Power BI is collection of tools and services which facilitates the acquisition of data, data modeling, visualizations and reports, as well as the distribution of analytical solutions.
Power BI Overview
The most prominent components of the Power BI are:
Power BI Desktop – A desktop-based authoring tool for connecting, transforming, and modelling data for interactive reports. There are two versions available, one that aligns with Power BI Service and one that aligns with Power BI Report Server.
Power BI Service – A cloud-based service that supports collaboration, sharing, enterprise distribution, creation of dashboards and alerts
Power BI App Workspace – A collaboration area within Power BI Service. It is a distinct area, which is dedicated to a specific team, subject area, or project. This is so that colleagues can view the content, and contribute.
Power BI App – A set of packaged content in Power BI service for distributing related reports and dashboards to large base of consumers.
Power BI Mobile Apps – These are native applications for iOS, Android and Windows, for viewing reports and dashboards on a mobile device.
On-Premises Data Gateway – This is an agent installed within the corporate for secure access to on-premises organizational data. It is available in two modes, Enterprise mode and Personal mode.
Power BI Premium – It is an offering that provides dedicated resources within Power BI Service. It offers organizations more predictable performance, larger storage volumes, larger dataset sizes, higher refresh rates, and incremental data refresh. For each read-only user, it also enables widespread distribution of content without a Pro license.
Power BI Report Server – An alternate to the Power BI Service for deploying reports within an on-premises data center. Power BI reports are deployed and delivered in an on-premises portal alongside SSRS reports, Excel reports, and mobile reports.
Power BI Report Design
This is to offer some simple tips and tricks to make reports as responsive and easy to manage.
Manage Report Authorship
Controls over who builds reports, where these reports are published, and how many reports are published, is essential. Allowing unrestricted report creation will result in duplicate reports and datasets. This means that:
- Maintenance of reports becomes time-consuming and difficult in case data sources change or calculations need to be altered.
- You reach the limits for how much data a user can publish using a subscription, or even the available memory capacity.
- Scheduled refresh for large numbers of reports at the same time can put excess load on data sources, making both the data sources and the report refresh slow.
- Different data modeling decisions, inconsistent calculations, column and measure names, could mean difficulty in comparing the resulting data in different reports and unsure which reports to trust.
Version Control of Content
A lot of work can go into designing a dataset or a report, and so that this work is not lost make sure that you save a copy of your .pbix file somewhere safe after making any changes. The best way of doing this is through some form of version control. Power BI does not have any native features for version control or for interfacing with external version control systems, most version control systems allow you to store files of any type in a repository, including the .pbix.
To file size limits by some version control systems, consider using Power BI template files (.pbit files) instead of .pbix files so that the files you are storing in version control are as small as possible. Power BI templates do not contain any data, and this makes them much smaller than .pbix files. Typically template files are utilized for standardization of look and feel, so this usage of them will need to be documented and communicated to the team.
Store .pbix files in any file-sharing solution because it saves historical copies of your files. The number of historical copies retained is typically configurable. This allows to gain access to previous versions, if a change needs to be reverted. Also, the file size limit for files in file-sharing solutions is more than adequate for most .pbix files.
Making changes directly to reports in Power BI Service, source control and versioning for Power BI files becomes particularly challenging. To minimize the risk of overwriting/losing changes, implement a standard practice for editing reports and publishing them.
Separating dataset from Report Authorship
Creating a dataset requires a deep understanding of the data and how it should be modeled. Depending on the complexity level of data sources, calculations, cleansing, and relationships, this requires some level of technical skill.
In many cases business users just want to create their own reports and may not have the skill, time, or desire to build a dataset for that report. Creating datasets associated with every report that is build, can result in the creation of many duplicate datasets. Therefore, separate the development of the datasets used by reports from the reports themselves wherever possible.
- Utilize SQL server analysis Services to store data
- Create a dataset in a .pbix file without any reports and publish it. This will create a new data set in Power BI service. This can then be used to create new reports in Power BI Desktop or create new reports directly in the PowerBI Service using the web interface.
Datasets intended for reuse in this manner can be created by the subject matter experts. The advantages to this approach are:
- Different users with different skillsets can work on the dataset and reports independently.
- The overall number of datasets is reduced, resulting in less maintenance is needed, scheduled refresh will be faster, and less data is stored in Power BI.
Use Template to Speed Up and Standardize Reports
Enforcing standards on the report being build from scratch can be time-consuming and difficult. To speed up the report development significantly, use Power BI templates (.pbit files), this will also help with standardization.
Templates allow you to create new .pbix files which
- Have corporate color scheme already in place
- Have corporate branding already applied
- Commonly used data connection already created
- Data source queries are parameterized making them easy to reuse yet customize the query behavior
- Commonly used DAX measures already created in the dataset