Microsoft Fabric adoption roadmap

The goal of this series of articles is to provide a roadmap. The roadmap presents a series of strategic and tactical considerations and action items that lead to the successful adoption of Microsoft Fabric, and help build a data culture in your organization.

Advancing adoption and cultivating a data culture is about more than implementing technology features. Technology can assist an organization in making the greatest impact, but a healthy data culture involves many considerations across the spectrum of people, processes, and technology.

Note

While reading this series of articles, we recommended that you also take into consideration Power BI implementation planning guidance. After you're familiar with the concepts in the Microsoft Fabric adoption roadmap, consider reviewing the usage scenarios. Understanding the diverse ways Power BI is used can influence your implementation strategies and decisions for all of Microsoft Fabric.

The diagram depicts the following areas of the Microsoft Fabric adoption roadmap.

The areas in the above diagram include:

Area	Description
	Data culture: Data culture refers to a set of behaviors and norms in the organization that encourages a data-driven culture. Building a data culture is closely related to adopting Fabric, and it's often a key aspect of an organization's digital transformation.
	Executive sponsor: An executive sponsor is someone with credibility, influence, and authority throughout the organization. They advocate for building a data culture and adopting Fabric.
	Business Alignment: How well the data culture and data strategy enable business users to achieve business objectives. An effective BI data strategy aligns with the business strategy.
	Content ownership and management: There are three primary strategies for how business intelligence (BI) and analytics content is owned and managed: business-led self-service BI, managed self-service BI, and enterprise BI. These strategies have a significant influence on adoption, governance, and the Center of Excellence (COE) operating model.
	Content delivery scope: There are four primary strategies for content and data delivery: personal, team, departmental, and enterprise. These strategies have a significant influence on adoption, governance, and the COE operating model.
	Center of Excellence: A Fabric COE is an internal team of technical and business experts. These experts actively assist others who are working with data within the organization. The COE forms the nucleus of the broader community to advance adoption goals that are aligned with the data culture vision.
	Governance: Data governance is a set of policies and procedures that define the ways in which an organization wants data to be used. When adopting Fabric, the goal of governance is to empower the internal user community to the greatest extent possible, while adhering to industry, governmental, and contractual requirements and regulations.
	Mentoring and user enablement: A critical objective for adoption efforts is to enable users to accomplish as much as they can within the guardrails established by governance guidelines and policies. The act of mentoring users is one of the most important responsibilities of the COE. It has a direct influence on adoption efforts.
	Community of practice: A community of practice comprises a group of people with a common interest, who interact with and help each other on a voluntary basis. An active community is an indicator of a healthy data culture. It can significantly advance adoption efforts.
	User support: User support includes both informally organized and formally organized methods of resolving issues and answering questions. Both formal and informal support methods are critical for adoption.
	System oversight: System oversight includes the day-to-day administration responsibilities to support the internal processes, tools, and people.
	Change management: Change management involves procedures to address the impact of change for people in an organization. These procedures safeguard against disruption and productivity loss due to changes in solutions or processes. An effective data strategy describes who is responsible for managing this change and the practices and resources needed to realize it.

The relationships in the above diagram can be summarized as follows.

• Your organizational data culture vision will strongly influence the strategies that you follow for self-service and enterprise content ownership and management and content delivery scope.
• These strategies will, in turn, have a big impact on the operating model for your Center of Excellence and governance decisions.
• The established governance guidelines, policies, and processes affect the implementation methods used for mentoring and enablement, the community of practice, and user support.
• Governance decisions will dictate the day-to-day system oversight (administration) activities.
• Adoption and governance decisions are implemented alongside change management to mitigate the impact and disruption of change on existing business processes.
• All data culture and adoption-related decisions and actions are accomplished more easily with guidance and leadership from an executive sponsor, who facilitates business alignment between the business strategy and data strategy. This alignment in turn informs data culture and governance decisions.

Each individual article in this series discusses key topics associated with the items in the diagram. Considerations and potential action items are provided. Each article concludes with a set of maturity levels to help you assess your current state so you can decide what action to take next.

Microsoft Fabric adoption

Successful adoption of analytical tools like Fabric involves making effective processes, support, tools, and data available and integrated into regular ongoing patterns of usage for content creators, consumers, and stakeholders in the organization.

Important

This series of adoption articles is focused on organizational adoption. See Microsoft Fabric adoption maturity levels for an introduction to the three types of adoption: organizational, user, and solution.

A common misconception is that adoption relates primarily to usage or the number of users. There's no question that usage statistics are an important factor. However, usage isn't the only factor. Adoption isn't just about using the technology regularly; it's about using it effectively. Effectiveness is much more difficult to define and measure.

Whenever possible, adoption efforts should be aligned across analytics platforms and BI services.

Note

Individuals—and the organization itself—are continually learning, changing, and improving. That means there's no formal end to adoption-related efforts.

The remaining articles in this Power BI adoption series discuss the following aspects of adoption.

• Adoption maturity levels
• Data culture
• Executive sponsorship
• Business alignment
• Content ownership and management
• Content delivery scope
• Center of Excellence
• Governance
• Mentoring and enablement
• Community of practice
• User support
• System oversight
• Change management
• Conclusion and additional resources

Important

You might be wondering how this Fabric adoption roadmap is different from the Power BI adoption framework. The adoption framework was created primarily to support Microsoft partners. It's a lightweight set of resources to help partners deploy Power BI solutions for their customers.

This adoption series is more current. It's intended to guide any person or organization that is using—or considering using—Fabric. If you're seeking to improve your existing Power BI of Fabric implementation, or planning a new Power BI or Fabric implementation, this adoption roadmap is a great place to start.

Target audience

The intended audience of this series of articles is interested in one or more of the following outcomes.

• Improving their organization's ability to effectively use analytics.
• Increasing their organization's maturity level related to the delivery of analytics.
• Understanding and overcoming adoption-related challenges faced when scaling and growing.
• Increasing their organization's return on investment (ROI) in data and analytics.

This series of articles will be most helpful to those who work in an organization with one or more of the following characteristics.

• Power BI or other Fabric workloads are deployed with some successes.
• There are pockets of viral adoption, but analytics isn't being purposefully governed across the entire organization.
• Analytics solutions are deployed with some meaningful scale, but there remains a need to determine:
  • What is effective and what should be maintained.
  • What should be improved.
  • How future deployments could be more strategic.
• An expanded implementation of analytics is under consideration or is planned.

This series of articles will also be helpful for:

• Organizations that are in the early stages of an analytics implementation.
• Organizations that have had success with adoption and now want to evaluate their current maturity level.

Assumptions and scope

The primary focus of this series of articles is on the Microsoft Fabric platform.

To fully benefit from the information provided in these articles, you should have an understanding of Power BI foundational concepts and Fabric foundational concepts.

Related content

In the next article in this series, learn about the Fabric adoption maturity levels. The maturity levels are referenced throughout the entire series of articles. Also, see the conclusion article for additional adoption-related resources.

Other helpful resources include:

• Power BI implementation planning
• Questions? Try asking the Microsoft Fabric community.
• Suggestions? Contribute ideas to improve Microsoft Fabric.

Experienced partners are available to help your organization succeed with adoption initiatives. To engage with a partner, visit the Power BI partner portal.

Acknowledgments

The Microsoft Fabric adoption roadmap articles are written by Melissa Coates, Kurt Buhler, and Peter Myers. Matthew Roche, from the Fabric Customer Advisory Team, provides strategic guidance and feedback to the subject matter experts. Reviewers include Cory Moore, James Ward, Timothy Bindas, Greg Moir, and Chuy Varela.