Data & AI, explained by the people building it.
Weekly perspectives from data engineers, architects, and leaders on data platforms, data products, AI enablement, governance, and everything in between.
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What readers are saying
Great idea with Modern Data 101. Curious to watch it grow.
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Explore by category
Lean AI
Where governed, discoverable data products get published, catalogued, and consumed across an organisation, turning data teams into internal product teams with real customers.
Interoperability
How data and AI systems talk to each other across vendors, formats, and platforms, open standards and integration patterns that keep enterprises vendor-neutral instead of locked in.
Edge AI
Running inference and data processing closer to where data is actually generated: devices, sensors, and edge nodes, instead of shipping everything to a central cloud first.
Digital Twin
Virtual replicas of physical systems that stay in sync with real-world data, used for simulation, monitoring, and predictive maintenance across manufacturing, energy, and logistics.
Ontology
The vocabularies and semantic structures that let people and machines agree on what data actually means; the quiet infrastructure behind every reliable AI system.
Data Product Marketplace
Where governed, discoverable data products get published, catalogued, and consumed across an organisation, turning data teams into internal product teams with real customers.
Data Products
Treating data as a packaged, owned, and documented product rather than a raw export, the foundation most modern data strategies are now being rebuilt around.
RCA & Observability
Finding out why a number is wrong before it reaches a dashboard: lineage, monitoring, and root-cause workflows that keep data, and the AI built on top of it, trustworthy.
Real Time Data
Moving from daily batch jobs to streaming pipelines, because AI copilots, fraud detection, and live dashboards can't wait for tomorrow's refresh.
Data Platforms for AI
The lakehouses, warehouses, and platform layers built to serve both human analysts and AI systems from the same governed foundation, instead of two parallel stacks.
Digital Transformation
The org-wide shift from legacy, siloed systems to connected, data-driven operating models, and the change management that actually makes it stick.
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Where does your org stand on data product maturity?
A 9-dimension self-assessment used by 100+ data teams to benchmark strategy, ownership, and platform readiness.
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Digital Twin
Discover trusted insights, connect with data peers, share ideas, get feedback, and grow your career in the evolving data industry evolving data industry.
Ontology
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Data Products
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RCA & Observability
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State of Data Products 2026 Q2
The quarterly read for data and AI leaders on the trends, gaps, and decisions shaping enterprise AI.
Real Time Data
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Data Platforms for AI
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Guides and reports to level up your data team
The Data Product Playbook
A 6-week, step-by-step guide to activating your first data product 4,000+ downloads and counting.
The Modern Data Report 2026
What sets high-performing data teams apart benchmarked across hundreds of practitioners and leaders.
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From the community
"...parts there had to be rebuilt because the entire legacy system was with the business for like 5-6 years at that point and was built like a Jenga tower in an advanced stadium."
"...but building it in such a way that is financially viable and beneficial for the business."
"...this allows you to create a single single source of truth and then be able to use that one metric calculation in a bunch of different tools."
Frequently asked questions
What topics does the MD101 blog cover?
Data products, AI enablement, data platforms, governance, observability, and the operating models enterprises use to turn raw data into trusted, usable systems, written by practitioners, for practitioners.
How often is new content published?
New articles publish weekly, alongside community contributions from Expert's Desk writers and guest practitioners across the data and AI space.
Can I contribute an article or become a community expert?
Yes. MD101 is a community-first platform: practitioners, architects, and leaders are welcome to pitch articles or join the Expert's Directory to share their perspective with a global audience.
How is Modern Data 101 related to The Modern Data Company?
Modern Data 101 is the community arm built and facilitated by The Modern Data Company, the team behind DataOS, a Data Operating System. The blog shares ideas; the company builds the platforms that put those ideas into production.
Read the ideas here. Build them with The Modern Data Company.
Modern Data 101 is where the data community thinks out loud. When you're ready to move from articles to architecture, data products, governed AI pipelines, or a full Data Operating System; the team behind this community can help you build it.
