MSQ Analytics World — Power BI & BI Modernization
Lakehouse Engineering Practice

Databricks Consulting &
Lakehouse Architecture

Design and implement scalable data engineering and lakehouse solutions powered by Databricks. We engineer robust Delta Lake pipelines, automate PySpark workloads, enforce Unity Catalog governance, and deliver seamless Power BI connectivity over high-performance SQL Warehouses.

View Lakehouse Architectures
Lakehouse Capabilities
  • Delta Lake optimization with Z-Ordering, Liquid Clustering, and data compaction
  • Scalable PySpark ETL/ELT pipelines automated via Databricks Workflows
  • Unity Catalog unified governance, data lineage, and fine-grained access control
  • High-performance Power BI integration via Serverless SQL Warehouses & Photon
Engine Photon / PySpark
Storage Delta Lake
Governance Unity Catalog
Capabilities

Databricks Lakehouse Engineering Capabilities

From big data ingestion to low-latency enterprise BI reporting, we build robust data platforms on Databricks.

Delta Lake Architecture

Design multi-hop Medallion data architectures. Implement Delta Lake transaction logs, ACID compliance, schema enforcement, and automated compaction.

  • Z-Order clustering & partition pruning
  • Automated file optimization (OPTIMIZE / VACUUM)
  • Time-travel and rollback capabilities

PySpark & Spark SQL Pipelines

Develop high-throughput data processing pipelines handling terabyte-scale data with optimal cluster sizing, dynamic partition pruning, and minimal shuffle overhead.

  • Structured Streaming for real-time telemetry
  • Delta Live Tables (DLT) declarative pipelines
  • Auto Loader cloud file ingestion

Power BI + Databricks SQL Integration

Connect Power BI to Databricks SQL Warehouses with sub-second response times. Design aggregated composite models combining high-speed Import and live DirectQuery.

  • Databricks Serverless SQL Warehouse tuning
  • Dual-mode Composite Semantic Models
  • DirectQuery query reduction techniques

Unity Catalog Governance

Implement fine-grained access control across data assets. Configure column-level masking, row-level filters, automated audit logging, and data lineage across files, tables, and models.

  • Centralized access policies across clouds
  • Automated runtime data lineage tracking
  • Dynamic data masking for PII compliance

Workflows & Orchestration

Schedule and monitor complex multi-task DAGs using Databricks Workflows. Implement automatic retries, alerting, and SLA management across end-to-end data pipelines.

  • Multi-task job dependencies & DAGs
  • Automated failure alerting via Webhooks
  • Git-integrated CI/CD deployment

Cluster Optimization & FinOps

Control cloud infrastructure costs with automated cluster termination, Spot/Preemptible instance bidding, Photon engine enablement, and DBU consumption monitoring.

  • DBU utilization tracking & cost governance
  • Serverless SQL warehouse auto-scaling
  • Single-node vs multi-node cluster tuning
Engineering Roadmap

Databricks Lakehouse Delivery Methodology

A structured consulting engagement model designed to deliver production-grade lakehouse engineering.

01

Assessment & Lakehouse Design

Evaluate existing data pipelines, storage formats, and concurrency demands. We design the Unity Catalog metastore, workspace structure, and Delta Lake layout.

Lakehouse Architecture Blueprint
02

Medallion Ingestion & PySpark

Develop robust Bronze, Silver, and Gold pipelines. Optimize Delta tables with liquid clustering, schema evolution, and automated data quality checks.

Automated Medallion Pipelines
03

Power BI & SQL Warehouse Tuning

Configure Databricks SQL Warehouses with Photon. Build composite Power BI semantic models ensuring sub-second response across billions of rows.

Validated Analytics Layer
04

Governance & FinOps Setup

Enforce Unity Catalog access controls, automated Workflows alerting, CI/CD with Git, and DBU cost monitoring dashboards for long-term sustainability.

Governed Production Handover
Cross-Reference

Related Demonstrations & Case Studies

Explore interactive big-data telemetry and lakehouse modernization implementations.

Interactive Demo

Supply Chain Telemetry & Lakehouse Demo

Interactive demonstration of high-throughput fleet telemetry, IoT event ingestion, and real-time Power BI DirectQuery filtering.

View Interactive Demo Related Service

Microsoft Fabric Consulting

Explore OneLake delta integration, Fabric shortcuts connecting to Databricks, and Direct Lake semantic models.

Explore Fabric Consulting Case Study

Enterprise Lakehouse Modernization Study

How a logistics enterprise unified fragmented SQL pipelines into a scalable Databricks Delta Lake and Power BI reporting framework.

Read Case Study
FAQ

Databricks Consulting Questions

Answers to common questions regarding Databricks Lakehouse performance, SQL Warehouses, and Power BI connectivity.

We optimize the connection layer using Databricks Serverless SQL Warehouses, configuring Z-Ordering and liquid clustering on Delta tables, optimizing Photon engine execution, and designing dual-storage composite models in Power BI to achieve sub-second visual rendering.
The Medallion pattern structures data progression across three tiers: Bronze (raw, append-only ingested data), Silver (cleansed, filtered, validated, and conformed data), and Gold (business-level aggregate Star Schemas ready for reporting and advanced analytics).
We implement Databricks Unity Catalog for centralized access control, row-and-column level masking, and data lineage, aligning Unity Catalog permissions with Microsoft Entra ID and Power BI workspace security.
Lakehouse Engineering

Ready to Architect Your Databricks Lakehouse?

Discuss your Delta Lake architecture, PySpark pipelines, Unity Catalog rollout, or Power BI integration with an experienced enterprise Databricks consultant.