In the fast-paced world of business, enterprises have long grappled with the challenge of weaving together diverse tools and technologies for tasks like business intelligence (BI), data science, and data warehousing.
This much needed plumbing often results in increased overheads, inefficiencies, and siloed operations.
Recognizing this struggle, Microsoft is gearing up to launch the Microsoft Fabric platform on its Azure cloud platform, promising to seamlessly integrate these capabilities and simplify the way enterprises handle their data.
Power of Integration
Imagine a world where the various threads of data engineering, data warehousing, Power BI, and data science are woven together into a single fabric. This is the vision behind Microsoft Fabric.
Instead of managing multiple disjointed systems, enterprises will be able to orchestrate their data processes more efficiently, allowing them to focus on insights and innovation rather than wrestling with the complexities of integration.
This is also the premise behind Ignitho’s Customer Data Platform Accelerator on the Domo platform. Domo has already integrated these capabilities. And Ignitho has also enhanced the platform with domain specific prebuilt AI models and dashboards.
Now enterprises have more choice as platforms such as Microsoft and Snowflake adopt a similar approach going into the future.
What is Microsoft Fabric Comprised Of
MS Fabric is still in Beta but will soon bring together all of the typical capabilities required for a comprehensive enterprise data and analytics strategy.
With Microsoft Fabric, data engineering becomes an integral part of the bigger picture.
These tasks are generally about getting data from the multiple source systems, transforming the data, and loading it into a target data warehouse from where insights can be generated.
For instance, think of a retail company that can easily combine sales data from different stores and regions into a coherent dataset, enabling them to identify trends and optimize their inventory.
A powerful data warehouse is not conceptually at the heart of Microsoft Fabric. Azure synapse is more logically integrated under the Fabric platform umbrella so can be deployed and managed more easily.
Rather than having a mix and match approach, Fabric makes it semantically easier to simply connect data engineering to the data warehouse.
For example, a healthcare organization can consolidate patient records from various hospitals, enabling them to gain comprehensive insights into patient care and outcomes.
Microsoft’s Power BI, a popular business analytics tool, now seamlessly integrates with the Fabric platform.
This means that enterprises can both deploy and manage Power BI more simply, along with data integrations and the data warehouse, to create insightful reports and dashboards.
Consider a financial institution that combines data from different departments to monitor real-time financial performance, enabling quicker decision-making.
These implementations of Power BI will now naturally gravitate to a data source that is on MS Fabric depending on the enterprise data and vendor strategy. In addition, the AI features on Power BI are also coming up soon.
Building on the power of Azure’s machine learning capabilities, Microsoft Fabric supports data science endeavors.
The important development now is that data scientists can access and analyze data directly from the unified platform, enhancing the deployment simplicity and speed of model development.
For instance, an e-commerce company can utilize data science to predict customer preferences and personalize product recommendations. These models are now more easily integrated with MS Power BI.
Important Considerations for Enterprises
MS Fabric promises to be a gamechanger when it comes to enterprise data strategy and analytics capability. But with any new capability comes a series of important decisions and evaluations that have to be made.
Evaluating Architecture and Migration
As Microsoft Fabric is still in its beta phase, enterprises should assess their existing architecture and create a migration plan if necessary.
Especially, if you haven’t yet settled on an enterprise data warehouse or are in the early stages of planning your data science capability, then MS Fabric needs a good look.
While there might be uncertainties during this phase, it’s safe to assume that Microsoft will refine the architecture and eliminate silos over time.
While Microsoft Fabric excels in bringing together various data capabilities, it’s essential to note that it currently still seems to lack a streamlined solution for API integration of AI insights, not just the data in the warehouse.
Enterprises should consider this when planning the last mile adoption of AI insights into their processes. However, just like we have done this in Ignitho’s CDP architecture, we believe MS will address this quickly enough.
It’s expected that Microsoft’s goal is to provide a single platform on its own cloud where enterprise can meet all their needs.
However, both from a risk management perspective, and those who favor a best of breed architecture, the tradeoffs must be evaluated.
In my opinion, the simplicity that MS Fabric provides is an important criterion. That’s because over time most platforms will converge towards similar performance and features. And any enterprise implementation will require custom workflows and enhancements unique to their business needs and landscape.
If your enterprise relies on the Microsoft stack, particularly Power BI, and is in the process of shaping its AI and data strategy, Microsoft Fabric deserves your attention.
By offering an integrated platform for data engineering, data warehousing, Power BI, and data science, it holds the potential to simplify operations, enhance decision-making, and drive innovation.
MS still has some work to do to enable a better last mile adoption, and simplify the stack further, but we can assume that MS is treating that with high priority too.
In summary, the promise that the Microsoft Fabric architecture holds for streamlining data operations and enabling holistic insights makes it a strong candidate for businesses seeking efficiency and growth in the data-driven era.
Contact us for an evaluation to help you with your data strategy and roadmap. Also read our last blog on generative ai in power bi.