Hi Jem,
Good day!!
Databricks is being leveraged in various ways across different organizations, primarily focusing on Business Intelligence (BI) use cases, data Engineering, and SQl, Machine learning etc.
1. **Business Intelligence (BI) and Analytics**:
- Databricks is used to create a unified data platform that supports BI tools like Power BI. This integration allows business analysts to generate reports and dashboards, providing actionable insights to stakeholders.
- The platform supports the creation of AI/BI dashboards, enabling drag-and-drop data visualizations and sharing insights across the organization.
2. **Data Integration and ETL**:
- Databricks provides powerful ETL (Extract, Transform, Load) capabilities, allowing data engineers to implement highly consistent and reliable ETL processes. This ensures that data is well-integrated and available for analysis.
- Delta Live Tables (DLT) simplifies the ETL process by allowing declarative ETL job writing, improving data quality through defined data expectations.
3. **Data Lakehouse Architecture**:
- Databricks combines the strengths of data lakes and data warehouses into a unified data lakehouse architecture. This architecture supports real-time data processing, data integration, schema evolution, and data transformations.
- The lakehouse architecture enables organizations to store and process data at scale, providing a single source of truth for data scientists, analysts, and production systems.
4. **Machine Learning and AI**:
- Databricks supports advanced analytics, machine learning (ML), and AI applications. Data scientists can use the platform to develop and deploy predictive models, leveraging tools like MLflow for model tracking and management.
- The platform also supports the creation of generative AI applications, such as chatbots and document summarization, by integrating with frameworks like LangChain.
5. **Real-Time Analytics and Streaming**:
- Databricks enables real-time data processing and analytics through its support for streaming data. This is particularly useful for use cases that require low-latency data processing, such as e-commerce recommendations and predictive maintenance.
- Organizations can use Databricks to build streaming pipelines that process data in real-time, ensuring up-to-date insights and decision-making.
6. **Data Governance and Security**:
- Unity Catalog in Databricks provides a unified and open governance solution for data and AI. It allows organizations to manage data access, ensure data quality, and maintain compliance with regulatory requirements.
- The platform supports secure data sharing and collaboration, enabling organizations to share data with external partners while maintaining control over data access.
https://learn.microsoft.com/en-us/azure/databricks/partners/bi/power-bi
https://learn.microsoft.com/en-us/azure/databricks/lakehouse-architecture/scope
https://www.databricks.com/blog/2019/11/04/new-microsoft-azure-data-warehouse-service-and-azure-data...
