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Unified Data Solution: Microsoft and Databricks Collaborate on Lakehouse Platform

Organizations across industries generate huge volumes of data every day, both structured and unstructured. To make sense of this data and derive insights that can help drive business growth, organizations need the right tools and platforms. Traditional data architectures like data warehouses and data lakes are no longer sufficient to meet the demands of today's data-driven world. This is where data lakehouses come in.


A data lakehouse is a new data architecture that combines the best of data warehouses and data lakes. It provides a unified platform to store, manage and analyze both structured and unstructured data. Microsoft and Databricks have partnered to provide a well-governed data lakehouse solution on Azure, which helps organizations leverage the power of data to drive insights and innovation.


A novel system design has enabled the creation of data lakehouses, which combine the data structures and management features of data warehouses with the cost-effective storage of data lakes. This integration allows data teams to work more efficiently by accessing data from a single system instead of multiple ones. Data lakehouses also guarantee that teams have access to the latest and most comprehensive data for their data science, machine learning, and business analytics initiatives.


History from Data Warehouse to Data Lakehouse

source: Databricks


Microsoft Azure Synapse Analytics is a cloud-based analytics service that offers big data and data warehousing capabilities in a single platform. Databricks provides a unified analytics platform for data teams to collaborate on data engineering, machine learning, and analytics workflows at scale. By integrating Databricks' Lakehouse Platform with Azure Synapse Analytics, the solution provides a secure, scalable and well-governed data lakehouse that enables organizations to handle the complete data lifecycle, from ingestion to archival.


The joint solution has several benefits for organizations. Firstly, it simplifies and automates data ingestion, preparation, and analytics workflows, which can help accelerate time to value. Secondly, it provides a unified data solution that allows data teams to collaborate more effectively, leading to faster and more accurate insights. Thirdly, it ensures the security, privacy, and compliance of data, which is crucial for organizations that deal with sensitive data.


One of the key features of the joint solution is the integration of Azure Synapse Analytics and Databricks' Delta Lake. Delta Lake is an open-source storage layer that provides reliability, performance, and scalability to data lakes. Delta Lake allows organizations to manage the complete lifecycle of their data, from ingestion to archival, in a single platform. Delta Lake also provides several features that are crucial for data lakehouses, such as ACID transactions, schema enforcement, and time travel.



source: azure architecture


The integration of Azure Synapse Analytics and Delta Lake enables organizations to ingest and prepare data using Azure Synapse Analytics, and then analyze it using Databricks. This makes it easier for organizations to collaborate on data engineering and analytics workflows. It also ensures the security and compliance of data, as organizations can enforce policies and regulations at the point of ingestion. Finally, it enables organizations to achieve faster insights, as data can be analyzed in real-time using Databricks' powerful analytics engine.


Another key feature of the joint solution is the integration of Azure Synapse Analytics and Databricks' MLflow. MLflow is an open-source platform for the complete machine learning lifecycle, from data preparation to deployment. It allows organizations to track experiments, reproduce results, and deploy models at scale. MLflow also provides several features that are crucial for machine learning in data lakehouses, such as model versioning, model registry, and model serving.


In conclusion, the partnership between Microsoft and Databricks provides a well-governed data lakehouse solution that enables organizations to leverage the power of data to drive insights and innovation. The joint solution offers several benefits, including simplification and automation of data workflows, improved collaboration among data teams, and ensuring the security and compliance of data.


By: Ravindra Mettupalli


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