How Data Mastery can help you
Led by our Director of Engineering and Data Architect, Rory McManus, Data Mastery are experienced and seasoned Databricks specialists. Working as a Databricks trusted partner, Data Mastery will bring about the efficiency, transformation, and success you and your customers want and need, now and in the future.
At Data Mastery we will accelerate the implementation of your new Data Platform through our IP based delivery framework with Azure Data Services. This implementation framework will provide a framework for a future proof platform in addition to delivering your company a data platform for DevOps, Security and Cloud Governance.
Our world class data engineers will position Databricks as your core AI and Data service. We will provide you with an interactive workspace that enables collaboration between data engineers, data scientists, and machine learning specialists transforming the way you do business for the better.
WHY CHOOSE DATAMASTERY
Easily ingest and transform batch and streaming data on the Databricks Lakehouse Platform. Orchestrate reliable production workflows while Databricks automatically manages your infrastructure at scale. Increase the productivity of your teams with built-in data quality testing and support for software development best practices.
Built on an open lakehouse architecture, Databricks Machine Learning empowers ML teams to prepare and process data, streamlines cross-team collaboration and standardizes the full ML lifecycle from experimentation to production.
Streamline the Databricks Data Science Platform workflow from data preparation to modelling to sharing insights with a collaborative, unified data science environment, built on an open lakehouse foundation. Get quick access to clean and reliable data, preconfigured clusters and multi-language support for maximum flexibility for data science teams.
What is Databricks?
Azure Databricks is a data analytics platform optimized for the Microsoft Azure cloud services platform. Azure Databricks Analytics offers three environments for developing data intensive applications. Databricks SQL, Databricks Data Science & Engineering, and Databricks Machine Learning.
Databricks SQL: provides an easy-to-use platform for analysts who want to run SQL queries on their data lake, create multiple visualization types to explore query results from different perspectives, and build and share dashboards.
Databricks Data Science & Engineering: Provides an interactive workspace that enables collaboration between data engineers, data scientists, and machine learning engineers. For a big data pipeline, the data (raw or structured) is ingested into Azure through Azure Data Factory in batches, or streamed near real-time using Apache Kafka, Event Hub, or IoT Hub.
Databricks Machine Learning: Is an integrated end-to-end machine learning environment incorporating managed services for experiment tracking, model training, feature development and management, and feature and model serving.