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.

Our Reference Architectures:

Our References

Contact us

Interested in how Databricks can transform your data workflows? Contact our team to learn more about its impact at Plainsight.

info@plainsight.pro

Contact our Databricks Expert

Bo Vande Sompele is here to help you navigate our technology offerings and identify how they can drive value for your business.