We live in a data-driven business culture. Business professionals are learning to perform daily analytics work with less and less reliance on IT. Unsurprisingly, self-service Power BI is on the rise. This solution helps everyone in your organization find insightful answers to critical business questions.
More than 3,000 CIOs ranked analytics and BI as the top differentiating technologies for their organizations. With quick access to valuable information, Power BI keeps businesses self-aware and makes them ready to adapt to the unpredictable before their competitors.
At the same time, using a self-service reporting system with little or no control over data governance means business users are likely to end up with duplicate data. This duplication eventually leads to inconsistencies in reports throughout your organization, severely denting your bottom line.
To achieve long-term success in the age of self-service Power BI, you need to successfully build a data governance strategy.
What Is Self-Service in Power BI?
Self-service business intelligence (BI) is a data analytics method that allows business users (e.g., business analysts, managers, executives) to access and explore datasets without any experience in BI, data mining, and statistical analysis. Users can run queries and customize data visualization, dashboards, and reports to support real-time data-driven decision-making.
Power BI offers robust self-service capabilities. You can tap into data from on-premise and cloud-based data sources, (e.g., Dynamics 365, Salesforce, Azure SQL Data Warehouse, Excel, SharePoint,) then filter, sort, analyze, and visualize the information without the help of a BI or IT team.
Using the Power Query experience, business analysts can ingest, transform, integrate, and enrich big data directly in the Power BI web service. The ingested data can then be shared across various Power BI models, reports, and dashboards with other users.
Why Is Self-Service in Power BI Important?
Imagine this not-uncommon scenario: In a meeting, Alice asks Bob a BI-related question. Bob has to go to his BI/IT team to pull the data. A week later, Bob comes back with the report, and they resume the discussion. Alice has to explore the data with her team. Another week goes by before they pick up the conversation again. This massive iteration cycle is hurting the agility and productivity of many businesses.
What if Bob could just pull a report using real-time data at the first meeting? What if Alice can then ask the questions on the spot to drill down into relevant data sets? They have a conversation right there and condense three or more weeks’ worth of discussions into one meeting—and potentially walk away with a solution they can implement right away to respond to market demands.
The most important impact of Power BI self-service goes beyond the one-off benefits of real-time insights, improved collaboration, and easy reuse of data. When business users need to jump through hoops to obtain data analytics, they can’t develop the muscle memory they need to turn to data when making decisions.
Without such immediate connection with and access to data, people would simply fall back on their guts, memory, or perception of their experience to make decisions…which often lead to far-from-perfect results. On the other hand, real-time access to data that allows users to answer questions on the fly will help them develop the muscle memory to make data-driven business decisions.
What is Data Governance in Power BI?
Data governance ensures that enterprise data is accurate, complete, secure, trustworthy, and accessible by overseeing the people, processes, and technologies involved in managing an organization’s data assets.
Power BI provides administrators a centralized location to enforce governance. Admins also audit user activities, gain visibility into how data sources are used, and understand how solutions are implemented.
Besides using audit logs to monitor data sharing across the organization, administrators can intervene and educate users as needed. Governance in Power BI helps organizations ensure the safe and reliable use of authoritative data in decision-making processes, thereby building trust in data over the long term.
Why Data Governance is Needed
To take control of data consistency, security, and availability, data governance is mandatory as soon as you deploy self-service Power BI. Most organizations start using self-service Power BI systems with no data governance strategy in place. Soon they realize their reporting is out of control—and there’s no single source of truth to rely on when making crucial business decisions.
This incomplete or incorrect data leads to less credible reports, preventing business users from adopting the tool. Moreover, with little to no control over data, businesses are likely to fail when it comes to meeting security and privacy compliance requirements.
If you find yourself struggling to deal with this reporting mess, you aren’t the only one. We learned that 93% of respondents using self-service BI system rate governance as a major concern. Thankfully, the evolution of Microsoft Power BI has led to significant improvements to help you achieve data governance goals.
However, relying solely on built-in data governance features of a self-service Power BI platform won’t solve all of your data challenges. To develop a robust data governance framework, you must also consider the people and processes involved.
How to Build a Power BI Governance Model
A governance model is all about defining the best practices, procedures, and responsibilities for efficient and secure usage of your Power BI platform. Microsoft already has valuable information on data governance that you can use as a starting point. But, you’ll also need to consider pointers that are relevant to your organizational needs.
This is how you build your own Power BI data governance model to get the most out of the platform.
1. Identify Deployment Approach
Power BI can be used in three different modes—Business-Led Self-Service BI, IT-Managed Self-Service BI, and Corporate BI. The control over data and the way information gets handled will depend on these installation modes.
All of these modes can co-exist, depending on the business requirements and user base. So, it’s essential to know data governance methods for each mode.
- Business-Led Self-Service BI: Business users have full involvement and control in this self-service mode. Users explore both governed and ungoverned data sources.
- IT-Managed Self-Service BI: This mode involves co-ownership between IT and BI leaders. Business users generate reports from a high-quality, governed dataset produced by IT. Both IT and BI leaders define regulations and procedures while benefiting from accuracy and consistency in data.
- Corporate BI: In Corporate BI mode, IT has full ownership of the entire solution. Business users do not have a monitoring layer to change reports. However, Corporate BI guarantees complete data integrity and safety.
2. Define Roles
Two fundamental types of users access the self-service Power BI platform—power users and casual users. Power users need access to advanced features to create insightful reports. Casual users require flexibility to modify existing reports, such as drill-down and field selection.
Identifying these differences, and providing the right access according to roles, ensures that users have access to information without compromising security. Power BI offers tools that help you set up access permissions per data source, per user, and individual dashboards and reports.
3. Publish and Monitor
Monitoring what users are doing is crucial for effective data governance. Knowing what kind of reports users are creating, editing, and deleting provides a clear picture of how data is being used.
Monitoring helps you keep track of changes so data integrity isn’t compromised. You can easily monitor usage with the Power BI audit log, which reveals who accessed what and any changes that the user made.
Self-Service Power BI Governance Best Practices
To achieve maximum productivity, without compromising security, you’ll want to follow these self-service Power BI governance best practices.
Check Data Quality
Performing regular data quality checks and developing security measures maintain the accuracy and integrity of organizational data. Collaborate with IT to identify data quality issues before the business user starts generating reports.
Develop Training Materials
Good data governance begins with sufficient training for any team member who touches Power BI. Training could include developing videos, manuals, and data governance documents that offer relevant information according to roles and needs.
Encourage the Use of Standardized Datasets
To encourage users to utilize authoritative data, make use of Power BI’s certification and promotion feature. The platform allows IT admins to mark datasets as certified when they meet the defined quality criteria. Additionally, the promotion feature enables users to promote their datasets for further exploration, providing an opportunity to reuse data.
Find a Balance Between IT and BI Leaders
A self-service BI platform is likely to invite conflicts between IT and BI leaders in the long run. Each party has individual preferences towards data governance procedures and regulations. To achieve greater efficiency with Power BI, find a balance between both teams.
The best way to strike this balance is by establishing a data governance committee that includes members from both IT and BI. This way you build a data governance plan that is mutually agreed upon, reducing the chances of tension and misalignment.
Data governance is an integral part of Power BI implementation. A strong data governance strategy empowers each business unit to use data intelligently. In the end, your teams will produce more creative and valuable insights, while maintaining data security and privacy.