Modern Data Architecture: From Data Warehouse to Data Cloud
The Evolution of Data Architecture
Read articlePractical perspectives on AI, data strategy, and enterprise transformation from the Extrodata team.
Data mesh, lakehouse patterns, and enterprise-scale data platform design.
2 articlesSemantic layers, dashboard design, and modern BI migration strategies.
1 articlePipeline architecture, streaming patterns, and ELT best practices.
1 articleGovernance frameworks, compliance, and data quality programmes.
1 articleSnowflake, Databricks, Azure — platform selection and migration paths.
1 articleOur mission, values, and perspective on the AI consulting landscape.
1 article
The Evolution of Data Architecture
Read article
Why Data Governance Matters More Than Ever
Read article
Thousands of enterprises are currently running business-critical reporting on legacy SQL Server Analysis Services (SSAS) cubes. Whether multidimensional or tabular, these on-premises (or lift-and-shift cloud) cubes were brilliant for their...
Read article
When enterprise stakeholders ask for “real-time data,” they rarely mean sub-second latency. Usually, what they actually need is data that is fresh enough to make an operational decision—which often means...
Read article
The concept of a Data Mesh is heavily marketed, but highly misunderstood. For the past few years, enterprise data teams have been sold on the promise of decentralized, domain-oriented data...
Read article
Understanding the architecture that unifies data warehousing, lakes, and analytics into a single platform.
Read article
We're launching Extrodata with a clear mission: deliver senior-only AI and Data consulting that produces measurable outcomes, not slide decks.
Read articleWe publish new insights monthly. Follow us on LinkedIn for daily thinking on AI and data.
Follow on LinkedIn