shane murrayinTowards Data ScienceOrganizing Generative AI: 5 Lessons Learned From Data Science TeamsLLMs hold tremendous promise, but generating sustainable value will require more than a tiger teamAug 25, 20232Aug 25, 20232
shane murrayinTowards Data ScienceConscious Decoupling: How Far Is Too Far for Storage, Compute, and the Modern Data Stack?While there is no right answer, there is likely a sweet spot for most organizations’ data platforms. Read on to see where that might be.Jul 24, 2023Jul 24, 2023
shane murrayinTowards Data ScienceWhich Team Should Own Data Quality?Specialists or generalists? Engineer or analyst? We examine which team structures are the best suited for efficiently improving data…Jun 9, 20234Jun 9, 20234
shane murrayExperimentation: How Data Leaders Can Generate Crystal Clear ROIData teams can drive quantifiable ROI by establishing a strong experimentation program. Here are the lessons we’ve learned at Airbnb, the…Apr 13, 2023Apr 13, 2023
shane murrayinTowards Data ScienceThe Chaos Data Engineering ManifestoAnother lesson we can learn from software engineers: break stuff to make it more reliable.Feb 24, 20234Feb 24, 20234
shane murrayinTowards Data ScienceMeaningful Experimentation: 5 Impactful Data Projects To Help Build Better ProductsPart two in a practical data leader series on how to best work with each department and all their wonderful eccentricitiesJan 6, 2023Jan 6, 2023
shane murrayinTowards Data ScienceHow Data and Finance Teams Can Be Friends (And Stop Being Frenemies)Part one in a practical data leader seriesNov 29, 20225Nov 29, 20225
shane murrayinTowards Data ScienceWhere Data Silos Live In Your OrganizationYou’ve heard of shadow IT, but what about shadow data?Nov 7, 2022Nov 7, 2022
shane murrayOrganizing Talent: Return of the Data Center of ExcellenceShane MurrayOct 6, 2022Oct 6, 2022