Databricks Implementation
Unified Analytics. Lakehouse Architecture
Databricks is the lakehouse platform that unifies data engineering, data science, and machine learning. Built on Apache Spark, it combines the best of data lakes and data warehouses
When Databricks Makes Sense
You have both analytics and ML/AI workloads
You're working with large-scale unstructured data (logs, JSON, images)
You need Python/Scala/R alongside SQL
You want a unified platform for data engineers and data scientists
You're building advanced ML pipelines and need MLflow
What We Implement
Initial Setup
Workspace configuration and governance,Cluster policies and cost controls
Lakehouse Architecture
Delta Lake table design,Bronze/Silver/Gold medallion architecture,Data quality with Delta Live Tables
Data Engineering
Spark job development and optimization,Structured Streaming pipelines,Workflow orchestration
Machine Learning
MLflow experiment tracking, Feature Store implementation, Model registry and deployment
SQL Analytics
Databricks SQL warehouse setup, Dashboard and visualization, BI tool connectivity (Looker, Power BI, Tableau)
Related Services
Solves These Challenges
