Databricks offers a robust and user-friendly platform designed for scalability, seamless integration, collaboration, and access to a comprehensive ecosystem of libraries and tools. It’s perfect for big data processing and machine learning projects. Through our partnership, you can fully leverage Databricks for data engineering, data warehousing, AI & ML, data science, and data governance on the Lakehouse Platform, maximizing its potential and value for your projects.
Store and manage all your data in a single platform following some specific schema that combines the strengths of data lakes and data warehouses.
Combine the power of Apache Spark with Delta Lake and custom tools to provide an unrivaled ETL (extract, transform, load) experience that automatically scales and deploys production infrastructure.
Increase your application functionality with Azure Databrick ML with a range of tools like MLflow and Databricks Runtime for Machine Learning to efficiently train, integrate LLM and OpenAI models to their Databricks workflows.
Perform queries against data in the lakehouse, and get visualizations over user friendly interface with cost effective compute resources.
Leverage the power of a Azure Databricks tools like Databricks Workflows and Databricks Git folders for scheduling, versioning, automating, deploying code and production resources to simplify your overhead for monitoring, orchestration, and operations.
Get near real-time data ingestion, processing on streaming data with the help of Databricks’s Apache Spark Structured Streaming and Delta Live Tables.
Ease your data engineering, data science, and machine learning tasks with Databricks Unified Analytics platform that seamlessly integrates with various AWS services.
Optimize resource utilization with automatic scaling of the compute cluster based on current workload requirement.
Leverage native AWS services like S3 for storage, IAM for authentication, and CloudTrail for auditing, ensuring a smooth integration within your existing AWS infrastructure.
We help you to select your suitable cloud provider like AWS or Azure that is best aligned with your infrastructure.
We configure the region, cluster, and security settings for your workspace.
We take into account various types of data sources you own like data warehouses, databases, data lakes, or cloud storage platforms and establish secure connection between them and Databricks platform with appropriate APIs.
We configure, launch, monitor, and terminate clusters using Databricks tools optimizing your resource allocation and cost efficiency.
We build pipelines to ingest data with bulk loading, streaming data pipelines, and real-time data processing. Ingested data is cleaned, transformed, and prepared for data analysis.
We build data processing scripts, machine learning models, and analytics pipelines writing codes on Databricks notebook. We automate data processing tasks to run at specific intervals or on triggers.
We explore Databricks' compatibility with your existing business intelligence (BI) tools and data management platforms to build a more comprehensive analytics ecosystem.
We regularly monitor your Databricks environment, including cluster performance, data quality, and job execution logs for continuous improvement and optimization of your data processing pipelines.
We seamlessly integrate with a variety of ecosystem partners and platforms to enable greater flexibility and speed to market.
We believe in partnering with organizations to help them discover the power of technology by unlocking their true digital potential.
