13.1 Futureproofing with Microsoft Fabric
As Microsoft transitions to Fabric, an integrated end-to-end analytics platform, BMT must prepare to leverage its features effectively. The following steps will ensure readiness:
- Pilot Testing: Initiate sandbox environments to explore Microsoft Fabric’s capabilities and assess compatibility with existing systems.
- Impact Assessment: Evaluate the potential impact of Microsoft Fabric on current Data Warehouse and Data Mart structures.
- Training and Upskilling: Provide training for Data Engineering and Business Intelligence teams to understand and use Fabric’s tools effectively.
- Incremental Transition: Develop a phased migration plan to adopt Fabric, starting with non-critical workloads.
- Continuous Review: Regularly review Microsoft Fabric’s updates to align with BMT’s evolving analytics needs.
Fabric integrates workloads like Data Engineering, Data Factory, Data Science, Data Warehouse, Real-Time Intelligence, Industry solutions, Databases, and Power BI into a shared SaaS foundation. Each of these experiences is tailored for distinct user roles like data engineers, scientists, or warehousing professionals, and they serve a specific task.
The AI-integrated Fabric stack accelerates the data journey and offers the following advantages:
- Extensive integrated analytics
- Familiar and easy-to-learn shared experiences
- Easy access and reuse of all assets
- Unified data lake storage preserving data in its original location
- Centralised administration and governance
13.2 Advanced Analytics and Machine Learning
The Platinum layer is the foundation for advanced analytics, enabling the integration of predictive and prescriptive capabilities to drive intelligent decision-making across the organisation. To future-proof this layer, we will harness the power of Azure Machine Learning, Azure Synapse Analytics, and Azure Databricks to create a scalable, cloud-native environment for developing, deploying, and managing machine learning models.
- Advanced Business Transformations:
- Complex Transformations: The Platinum Layer handles intricate data transformations that go beyond the scope of the Silver and Gold layers. These transformations include aggregations, financial modeling, and scenario analysis to support strategic decision-making.
- Business Logic Integration: This layer integrates sophisticated business logic to ensure that the data transformations align with organizational goals and strategies.
- Machine Learning and Predictive Analytics:
- ML Models: The Platinum Layer is where machine learning models are developed, trained, and validated. These models use historical data to make predictions about future trends, such as sales forecasts, customer behaviour, and budget requirements.
- Predictive Analytics: By applying ML algorithms, the Platinum Layer generates predictive insights that help the organization anticipate future scenarios and make data-driven decisions.
- Integration and Data Flow:
- Returning Views to Gold Layer: The outputs from the Platinum Layer, including transformed views and predictive insights, are returned to the Gold Layer. This ensures that these advanced analytics are readily accessible for consumption and integration into business processes.
- Continuous Feedback Loop: The Platinum Layer operates in a continuous feedback loop, where insights and models are constantly refined based on new data and changing business conditions.
- Opportunities:
- Predictive Analytics: Utilizing advanced machine learning models for predictive analytics and forecasting.
- Business Transformation: Leveraging data insights for strategic business transformations and decision-making.
- Collaboration with Data Scientists: Enhancing collaboration with data scientists to develop innovative solutions.