityKiva Systems his first data product at Kivaafter the Kiva acquisitionFlatiron Healthbuilding Flatiron's Data Insights team from scratchGleanthe pain points in data visualization/exploration the product features of GleanDataOpsbroken dashboardsCarlos' Contact Info TwitterLinkedInGitHubWebsiteMediumGlean's Resources WebsiteTwitterLinkedInAboutDocsBlogInteractive Public DemoDataOpsMentioned Content Blog Posts How the Data Insights team helps Flatiron build useful data productsThe biggest mistake making your first data hire: not interviewing for productHow to interview your first data hireMy hack for getting started with data as a productIntroducing GleanYour dashboard is probably brokenPeople Vicki BoykisAnthony GoldbloomWes McKinneyBook The Toyota Way: 14 Management Principles from the World's Greatest ManufacturerNotes My conversation with Carlos was recorded back in June 2022. The Glean team has had some announcements in 2023 that I recommend looking at: The recently launched, interactive public demo siteThis recent integration with DuckDBThis post about Version Control for BITheir Public RoadmapAbout the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Duration:01:18:07

Episode 113: Data Applications, Real-Time Analytics, and Cloud Product Management with Shruti Bhat

4/12/2023
Show Notes Hewlett-PackardIBMUCLA Anderson School of ManagementVMwareRavello SystemsOracle'sRocksetreal-time analyticsdata applicationsRockset architecturethe modern real-time data stackuse casesShruti's Contact Info LinkedInTwitterForbesRockset's Resources WebsiteTwitterLinkedInFacebookDocsBlogCommunityProductArchitectureCustomersReal-Time Analytics ExplainedWhat Is A Data Application?Mentioned Content Articles Building Data Applications Powered by Real-Time AnalyticsHow startups can create a culture where women can winStreaming Data and the Modern Real-Time Data StackPeople Barr MosesJay KrepsAlex DeBrieDynamoDB ExpertBook Competing Against LuckNotes My conversation with Shruti was recorded back in June 2022. Since then, a lot has happened. I recommend looking at the resources below: The launch of compute-compute separation for real-time analyticsThis benchmark on top real-time analytics databases in 2023This talk on emerging architectures for real-time CDCAbout the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Duration:01:17:13

Episode 112: Distributed Systems Research, The Philosophy of Computational Complexity, and Modern Streaming Database with Arjun Narayan

4/7/2023
Show Notes UWC Mahindra CollegeWillams Collegethe University of CambridgeUniversity of PennsylvaniaAndreas HaeberlenPh.D. dissertationCockroach LabsCockroachDB Performance GuideRocksDB deep-divedatabase transaction isolation semanticslog-structured merge treesThe Philosophy of Computational ComplexityMaterializeTimely DataflowDifferential DataflowFrank McSherrythe architecture designStreaming SQLopen-source projectenterprise-grade featuresMaterialize CloudMaterialize’s unbundled cloud architectureArjun's Contact Info LinkedInTwitterGitHubGoogle ScholarMaterialize's Resources WebsiteTwitterLinkedInSlackDocsGitHubBlogEventsGuidesCareersMentioned Content Research + Articles Distributed Differential Privacy and ApplicationsPerformance Report: Benchmarking CockroachDB's TPC-C PerformanceWhy We Built CockroachDB on top of RocksDBA History of Transaction HistoriesA Brief History of Log Structured Merge TreesPeople Kyle KingsburyBob MugliaFrank McSherryBook Zero To OneNotes My conversation with Arjun was recorded back in May 2022. Since then, a lot has happened. I recommend looking at the resources below: About Materialize webpageGuide: What is a Streaming DatabasewhyCase Study: Real-time Delivery Tracking UI in a Single Sprint at OnwardTech Demo: CI/CD Workflows for dbt+MaterializeAnnouncing The Next Generation of MaterializeAbout the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Duration:01:49:17

Episode 111: Astrophysics, Visualization Recommendation, and Scalable Data Science with Doris Lee

3/24/2023
Show Notes physicsastrophysicscomputer scienceRISE LabI Schoolher Ph.D. dissertationLuxLuxPonderthe fragmentation challengesModinacross various industriesDoris' Contact Info WebsiteTwitterLinkedInGitHubPonder's Resources WebsiteTwitterLinkedInSlackModinLuxEventsMentioned Content Publications The Case for a Visual Discovery Assistant:A Holistic Solution for Accelerating Visual Data ExplorationUnderstanding Sense-making in Visual Query SystemsDeconstructing Categorization in Visualization Recommendation: A Taxonomy and Comparative StudyLux: Always-On Visualization Recommendation for Exploratory Data ScienceBlog Posts Insight Machines: The Past, Present, and Future of Visualization RecommendationAnnouncing PonderHow we parallelized 600+ pandas functions with ModinUsing Lux to visualize your pandas dataframes with zero effortPh.D. Alum Doris Lee Wants to Democratize Data Science ToolsPeople Chip HuyenShreyar ShankarParul PandeyNotes My conversation with Doris was recorded back in May 2022. Earlier this year, Ponder developed the first-of-its-kind technology that allows anyone to run their pandas code directly in your data warehouse, be it Snowflake, BigQuery, or Redshift. With Ponder, you get the same pandas-native experience that you love, but with the power and scalability of cloud-native data warehouses. More details are in this blog post. Additionally, you can run NumPy commands on your data warehouse as well. This means you can work with the NumPy API to build data and ML pipelines, and let Snowflake / BigQuery / Redshift take care of scaling, security, and compliance. More details are in this blog post. If you are interested in trying these new capabilities out, sign up here! About the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Duration:00:54:50

Episode 110: Wisdom in Building Data Infrastructure, Lessons From Open-Source Development, The Missing README, and The Future of Data Engineering with Chris Riccomini

3/14/2023
Show Notes Santa Clara UniversityNeoMagicIntacct CorporationPayPalLinkedInAster DataGreenplumHadoopmodels and microservices should be running on the same continuous delivery stackApache SamzaWePayApache AirflowApache Kafkathe writing journey of the "Missing README"Dmitriy RyaboyThe Future of Data Engineeringkey trendsa strategic investor and advisorChris's Contact Info WebsiteTwitterLinkedInGithubAngelListMentioned Content Blog Posts Joel Spolsky's BlogModels and microservices should be running on the same continuous delivery stackUsing checksums to verify syncing 100M database recordsDatacast episode with Jeremiah Lowin, CEO of PrefectKafka CDC breaks database encapsulationKafka provides data portability and infrastructure agilityThe Future of Data EngineeringWork For Two CompaniesPeople Will LarsonMaxime BeaucheminJulia EvansGunnar MorlingCoda HaleBooks Google's Site Reliability Engineering BooksOn Writing WellThe Missing READMEEmpire of Light: Tesla, Edison, Westinghouse, and the Race to Electrify the WorldNotes My conversation with Chris was recorded back in May 2022. Earlier this year, Chris released Recap, a dead simple data catalog for engineers, written in Python. Recap makes it easy for engineers to build infrastructure and tools that need metadata. Check out his blog post and get started with Recap's documentation! About the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Duration:02:06:09

Episode 109: Developer Productivity, Real-Time Data Infrastructure, and The Fat-Tailed Nature of Enterprise Software with Nnamdi Iregbulem

2/21/2023
Show Notes Yale UniversityMcKinseyJ.P. MorganJ.P. MorganICONIQ CapitalGitLabStanford Graduate School of BusinessCS 231NCS 224NConfluentLightspeed VenturePonderVoltron DataRedpandaMaterializereal-time data infrastructurehiring decisionsnavigating growth strategymajor industry trendstop strategic prioritiesbiggest challengesadvicescaling their developer relationsthe challenge of hiring developer advocatesthe developer productivity manifestothe developer productivity flywheelmore developers lead to lower productivitywe are leaving on the table $670B of softwarewhy VCs don't index-investwhy Saas monetization is concentrated on the tailswhy product-market fit gets harder to achieve the longer you search for itnew and improved SaaS metric called Weighted ACVa mission to increase total software output by investing in technical tools for technical peopleNnamdi's Contact Info WebsiteLightspeed ProfileLinkedInTwitterGitHubMediumLightspeed's Resources WebsiteTwitterLinkedInGlobal PresenceMedium BlogMentioned Content Articles Six Trends Shaping Developer ProductivityTop Three Strategic Priorities of Developer Productivity StartupsFour Challenges Facing Developer Productivity StartupsAwesome Developer Advocates Are Hiding in Plain SightThe Developer Productivity Manifesto Part 1 — The FlywheelThe Developer Productivity Manifesto Part 2 — More (Developers) Isn’t Always MoreThe Developer Productivity Manifesto Part 3 — Leaving Software on the TableYou Don't Understand Compound GrowthFunding Simply Shifts the BottleneckWhy Don't VCs Index Invest?Enterprise Software Monetization is Fat-TailedProduct-Market Fit is LindyIntroducing a New and Improved SaaS Metric: Weighted ACVPeople Mike VolpiKeith RaboisBooks Nassim Taleb's Incerto Series: Notes My conversation with Nnamdi was recorded in May 2022. Since then, many things have happened. I'd recommend checking out: announcement of the new three funds123the reality of tech layoffsthe need for more startupsrecent investment in Select StarAbout the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Duration:01:15:24

Episode 108: Computer Vision, Product Management, and Enterprise Investing with Tom Rikert

2/16/2023
Show Notes Silicon GraphicsAutodeskHarvard Business SchoolAdWordsYouTube'sWildfirea16zdiscussing the rise of Enterprise Hackershis decision to join NextWorld CapitalMasterful AIthe announcement of the Masterful AI platformMasterful's product roadmapacross various industriesTom's Contact Info LinkedInTwitterMediumWebsiteMasterful AI's Resources WebsiteTwitterLinkedInDocsSlack Community"Building Things with Machine Learning" PodcastMentioned Content Articles The Enterprise Hacker RisesJoining NextWorld CapitalThe Next Big Opportunity In Enterprise Starts In The FieldMy visit to the Obama White House: AI, the future of jobs, and a VC’s Letter to the next administrationAI hype has peaked so what’s next?AI is bringing superpowers to the specialistIntroducing Masterful AIPeople Andrew NgDeepLearning.AIChris DixonBook AI SuperpowersNote My conversation with Tom was recorded back in May 2022. Here is the note from Tom regarding updates with Masterful: The latest at Masterful AI is that we’re launching a new generative AI product. We saw a need to make generative models more customizable and more reliable, so companies can trust them for real business applications. We’re starting by enabling companies to tell a more vivid and personalized story about their products at scale. About the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Duration:01:11:07

Episode 107: Investing At The Nexus of Computational Sciences with Grace Isford

2/10/2023
Show Notes Management Science and Engineeringthe Mayfield FellowshipStanford Women in BusinessStanford Management CompanyHandshakeStripes GroupCanvas VenturesSeries A investment in VendiaSeries A investment in RobocorpThe Mindset of a Data Leaderincredibly detailed deck on the Web3 WorldLux CapitalGrace's Contact Info WebsiteLux ProfileLinkedInTwitterLux Capital WebsiteTwitterLinkedInSecuritiesMentioned Resources Articles The Third-Party API Economy: Part IThe Third-Party API Economy: Part IIThe Mindset of a Data LeaderThe Web3 WorldWelcoming our newest investor Grace Isford to Lux CapitalPeople Fred WilsonMatt HuangFred EhrsamKatie HaunBook WantingNotes My conversation with Grace was recorded back in April 2022. Since then, many things have happened. I'd recommend: Tina SeeligChristian Catalinibuilding the next AI/ML infrastructure stackthe intersection of AI and creativityAdditionally, Grace invested in RunwayML's Series C, a pioneer in the Generative AI space. If you are in NYC, be sure to stop by the upcoming first annual AI film festival powered by Runway! About the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Duration:00:56:49

Episode 106: Advancing AI Adoption with Dânia Meira

1/4/2023
Show Notes the University of Campinasthe University of FluminenseMYTOYS GROUPa data ambassadorAI Guild#datalift#datacareerDânia's Contact Info LinkedInTwitterWebsiteGitHubMediumAI Guild's Resources WebsiteLinkedInYouTubeJoin As A Member#datalift#datacareerMentioned Content People Andrew Ngdeeplearning.aiAlessandra SalaJoy BuolamwiniBook Weapons of Math DestructionAbout the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Duration:01:08:55

Episode 105: Building The Next-Generation Spreadsheet, Being A Curious Analyst, and Engineering Entrepreneurship with Bobby Pinero

12/19/2022
Show Notes St. Albans SchoolManagement Science and EngineeringIBMInflectionIntercomScaling Analytics at Intercoma few metricsthe data points that startups should measureEqualsBen McRedmondthe Equals productBobby's Contact Info LinkedInTwitterEquals Resources WebsiteTwitterLinkedInSpreadsheet TemplatesInsights In Action interview seriesIntroducing Pivot Tables for EqualsEquals raises $16M Series A from a16z to replace ExcelEquals is hiring across Engineering, Design, Growth, and an Executive Assistant. Reach out to Bobby if you are interested! Mentioned Content Articles + Talk 23 SaaS Metrics for Fundraising + OptimizationScaling Analytics at IntercomData Points: What Should Your Startup Measure?Every analyst is a finance analystThe only question that matters when interviewing analystsWhen to make your first finance hireThe hardest leap to make as a scaling finance leaderFinance and describing product-market fitThe curious analystThe less lonely finance leaderWhy every scaling finance team is understaffedRevenue is the best North Star metricPeople Karen ChurchNoah GoodmanPeter FishmanAbout the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Duration:01:04:46

Episode 104: Streamlining Machine Learning In Production with Ran Romano

12/8/2022
Show Notes Reichman UniversityVMware'sWix.com2020 talk discussing Wix's ML PlatformQwakBuild SystemServingData LakeFeature StoreAutomationsRan's Contact Info LinkedInQwak's Resources WebsiteTwitterLinkedInWhy QwakBlogMentioned Content Talks Overview of Wix's Machine Learning PlatformFeature Stores - Unified Data Pipelines for MLPeople Andrew NgMatei ZahariaBarr MosesBook PrinciplesAbout the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Duration:00:58:59

Episode 103: Computational Economics, Statistical Arbitrage, and Adaptable Data Consolidation with Eric Daimler

11/28/2022
Show Notes Carnegie Mellon UniversitySilicon Valley CampusEntrepreneurial Management programHg Analyticsa Presidential Innovation FellowConexusCategory TheoryEric's Contact Info TwitterLinkedInConexus' Resources WebsiteResourcesMentioned Content People Kai-Fu LeeAndrew NgEric XingBook ReCulturing: Design Your Company Culture to Connect with Strategy and Purpose for Lasting SuccessAbout the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. Get in touch with feedback or guest suggestions by emailing khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to or browse the full guest list.

Duration:01:02:19

Episode 102: Early-Stage Investing, Modern Venture Capital, and Trends in Enterprise Infrastructure with Astasia Myers

11/23/2022
Show Notes the Graduate Business SchoolCondoleezza RiceSan Leon Energy: Hydraulic Fracturing in PolandUniversity of Cambridge's Judge Business SchoolBaird and Co.Cisco InvestmentsRedpoint VenturesSolo.ioLaunchDarklyHexPresethiring decisionspricing productsnavigating go-to-market strategyher Medium blog Memory Leakdata science notebooksdata orchestrationdata pipeliningML data managementtypical challengesincorporate Product-Led Growth into their go-to-market motioncommunity as a fueladvicestartingcommunity initiativesQuiet CapitalData-Centric MLAstasia's Contact Info LinkedInMediumTwitterQuiet Capital WebsiteLinkedInTwitterMentioned Resources Content John Gannon BlogPeople Satish DharmarajScott RaneyAmanda RobsonNotes My conversation with Astasia was recorded back in April 2022. Since then, many things have happened. I'd recommend: her Memory Leak newsletterQuiet Capital's new portfolio careers pageAstasia's appearance on the Data Stack ShowEdge DeltaDiagridOmniher real-time infrastructure landscape

Duration:01:17:17

Episode 101: Scaling Data Engineering, Building Data Teams, and Managed Data Stack with Tarush Aggarwal

11/7/2022
Show Notes Carnegie Mellon UniversitySalesforceWyngWeWorkMarquez5xa managed data stackdata engineersvendors that make up the modern data stacka lot of good videosTarush's Contact Info LinkedInTwitterMedium5x Resources WebsiteLinkedInTwitterYouTubeInstagram5x Explained in 2 MinutesManaged Data PlatformOn-Demand Data Engineering ServicesIntegrationsMentioned Content People George FraserTaylor BrownPrukalpa SankarFrank SlootmanBooks Stealing FireThe 5 AM ClubAbout the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. Get in touch with feedback or guest suggestions by emailing khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to or browse the full guest list.

Duration:00:55:27

Episode 100: Data-Centric Computer Vision, Productizing AI, and Scaling a Global Startup with Hyun Kim

10/28/2022
Show Notes Duke Universitybringing ML to diagnose Parkinson’s disease with brain MRI scansAmazon Robotics ChallengeSK Telecomsynthetic image generationSuperb AIthe Y Combinator Winter 2019 batchSuperb AI’s Labeling platformits inceptionCustom Auto-Labelthe newly released Superb DataOps platformthe quickly evolving AI Infrastructure ecosystemHyun’s Contact Info LinkedInTwitterSuperb AI Resources WebsiteLinkedInTwitterYouTubeGitHubDocsSuperb AI Suite Labeling PlatformSuperb AI DataOps PlatformThe Ground Truth NewsletterSuperb AI AcademyMentioned Content People Andrew NgAndrej KarpathyIan GoodfellowBook Zero To OneAbout the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. Get in touch with feedback or guest suggestions by emailing khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to or browse the full guest list.

Duration:01:09:29

Episode 99: Data Mobility, Enterprise GTM, and Tech Leadership with Gary Hagmueller

8/30/2022
Show Notes Arizona State UniversityUSC — Marshall School of BusinessVerizonNorthPoint CommunicationsVinfolioKnowNowZuoraCLARA AnalyticsRedpoint VenturesArcion Labsdata mobility platformfinding the right technology partnersGary’s Contact Info LinkedInTwitterCrunchbaseArcion’s Resources WebsiteLinkedInTwitterYouTubeDocsSlack“Dawn of the Data Mobility Era“Arcion lands $13M to help companies replicate data across platformsMentioned Content Content The Network Effects BibleBlog by Tomasz TunguzPeople Gurjeet SinghSatish DharmarajNotes My conversation with Gary was recorded back in March 2022. Since then, many things have happened at Arcion. I’d recommend checking out: Arcion CloudThis article about data mobilityThis article about change data captureThis big product launch on Oracle log reader availabilityThe article about the missing piece for the Modern Data StackArcion is launched with Databricks Partner Connectthe Oracle Cloud World 2022About the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. Get in touch with feedback or guest suggestions by emailing khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Duration:01:18:23

Episode 98: Building Developer Tools, Managing Platform Products, Fostering Diversity, and Enabling Real-Time Data Applications with DeVaris Brown

8/16/2022
Show Notes UIUCIntelCisco SystemsMicrosoftMarmaladeKlick PushZendeskthe Zendesk Developer PlatformVSCOSlyce.ioHerokuthe founding story of Meroxaconnections between data sources and destinations in real timeConduita few customer use cases of MeroxaMeroxa’s cultural valuesDeVaris’ Contact Info LinkedInTwitterWebsiteGitHubMeroxa’s Resources WebsiteLinkedInTwitterYouTubeCareersDocumentationConduitGitHubDiscordTwitterDocsMentioned Content Articles “Hello World, Meroxa StylePart 1Part 2“Conduit: Streaming Data Integration for Developers“Why Conduit? An Evolutionary Leap Forward for Real-Time Data Integration“Hello Meroxa 2.0Resources for minorities Kura LabsFree Code CampBooks Zero To OneThe Hard Thing About Hard ThingsPeople Tristan HandyArjun NarayanBenn StancilChad SandersonNotes My conversation with DeVaris was recorded back in April 2022. Since then, many things have happened at Meroxa. I’d recommend checking out: Meroxa 2.0TurbineThis interview on data-driven work cultureNew CDC Connectors built into ConduitMeroxa is a recipient of DoD funding to help the US Space Force monitor aircraft health in real-timeAbout the show Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe. Datacast is produced and edited by James Le. Get in touch with feedback or guest suggestions by emailing khanhle.1013@gmail.com. Subscribe by searching for Datacast wherever you get podcasts or click one of the links below: Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Duration:01:37:04