Rapidly implement an Azure Databricks Data Lakehouse with Fractal's Enterprise Data Lakehouse Migration Accelerator
According to research sponsored by Databricks, 73% of organizations are currently linking their data warehouses to data lakes to enable the use of all their data in BI and machine learning analytics. This approach works for most of these organizations; however, it comes with challenges. For example, leveraging both a Data Lake and Data Warehouse creates the need for a complicated and costly architecture. Such a complex architecture also leads to other underlying challenges, like maintaining the database connections and connections to the BI and data science solutions and services using the data.
A Data Lakehouse built on Azure Databricks helps address these challenges by combining the cost-efficient data storage of a Data Lake with the data management and ACID-compliant transaction capabilities of a Data Warehouse. This allows organizations to leverage all of their data in BI visualizations and machine learning analytics from a single source of truth with a simplified architecture that helps reduce costs and the risk of errors.
At the end of the 12-week period, the client should expect to receive a fully functional Data Lakehouse operating on Azure Databricks.
We have a GitHub repository for this solution where you can go through step by step to deploy the resources.
Click here to access the GitHub repository.