The podcast discusses the potential impact of Fabric on the adoption of Power BI desktop, highlighting the concerns of business analysts and the challenges faced by IT organizations. It explores the advantages and disadvantages of using Fabric for business purposes, emphasizing its quick adoption and data visualization capabilities. The concept of creating separate pipelines and curating data sets is also explored, highlighting the importance of relevant data and permission levels. The podcast delves into the features and benefits of Fabric in comparison to existing solutions, discussing its value for organizations with a focus on SQL and data culture.
Fabric in Power BI provides a centralized system for data storage and processing, simplifying integration and bringing transparency to data processes.
Adopting fabric may be challenging for IT departments, highlighting the need for controlled and incremental implementation to showcase success stories and expand usage.
Segmented implementation of fabric, starting with a single use case and gradually expanding, allows business users to adopt fabric at their own pace and increases overall data maturity.
Deep dives
The Potential of Fabric in Power BI
Fabric in Power BI has the potential to bring a lot of interesting workflows into the platform, especially for business users. It unifies the architecture and provides a centralized system for data storage and processing. Fabric simplifies the process of connecting different services and allows for easier integration of third-party systems. This unified approach also brings transparency to data processes, making it easier to trace the flow of data from source to report. While there may be concerns about overwhelming business users with the complexity of fabric, starting with small segments and gradually expanding the usage can help in adoption and success.
Challenges in Adoption and Unifying Data Engineering
Adopting fabric may be challenging for IT departments, as they may not fully understand its integration with existing systems. There can be reservations about switching to fabric, especially for organizations that have already established efficient data engineering processes. It is important to highlight the benefits of fabric in terms of unified data storage, improved transparency, and simplified integration with third-party systems. However, the implementation of fabric should be done in a controlled and incremental manner, introducing segments and showcasing success stories to gradually expand its usage.
The Role of Segmented Implementation and Increasing Data Literacy
A segmented implementation approach can be beneficial in introducing fabric to business units. Starting with a single use case, such as a lake house, and gradually expanding the usage can help business users become familiar with fabric's capabilities without overwhelming them. This approach not only enables business users to adopt fabric at their own pace but also elevates their data literacy. By creating accurate pipelines and demonstrating the value of fabric in specific business units, organizations can increase the overall data maturity and drive better decision-making.
Advantages of fabric over existing systems
Fabric provides opportunities for diverse teams to work together in the same environment, although some IT professionals may be hesitant to migrate over due to a feature gap. The integration of fabric with Power BI allows for direct access to lake house tables, which simplifies the data engineering process. However, there is a need for a clear roadmap and best practices to fully utilize the potential of fabric.
The challenges of adopting fabric for business users
The lack of a clear understanding of how to use a lake house in departments or teams creates uncertainty for business users. The need to learn new concepts like Apache Spark and Delta Lake makes it difficult to integrate fabric into the existing workflow. There is also a need for comprehensive training and education to bridge the skill gap for business analysts. The fabric workspace can be a valuable tool for business users to access and analyze refined data sets, but the implementation should be done gradually and accompanied by proper training and guidance.
Mike, Seth, & Tommy dive into an awesome mailbag question:
When Microsoft added PBI desktop to O365 (Dynamic 365? Something 365) it was seen as something that will really increase adoption as more business analysts are exposed to it. But I wonder if Fabric (which as an IT professional, I'm really excited about) will have the opposite effect. Will business analysts and leaders find it too intimidating once they start to hear about data engineering, data science, pipelines, Datalakes, etc? And will IT departments pull back on it out of fear that these new tools will be used inappropriately? You've talked about it from the IT department side some, but I'm really curious what you think about overwhelming the business side. I can see a lot of "No thanks, I'll stick to Excel" thinking for those newly introduced to PBI/Fabric. Legacy business users, maybe not so much?
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