Hadoop-to-Databricks Migration QuickStart

Apache Hadoop Integrator


  • Accelerate high-value analytics initiatives and gain experience with Databricks.
  • Get up and running on Databricks in an accelerated timeline. 
  • Complete one (1) Hadoop workload migration and analyze with SQL analytics and BI tools.
  • Blueprint accelerators speed time to value and actionable insights.

QuickStart Overview


a data team to analytics on Databricks


Databricks & data services, non-prod env


1 Hadoop workload migration


with SQL Analytics and BI tools

Case Study

Major U.S. oil drilling company


  • Siloed data in disparate systems and Hadoop environment — not highly performant
  • Drill bit sensors collected data every second, but delivered to data scientists only once every 24 hours (not quick enough for BI to inform decisions)
  • Timing delays in data availability resulted in slow response times and drilling adjustments (inefficient)


  • Stream siloed data (rig, sensor, oil sample, financial, HR, marketing) into Azure Databricks Data Lake
  • Process, normalize, and organize data into tables
  • Remove need for third party legacy engineering tools to structure raw data
  • Data modeling via Azure SQL & Azure Data Factory
  • Share data to Power BI for real-time analytics, dashboards, and reports



Data migrated to Data Lake


Increase in rig state data processing

(from 24 to every 4 hours)


increase in speed of OFT data processing

(45 days of OFT data processed in 1 hour instead of 24 hours)

Real-time drilling data available in 1 second!

Quickstart timeline

Stage 1

Lakehouse 101

  • Data acquisition
  • Simple data transformations
  • Organizing data
  • Security
  • BI, reporting
  • Optimizing costs & management

Stage 2-3

Up & running

  • Implementation → Powered by Infra-as-Code
  • Security Config → Blueprint security rapid config
  • Lakehouse optimization → Blueprint Lakehouse Optimizer

Stage 4-8

Data pipelines

  • Identify data sources
  • Historical & current data
  • Data transformations
  • Data quality
  • Data set creation, scheduled
  • Tables in the Lakehouse, ready!

Stage 8-10

BI & analysis, optimize, & roadmap

  • Power BI or Tableau
  • DBSQL for ad hoc analysis
  • Dashboards & reports
  • Utilization management
  • Roadmap the future

Deployment journey

AWS or Azure readiness

QuickStart data sources

Scripted build

Sample data & notebooks

Workflows active

Databricks is LIVE!

Lakehouse Optimized


Build a net-new use case and validate
cost vs performance and usability of Databricks platform.

  • TCO and performance projection report
  • Established Databricks Lakehouse environment
  • Data ingestion pipeline
  • Platform utilization monitoring app
  • Working end-to-end use case/business process
    deployed to non-production environment
  • Results report and demonstration

Databricks Center of Excellence 

Your one-stop Databricks partner

Limited time offers.
Contact us to get started now.

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