March 13, 2026 at 08:18 PM | Est. read time: 11 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Adding dbt (data build tool) to an existing data warehouse can feel like renovating a house while living in it: you want better structure and reliability, but you can’t break […]
Implementing dbt in an Existing Data Warehouse: A Practical, Low-Risk Playbook Read More »
March 11, 2026 at 06:53 PM | Est. read time: 11 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Microsoft Fabric is quickly becoming the “single pane of glass” for analytics teams who want data integration, lakehouse, warehouse, real-time analytics, and BI in one place. If your organization has
March 11, 2026 at 05:59 PM | Est. read time: 12 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Migrating from Amazon Redshift to Snowflake is a common move for data teams looking for more elasticity, simpler operations, and strong cross-cloud flexibility. But while both platforms are columnar, MPP-oriented
March 04, 2026 at 01:29 PM | Est. read time: 10 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Databricks SQL can feel “fast” out of the box-but when workloads scale, the difference between acceptable and snappy often comes down to how efficiently the engine executes each stage of
Databricks Photon Engine: How It Actually Improves Query Speed (and When You’ll Feel It) Read More »
March 04, 2026 at 01:40 PM | Est. read time: 11 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. High-growth companies don’t “just need a data warehouse.” They need a modern data platform that can keep up with rapid product changes, exploding data volumes, new compliance demands, and a
March 04, 2026 at 01:25 PM | Est. read time: 12 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. ClickHouse is built for speed, but “fast by default” doesn’t always mean “fast at scale.” Once datasets reach billions of rows and queries become more concurrent, performance depends heavily on
March 04, 2026 at 01:42 PM | Est. read time: 11 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. AI has moved beyond “nice-to-have” experimentation and into the core of how data platforms are built, operated, and improved. What’s changing fastest isn’t just the analytics layer-it’s the day-to-day work
How AI Is Reshaping Data Engineering Workflows (and What It Means for Modern Data Teams) Read More »
March 04, 2026 at 03:41 PM | Est. read time: 12 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Choosing a cloud data warehouse isn’t just a feature comparison-it’s a decision that affects cost, performance, governance, and how quickly teams can deliver analytics and AI-ready data products. Two of
Amazon Redshift vs. Snowflake: Which Is Better for Your Data Warehouse Use Case? Read More »
March 04, 2026 at 04:14 PM | Est. read time: 12 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. “Lakehouse” has become one of the most practical ideas in data engineering: keep the flexibility and cost profile of a data lake, but add the governance, performance, and reliability people
March 03, 2026 at 02:08 PM | Est. read time: 12 min By Laura Chicovis IR by training, curious by nature. World and technology enthusiast. Modern software is increasingly data-centric-meaning the data is not just an output of the system, but the system’s primary product. Whether the goal is analytics, AI/ML, personalization, fraud detection, or