databricks

Databricks empowers organizations to unify data, analytics, and AI on a single platform. It simplifies collaboration across data science, data engineering, and business teams.

why we use databricks

Databricks helps us accelerate innovation by offering:

Unified Data Lakehouse Architecture: Combines the flexibility of data lakes with the performance of data warehouses.
Scalable Data Processing: Optimized for high-performance big data workloads with Apache Spark™.
End-to-End AI and Machine Learning: Enables seamless model development, training and deployment.
Collaboration Tools: Real-time sharing of notebooks and visualizations.

key features

Delta Lake
Delivers reliable data pipelines with ACID transactions, schema enforcement, and time travel for versioned data.

Collaborative Notebooks
Write and execute code in Python, SQL, Scala and R, all in one place, while visualizing results effortlessly.
Optimized Runtime
Pre-configured clusters for enhanced Apache Spark™ performance, ensuring faster execution of workloads.
MLflow
Track, deploy, and manage machine learning workflows at scale using the open-source MLflow framework.

How We Leverage Databricks

At Plainsight, we use Databricks to:

Process large-scale data pipelines efficiently.
Build and scale machine learning models to drive actionable insights.
Unify data engineering and data science workflows for faster collaboration.
Reduce time-to-value by delivering insights quickly through automated, scalable systems.