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Executive leadership: Individuals who are responsible for defining organizational goals and strategies, like the Power BI executive sponsor or a Chief Executive Officer (CEO), Chief Information Officer (CIO), or Chief Data Officer (CDO). BI and analytics directors or managers: Decision makers who are responsible for overseeing the BI program and BI strategic planning. Center of Excellence (COE), IT, and BI teams: The teams that are responsible for tactical planning, measuring, and monitoring progress toward the BI objectives. Subject matter experts (SMEs) and content owners and creators: The teams and individuals that champion analytics in a team or department and conduct BI solution planning. These teams and individuals are responsible for representing the strategy and data needs of their business area when defining the BI strategy.

Defining your BI strategy is essential to get the most business value from BI initiatives and solutions. Having a clearly defined BI strategy is important to ensure efforts are aligned with organizational priorities.

Become data-driven with a BI strategy

Your business strategy should directly inform your BI strategy. As your business objectives evolve, your BI processes and tools may also need to evolve, especially as new data needs arise. New opportunities and insights learned from BI solutions can also lead to changes to your business strategy

In this series, goals are high-level descriptions of what you want to achieve. In contrast, objectives are specific, actionable targets to help you achieve a goal. While a goal describes the desired future state, objectives describe the path to get there

A successful BI strategy starts small. It focuses on a few prioritized areas and broadens scope over time, ensuring consistent progress

In this example, the BI goals and priorities are: Data literacy: Improve the ability of the salespeople to make decisions based on data and report visualizations. Content ownership: Clarify who owns the data and reporting items for different use cases. Mentoring and user enablement: More effectively enable the salespeople with the skills and tools to answer questions with data. Governance: More effectively balance governance risk and enablement of the sales teams. Data engineering: Create a unified view of sales and profitability data for analytics

In this example, the BI objectives are: Data literacy: Ensure that 90 percent of the salespeople complete the data literacy program. Content ownership: Adopt the managed self-service BI usage scenario, where central teams manage central, certified Power BI datasets and reports. Some self-service content creators can connect to these datasets for their own analysis and reporting needs.

To achieve its objectives, the organization aims to design and deploy the following BI solutions. Central BI teams will work to store profitability data for customers and products in a unified lakehouse. Central BI teams will publish an enterprise semantic model as a Power BI dataset that includes all data required for central reporting and key self-service reporting scenarios. Security rules applied to the Power BI dataset enforce that salespeople can only access data for their assigned customers. Central BI teams will create central reports that show aggregate sales and profitability across regions and product groups. These central reports will support more sophisticated analysis by using interactive visualizations. Salespeople can connect directly to the BI dataset

Incremental progress: Define your BI strategy by focusing on priorities and breaking them into manageable parts. You can implement these parts in phases and complete them incrementally over multiple continuous improvement cycles

Strategic planning (every 12-18 months): This high-level planning focuses on aligning business goals and BI goals. It's valuable to align this strategic planning with other annualized business processes, like budgeting periods. Tactical planning (every 1-3 months): Monthly or quarterly planning sessions focus on evaluating and adjusting existing tactical plans. These sessions assess existing priorities and tasks, which should take business feedback and changes in business or technology into account. Continuous improvement (every month): Monthly sessions focus on feedback and urgent changes that impact ongoing planning. If necessary, decision makers can make decisions, take corrective action, or influence ongoing planning.

Your first step when defining your BI strategy is to establish a working team. A working team leads the initiative to describe and plan the BI strategy. It's a cross-functional group of experts that's enabled by the support of the executive sponsor. The group should have a deep understanding of technical and business processes across the organization.

A COE or central BI team confers with the executive sponsor to identify and appoint working team members. The COE may also provide guidance to the working team to support their activities.

Identify and engage an executive sponsor A key role of the executive sponsor is to help formulate strategic BI goals and priorities. The executive sponsor is an individual in a position of senior, strategic leadership who has an invested stake in BI efforts and the BI strategy. They provide top-down guidance and reinforcement by regularly promoting, motivating, and investing in the BI strategy.

Advocating for the initiative: They advance the strategic initiative by: Legitimizing working team activities, particularly when the working team faces resistance to change. Promoting the BI strategy initiative with announcements or public endorsement. Motivating action and change to progress the BI strategy initiative. Representing the working team and sharing the BI strategic plan among C-level executives to obtain executive feedback

Planning and preparation: The working team should plan and prepare the various aspects of the BI strategy initiative, such as: Defining the timelines, deliverables, and milestones for the initiative.

Create a communication hub

While a moderator should be proficient in eliciting information, they don't require deep domain knowledge. Ideally, all workshops for a given business area should be led by the same moderator. The objective of the workshops is to collect sufficient input from stakeholders to accurately describe their business objectives and data needs. A successful workshop concludes with stakeholders feeling that the working team members understand the business objectives and data needs. This stakeholder input is used together with the working team's independent research to complete an assessment of the current state of BI adoption and implementation.

For each business area in scope, these findings should describe: Business goals. Business objectives to make progress towards their goals. Business processes and initiatives to achieve their objectives. Business data needs to support the processes and initiatives. BI tools and solutions that people use to address their business data needs. How people use the tools and solutions, and any challenges that prevent them from using the tools and solutions effectively

Align with stakeholders and executives It's critical that the final assessments and decisions be shared with stakeholders. In the communication hub, stakeholders can asynchronously follow up on the progress of these deliverables and contribute feedback. However, you should conclude strategic planning by presenting the assessments and priorities back to stakeholders and executives. The following sections describe how you align with stakeholders and executives.

This article helps you to define your business intelligence (BI) goals and priorities through strategic planning. It's primarily targeted at:

A BI strategy is a plan to implement, use, and manage data and analytics. As described in the BI strategy overview article, your BI strategy is a subset of your data strategy. It supports your business strategy by enabling business users to make decisions and take actions by using data and BI solutions more effectively.

In this series, we define goals as high-level descriptions of what you want to achieve. In contrast, objectives are specific, actionable targets that help you achieve a goal. While a goal describes the desired future state, objectives describe the path to get there.

This article helps you to plan solutions that support your business intelligence (BI) strategy. It's primarily targeted at: BI and analytics directors or managers: Decision makers who are responsible for overseeing the BI program and strategically important BI solutions. Center of Excellence (COE), IT, and BI teams: The teams that design and deploy enterprise BI solutions for their organization. Subject matter experts (SMEs) and content owners and creators: The teams and individuals that champion analytics in a department and design and deploy solutions for self-service, departmental BI, or team BI usage scenarios

You define your BI strategy by starting with BI strategic planning. Strategic planning helps you to identify your BI goals and priorities. To determine the path to progress toward your BI goals, you describe specific objectives by using tactical planning. You then achieve progress toward your BI objectives by planning and deploying BI solutions.

Collecting the wrong requirements is a common reason why implementations fail. Often, teams collect the wrong requirements because they engaged with the wrong stakeholders, like decision makers who provide top-down requests

The business design concludes with the following deliverables. Draft solution designs: Mock-ups, prototypes, or wireframe diagrams illustrate the solution design. These documents translate the requirements to a concrete design blueprint. List of business metrics: Quantitative fields expected in the solution, including business definitions, and expected aggregations. If possible, rank them by importance to the users. List of business attributes: Relevant attributes and data structures expected in the solution, including business definitions and attribute names. If possible, include hierarchies and rank the attributes by importance to the users. Supplemental documentation: Descriptions of key functional or compliance requirements. This documentation should

Conduct initial setup The project team should perform initial set up to commence development. Initial set up activities can include: Initial tools and processes: Perform first-time setup for any new tools and processes needed for development, testing, and deployment. Identities and credentials: Create security groups and service principals that will be used to access tools and systems. Effectively and securely store the credentials. Data gateways: Deploy data gateways for on-premises data sources (enterprise mode gateways) or data sources on a private network (virtual network, or VNet, gateways). Workspaces and repositories: Create and set up workspaces and remote repositories for publishing and storing content

Step 3: Conduct a proof of concept

Iterative development and validation cycles proceed until the project team arrives at a predefined conclusion. Typically, development concludes when there are no more features to implement or user feedback to address. When the development and validation cycles conclude, the project team deploys the content to a production environment with the final production release. The following diagram depicts how the project team can iteratively deliver BI solutions with development and validation cycles. The diagram depicts the following steps.

simplify the process, consider handling the following requests together: Software requests User license requests Training requests Data access requests

Plan for authoring tools

Paginated reports are best suited to highly formatted, or print-ready, reports such as financial statements

A paginated report always focuses on the creation of one individual report (conversely, a dataset created in Power BI Desktop may serve many different reports).

more skill than creating

Proper workspace planning is an integral part of making an implementation successful

We recommend that you make the tenant-level workspace decisions as early as possible because they'll affect everything else

Managing this process can be fully centralized (for instance, only IT is permitted to create a workspace). A more flexible and practical approach is when it's a combination of centralized and decentralized individuals. In this case, certain satellite members of the Center of Excellence (COE), champions, or trusted users have been trained to create and manage workspaces on behalf of their business unit.

Workspace naming conventions

The following table lists the information to collect in a request for a new workspace.

Workspace governance level

There are four key decision criteria to determine the level of governance: Who owns and manages the BI content? What is the scope for delivery of the BI content? What is the data subject area? Is the data, and/or the BI solution, considered critical?

You might start out with two levels of workspaces: governed and ungoverned. We recommend that you keep the governance levels as simple as possible

When planning for workspaces, it's important to consider not only the type of content it will store, but also the activities that the workspace is intended to support.

Business-led self-service BI: Content is owned and managed by the content creators within a business unit or department.

and managed by a centralized team, whereas various content creators from

Consider expectations for collaboration: Determine how workspace collaboration needs to occur and who's involved within a single team or across organizational boundaries. Consider expectations for content ownership and management: Think about how the different content ownership and management approaches (business-led self-service BI, managed self-service BI, and enterprise BI) will influence how you design and use workspaces.

The secondary objective for a workspace is to distribute content to consumers who need to view the content

Workspace ownership

One of the most important things to consider when planning workspaces is determining the ownership and stewardship roles and responsibilities. The goal is to have clarity on exactly who is accountable for creating, maintaining, publishing, securing, and supporting the content in each workspace

to the principle of least privilege

Your decisions related to accountability and responsibility should correlate directly with your actions related to defining workspace access, which is described later in this article.

A workspace naming convention is required

Determine your objectives for data reuse: Decide how to achieve data reuse as part of a managed self-service BI strategy. Update the tenant setting for who can use datasets across workspaces: Determine whether this capability can be granted to all users. If you decide to limit who can use datasets across workspaces, consider

Workspace lifecycle management

Source file storage

Large enterprise BI implementations often employ a centralized approach. Enterprise Power BI content is commonly maintained by a centralized team, for use broadly throughout the organization. The centralized team responsible for content management is usually IT, BI, or the Center of Excellence (COE)

Avoids creating duplicate datasets. Reduces the risk of inconsistent data and calculations. Supports all slicing, dicing, and pivoting capabilities within the visuals while remaining connected to the dataset that's stored in the Power BI service.

discipline at the core and flexibility at the edge. The data architecture is usually maintained by a single team of centralized BI experts, while reporting responsibility belongs to creators within departments or business units

Shared dataset The key aspect of making managed self-service BI work is to minimize the number of datasets. This scenario is about shared datasets that help achieve a single version of the truth.

reports, it facilitates the separation of effort and responsibility. A shared dataset is commonly maintained by a centralized team

As described in the Power BI adoption roadmap, managed self-service BI is characterized by a blended approach that emphasizes discipline at the core and flexibility at the edge. The data architecture is usually maintained by a single team of centralized BI experts, while reporting responsibility belongs to creators within departments

However, when the core data architecture doesn't include all data required, dataset creators can extend, personalize, or customize existing shared datasets.

Sometimes self-service creators need to augment an existing dataset with, for instance, additional data that's specific to their department. In this case, they can use DirectQuery connections to Power BI datasets

The scenario diagram depicts a DirectQuery connection. The act of converting a live connection to a DirectQuery connection creates a local model that allows new tables to be added

Support dataset creators The scenario diagram depicts using a Power BI dataflow to provide prepared data to other self-service dataset creators. Note Datasets use the dataflow as a data source. A report can't connect directly to a dataflow. Here are some advantages of using Power BI dataflows

A prototype—or proof of concept (POC)—is a Power BI solution that's intended to address unknowns and mitigate risk

Power BI service Publishing prototyping solutions to the Power BI service is optional. It can be useful when there's a need to share preliminary results for feedback and decision-making purposes. Tip Prototyping solutions