Events at UC Berkeley

💡 Seminars, meetups and workshops on #Connected #DataProducts, #CulturalAnalytics and #OpenScience.

events.berkeley.edu/BIDS

Data Mesh without product thinking is decentralized chaos. 📊

Ownership distributed. Accountability didn't.

The fix is simple: treat data contracts as API boundaries, not catalog entries.

That's the difference between a mesh and a marketplace. 🏗️

#DataMesh #DataProducts #EvilTwin #EvilMaid #Amazon

RE: https://me.dm/@bayo/116270059395367077

Data Mesh without product thinking is just decentralized chaos with better slide decks. 📊

Most teams distributed ownership. Nobody followed with accountability.

The teams winning? They treat data contracts as the API boundary, not a catalog entry […]

🚨 Don't miss the next webinar of our webinar series - Unlocking Data Value with DATAMITE!

Key details:
🧑‍💻"Transforming data into impactful products".
📅 11 March, 12:00 - 13:00 CET.
📍Online.
🗣️ By CERTH

Join the session here: meet.google.com/wuu-uohp-sws

#DataProducts #DataMonetisation #Webinar

The Advanced Lakehouse Data Product: Shortcuts In, Materialized Views Through, Versioned Schemas Out There’s a familiar tension in modern analytics: teams want data products that are easy to discover and safe to consume, but they also want to move fast—often faster than the governance model can tolerate. In Microsoft Fabric, that tension frequently shows up as a perception of workspace sprawl. A “single product per workspace” model is clean on paper—strong boundaries, tidy ownership, straightforward promotion—but it can quickly turn into dozens (or hundreds) of workspaces to curate, secure, and operate. This post proposes a different pattern—an advanced lakehouse approach that treats the lakehouse itself like a product factory:

A “workspace per data product” sounds clean—until you have 60 #DataProducts. This advanced lakehouse pattern uses shortcuts + #MaterializedLakeViews + versioned schemas to deliver left-shifted data products with #OneLakeSecurity, while keeping the perception of #MSFabric sprawl under control.

SAP Business Data Cloud Connect for Microsoft Fabric: The New Backbone of Your Data‑Product Strategy SAP and Microsoft have just taken away one of the biggest excuses for slow analytics and AI on SAP: “We can’t move that data safely or reliably enough.” At Microsoft Ignite 2025, they announced SAP Business Data Cloud (BDC) Connect for Microsoft Fabric—a new capability that lets you share SAP Business Data Cloud data products and Microsoft Fabric data sets bi‑directionally, with zero‑copy, and have those products show up natively in OneLake and back in BDC.

With #SAP #BusinessDataCloud Connect for #MSFabric, you can bring SAP #DataProducts into OneLake—and send Fabric insights back into SAP—bi‑directionally and zero‑copy. Add SAP Databricks, Azure Databricks, and Purview data products, and you have a practical, multi‑platform data‑product estate

Data as an Asset: Building Data Capital on the Balance Sheet. Sanjay K Mohindroo

Data isn’t exhaust—it’s capital. Will you put it on the balance sheet? #DataCapital #DataAssets #DataEconomy #DataProducts #DataMonetisation #DataGovernance #CIO #CFO #CDO #DigitalTransformation
medium.com/@sanjay.mohi...

Data as an Asset: Building Data Capital on the Balance Sheet. Sanjay K Mohindroo

Data isn’t exhaust—it’s capital. Will you put it on the balance sheet? #DataCapital #DataAssets #DataEconomy #DataProducts #DataMonetisation #DataGovernance #CIO #CFO #CDO #DigitalTransformation
medium.com/@sanjay.mohi...

Chief Data Officer vs. CIO: The Power Shift in the Data-Driven Era. Sanjay K Mohindroo

CIO vs. CDO—partners or rivals? The future of your enterprise may hinge on the answer. #CIO #CDO #ChiefDataOfficer #DataLeadership #DataCulture #DataProducts #DataStrategy #DigitalTransformation #AI #BigData #Cloud
medium.com/@sanjay.mohi...

Chief Data Officer vs. CIO: The Power Shift in the Data-Driven Era. Sanjay K Mohindroo

CIO vs. CDO—partners or rivals? The future of your enterprise may hinge on the answer. #CIO #CDO #ChiefDataOfficer #DataLeadership #DataCulture #DataProducts #DataStrategy #DigitalTransformation #AI #BigData #Cloud
medium.com/@sanjay.mohi...

From Data Lakes to Value Streams: Building Data Products That Matter. Sanjay K Mohindroo

Data is not storage—it’s a product. What are you building? #DataProducts #DataLakes #DataMonetisation #AI #Cloud #BigData #DigitalTransformation #CIO #CTO #Leadership #Innovation #DataStrategy #AIethics
medium.com/@sanjay.mohi...

From Data Lakes to Value Streams: Building Data Products That Matter. Sanjay K Mohindroo

Data is not storage—it’s a product. What are you building? #DataProducts #DataLakes #DataMonetisation #AI #Cloud #BigData #DigitalTransformation #CIO #CTO #Leadership #Innovation #DataStrategy #AIethics
medium.com/@sanjay.mohi...

Making Schema Change Boring: A Short History—and How Microsoft Fabric’s Medallion Lakehouse Bakes It In Schema changes have always been risky because a schema isn’t just columns—it’s the interface between data producers and data consumers. Historically, that interface was rigid, which made any change expensive. Modern lakehouse design solves the problem structurally: a Medallion architecture separates where variation is tolerated (Bronze) from where commitment is made (Silver) and relied upon (Gold). In Microsoft Fabric, those roles map cleanly to Lakehouse, Warehouse, and Power BI’s semantic layer, with governance and domain‑oriented (data‑product) design tying it all together.

Schema change isn’t a failure to control—it’s reality to choreograph. Use Fabric’s Medallion pattern to absorb change in Bronze, productize it in Silver, and deliver confidence in Gold. Governance and domains make it boring—and that’s the point. #SchemaEvolution #Lakehouse #DataProducts #DataGoverna

Build Products, Not Ponds If you agree that data should be judged by the decisions it improves, the way you build with data changes. You stop trying to pour every table from every system into one giant lake and assume value will appear later. Instead, you ship small, finished data products that help with one decision at a time. The first approach optimizes for storage.

If your #DataStrategy starts with “ingest everything,” you’re optimizing for storage, not #Decisions.
The real change happens when you build data products that deliver clear outcomes — one decision, one promise, one #MeasurableResult at a time.
Stop managing ponds. Start shipping #DataProducts.

An infographic in a shape of a rounded bottom pyramid, portraying the TRICUSO value chain with information going upwards from measurements, to quality control and data products, to mapping and modelling, then scientific assessments and policy advice as the last step at the top.

TRICUSO’s main objective is to innovate every level of the #Ocean #Carbon #Observation #ValueChain:

🔎 #Measurements
📊 #QualityControl and #DataProducts
🌍 #Mapping and #Modelling
🧐 #ScientificAssessments
📝 #PolicyAdvice

Learn more at tricuso.eu/overview/ 💡

@horizoneu.bsky.social #REA

Starburst lets SQL devs build AI features without learning Python or waiting on data science teams. # Starburst Brings AI Agents to SQL Developers—No Machine Learning PhD Required The data platform company [Starburst][1] is rolling out features that put AI capabilities directly into the hands of SQL...

coderlegion.com/6232/starbur... #AI #Starburst #SQLDevelopers #DataEngineering #AIAgents #MCP #DataProducts #EnterpriseAI

A New Paradigm For Data Teams: The Changing Role of the Data Visualization Engineer When teams build warehouses the old way—source → bronze → silver → gold → semantic—visualization and semantic specialists are invited in at the end. Their job looks reactive: wire up a few visuals, name some measures, make it load fast enough. They inherit whatever the pipeline produced, then try to make meaning out of it. The failure mode is predictable: pixel‑perfect charts sitting on semantic quicksand, with definitions that shift underfoot and performance that depends on structures no one designed for the questions at hand.

In a previous post, I talked about a revelation I had with regard to the way we could architect #DataProducts in a more efficient way in #MSFabric. The more I thought about this, the more I thought that this change would have (and is currently having) a profound effect on the way we structure our…

Modern Data Strategies for AI ROI — free, virtual event on Nov 12.

Get frameworks tied to outcomes, KPI templates, and architectures that power AI/BI/ML & self-service. Live Q&A.

👉 RSVP: bit.ly/4pVGYLu

#TDWIVirtualSummit #AI #BI #DataStrategy #DataProducts #Analytics

A New Paradigm For Data Teams: The real bottleneck isn’t data, it’s definition Most data teams still run a tidy assembly line: ingest sources into bronze, standardize into silver, curate into gold, and only then wire up a semantic model for BI. That sounds rigorous—but it puts the business contract (grain, conformed dimensions, measure logic, security scope, and SLOs) at the very end. By the time the organization finally argues about what “AUM” or a compliant “time‑weighted return” …

A conversation last week with @ErinSanders got me thinking about how some of the #DataEngineering challenges we face come from the process that we use to develop #DataProducts. #MSFabric allows us to literally #BeginWithTheEndInMind and develop from the goal we are trying to reach, rather than…

Data as an Asset: Building Data Capital on the Balance Sheet. Sanjay K Mohindroo

Data isn’t exhaust—it’s capital. Will you put it on the balance sheet? #DataCapital #DataAssets #DataEconomy #DataProducts #DataMonetisation #DataGovernance #CIO #CFO #CDO #DigitalTransformation
medium.com/@sanjay.mohi...

Data as an Asset: Building Data Capital on the Balance Sheet. Sanjay K Mohindroo

Data isn’t exhaust—it’s capital. Will you put it on the balance sheet? #DataCapital #DataAssets #DataEconomy #DataProducts #DataMonetisation #DataGovernance #CIO #CFO #CDO #DigitalTransformation
medium.com/@sanjay.mohi...

Chief Data Officer vs. CIO: The Power Shift in the Data-Driven Era. Sanjay K Mohindroo

CIO vs. CDO—partners or rivals? The future of your enterprise may hinge on the answer. #CIO #CDO #ChiefDataOfficer #DataLeadership #DataCulture #DataProducts #DataStrategy #DigitalTransformation #AI #BigData #Cloud
medium.com/@sanjay.mohi...

Chief Data Officer vs. CIO: The Power Shift in the Data-Driven Era. Sanjay K Mohindroo

CIO vs. CDO—partners or rivals? The future of your enterprise may hinge on the answer. #CIO #CDO #ChiefDataOfficer #DataLeadership #DataCulture #DataProducts #DataStrategy #DigitalTransformation #AI #BigData #Cloud
medium.com/@sanjay.mohi...

From Data Lakes to Value Streams: Building Data Products That Matter. Sanjay K Mohindroo

Data is not storage—it’s a product. What are you building? #DataProducts #DataLakes #DataMonetisation #AI #Cloud #BigData #DigitalTransformation #CIO #CTO #Leadership #Innovation #DataStrategy #AIethics
medium.com/@sanjay.mohi...

From Data Lakes to Value Streams: Building Data Products That Matter. Sanjay K Mohindroo

Data is not storage—it’s a product. What are you building? #DataProducts #DataLakes #DataMonetisation #AI #Cloud #BigData #DigitalTransformation #CIO #CTO #Leadership #Innovation #DataStrategy #AIethics
medium.com/@sanjay.mohi...

Everyone built data lakes.
Now we’re drowning in unusable data.
AI doesn’t need lakes.
It needs pipelines -focused, governed, built for decisions.

The real bottleneck?
Not compute. Not models.
It’s data usability.
Don’t pour more.
Build better.

#Dataproducts #AI #dataquality

Today’s insight:

The code is the mine. The data is the platinum.
The moment that flips? That’s your VIP—Value Inversion Point.
Plan for it. Monetize it. Protect it.

#SaaS #dataproducts #productstrategy

Modern Forecasting Mastery by Valery Manokhin on Maven Master forecasting with hands-on, real-world training. No fluff—just insights that drive ROI and advance your career.

Cohort 2 is already taking shape → maven.com/valeriy-ma...

#forecasting #data #timeseries #machinelearning #cohortbasedcourse #causalinference #dataproducts

Part 5: Strategic Advantages of a Table-Oriented Publish-Subscribe Architecture Enterprise data integration faces growing complexity and fragmentation, making traditional event-driven models inadequate for sharing complete reliable datasets

I just published Part 5 of my article series on #PubSubForTables and its impact on modern #DataIntegration, #DataArchitecture, and #DataProducts is out! We're in the home stretch now. Grab your 🤿 snorkel and mask and dive in with me.

www.linkedin.com/pulse/part-5...

On stage in Antwerp, Kiran Prakash (Thoughtworks) is delivering his talk "What we talk about when we talk about Data Products." #datameshlive #dataproducts