Published in Towards Data Science·May 4What Is Well-Modeled Data for Analysis?Modeling data is not enough— you need to do it well — This article will be constrained to modeling read-access data for the purposes of analysis — i.e. the O part of I/O. I’m also not going to discuss data quality or pre-processing—but I trust you won’t forget about those things. Why should you care about data modeling? It’s about getting the most value from your data — quickly…Data Mesh6 min read
Published in Data Arena·Dec 16, 2021Lessons learned after deploying over 200 domain-driven data productsThere are two hot buzzwords competing for the data business 2021 Concept of the Year: Data Harmonization and Data Product. If you’re in my field — and presumably you are — you’ve started hearing and using these terms on a daily basis. I’m now even seeing job titles on LinkedIn…Data Mesh5 min read
Published in Towards Data Science·Jun 13, 2021Cleaner Code with Hungarian NotationTranscend the constraints of English parlance for better organization and faster interpretation of your work. Preface Do you remember when you learned how to format calendar dates for alphanumeric sorting? You either had dates in the month-first US format, e.g. 09–11–1991, or in the day-first European format, e.g. 11–09–1991, and you…Data Science5 min read
Published in Towards Data Science·Jun 9, 2021No-code, Low-code, and Pro-codeWhat do we mean when we use these trendy terms? Why do they matter? And aren’t these just new names for things that already existed? — Let’s begin with why these terms matter I’m presuming you’ll agree: Developers should be able to build novel, useful, scalable, secure software with only a minimal amount of clean, maintainable code. Minimizing the complexity and scope of code enables faster deployment of software applications which are easier to maintain and improve.Software4 min read
Published in Tag.bio·Mar 25, 2021Low-code Data Mesh Startup Tag.bio Leaps Forward with Sanjay PadhiI’m pleased to announce that Sanjay Padhi, PhD — formerly Head of AWS Research and leader in scientific computing at CERN — has joined Tag.bio as Chief Technologist and Executive Vice President. Dr. Padhi brings to Tag.bio a wealth of experience in cloud computing architecture and infrastructure for data research…Data Mesh2 min read
Published in Towards Data Science·Feb 14, 2021The Many Marvelous Meanings of “Data Harmonization”My industry’s favorite new buzzword—harmonized !— can describe many diverse, aspirational attributes of data systems. What does this new wonder-term mean, and to whom? — Across the span which ranges from data engineering, data applications, data science, and data analytics, to the industry verticals in which my company is focusing — Healthcare and Life Sciences — there are bazillions of acronyms, jargon terms, and buzzwords.Data9 min read
Dec 16, 2020What I learned while losing my mind when my laptop broke downYou know how sometimes you get sick after an intense period of Adulting, and someone inevitably says “it’s just your body telling you to slow down"? After 7 years of startup hustle, on Saturday my 2-year old laptop told me to slow down. It happened out of nowhere — my…Startup4 min read
Published in Towards Data Science·Nov 22, 2020Data Mesh 2.0The era of the monolithic data warehouse/data lake is coming to an end — long live the decentralized data mesh! Oh, do not despair! All those person-years spent cleaning, transferring, and loading data into your centralized systems hasn’t been in vain. With data mesh, you don’t have to start again…Data Mesh5 min read
Oct 9, 2020The Most Precious ResourceData Science — Answering questions with data — Is presumed to be an art, Or at least a high-tech craft, Producing exponential value and driving innovation. Organizations know Answering questions with data Needs to be faster, Automated. They design a plan — A centralized data lake with dashboards! But it takes too long to build. It…Data Science1 min read
Published in Towards Data Science·Jun 25, 2020Towards a World Wide Web of DataUsing the most successful, scalable pattern in software history to solve the worst problems in Data Science and Analytics. — Data, data, everywhere… …brimming with immense potential value for discovery in science, business and society. Unfortunately, the actual utility of most collected data is greatly diminished for value discovery/extraction purposes — like drinking salty seawater, the cost/benefit is a net loss. Why is this?Data Science9 min read
