Fabric Eventhouse and KQL: Real-Time Analytics That Holds Up
A security operations team may ingest millions of events, search for a suspicious pattern from the past fifteen minutes, and then examine…
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Data & Analytics
Build knowledge of data engineering, Microsoft Fabric, Databricks, BI, analytics and databases.
Modern data platforms succeed when information remains trustworthy from ingestion through transformation, modeling and consumption. Partitioning, governance, lineage, semantic models and operational monitoring shape both cost and reliability. Product features matter, but decisions about consistency and ownership often matter more.
Microsoft Power BI Data Analyst (PL-300) focuses on analytical modeling and reporting. Microsoft Fabric Data Engineer (DP-700) addresses data engineering workflows, while Databricks Certified Data Engineer Associate emphasizes the design and operation of data solutions on Databricks. These represent complementary perspectives rather than an automatic progression sequence.
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Carefully selected articles on the technologies, roles and concepts that shape this subject.
Fabric Lakehouse or Warehouse? Make the Tradeoff Explicit
For DP-600 candidates, knowing where analytical data is served is as important as modeling it correctly. Microsoft Fabric offers both Lakehouse and…
Read articleFeature Store Design: Keep Training and Serving Consistent
A machine-learning model can pass offline validation and still behave badly in production because the features used during training do not mean…
Read articleKQL Query Optimization: Make the Engine Do Less Work
An analyst writes a KQL query that returns the correct result in development but takes minutes against a month’s production telemetry. Adding…
Read articleDatabricks Liquid Clustering: A Practical Delta Lake Design
Teams maintaining large Delta tables often inherit a complicated rulebook: pick static partitions, accept the imbalance when data grows, and schedule ZORDER…
Read articleAI-Assisted SQL Workflows Without Losing Query Control
A natural-language assistant can convert a question such as ‘Which customer segments had the largest quarter-on-quarter revenue decline?’ into a SQL query.…
Read articleDatabricks Generative AI Engineer Associate: Serving Models and Proving Quality
A model can score well in a notebook and disappoint the first hundred customers who use it. Interactive requests arrive at uneven…
Read articleDatabricks Generative AI Engineer Associate: RAG That Answers From Evidence
A support assistant that confidently quotes last year’s warranty policy is worse than one that admits it cannot find the answer. The…
Read articleDatabricks Generative AI Engineer Associate: Vector Search Beyond Similarity
An enterprise search team builds an embedding index of troubleshooting notes and celebrates strong similarity scores. Then its assistant recommends a network-device…
Read articleDatabricks Generative AI Engineer Associate: LLMOps and Governance in Practice
A healthcare analytics team upgrades its generative assistant after promising an accuracy improvement. The rollout succeeds technically, but weeks later nobody can…
Read articleDatabricks Data Engineer Professional: Operating Reliable Pipelines
The hardest part of a data pipeline is often not the transformation. It is what happens at 03:00 when one upstream system…
Read articleDatabricks Data Engineer Professional: Streaming That Stays Correct
A streaming pipeline can look healthy while quietly corrupting a business metric. The dashboard refreshes every minute, the compute stays green, and…
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