I’ve been doing some work with Power BI Online datasets this week. It’s the first time I’ve taken a look at them in any great detail, as I have traditionally preferred to create and deploy any data sources needed for my reports via the Desktop client. Datasets address the needs for users who do not necessarily have the necessary Power Query/DAX language and require a mechanism to quickly hook up to a pre-prepared dataset, thereby allowing them to start consuming any data rapidly. They are defined within an individual workspace and, once deployed, can then be shared out to other users to connect to. Datasets can help towards ensuring that any extensive piece of work developing a data model can be benefitted by as many users as possible and can reduce the need for people having to create data sources themselves if organised correctly. To find out more about how to create a dataset, you can take a look through my recent series all around Microsoft Exam 70-778, where I cover this topic in further detail.

Datasets can remove some headaches for more substantial Power BI deployments, but you should be aware of they can’t do. The most noteworthy limitations include:

  • You can only connect a Power BI report to a single Power BI dataset at any time. You are unable to bring in additional data sources via Power Query and, likewise, if you have already defined several data sources within your report, you cannot then bring a Power BI dataset into your model.
  • It is not possible to make any modifications to a Power BI dataset from within Power BI Desktop, either via Power Query manipulation or by adding DAX custom columns; you can, however, define new Measures using DAX.

Where this can start to be problematic is when you are attempting to surface data generated by the Applications Insights Continuous Export facility via a Stream Analytics job. The great thing about Stream Analytics is that you can define multiple input/output locations for data that it processes, one of which includes a Power BI dataset. A convenient feature and one that can potentially sidestep the need to export any information out to a SQL-based destination for further processing. However, one area where the feature handicaps itself is in the fact that you cannot output multiple tables within the same Power BI dataset. If you attempt to do this, you get the following error message:

When you take into account the limitations mentioned above concerning a strict 1:1 mapping between dataset/report, problems can arise when it comes to defining your queries on the Stream Analytics side of things. You either have to export out all of the base information in a raw format or instead develop highly customised queries on the Stream Analytics side. The latter solution may successfully meet a specific business requirement, but risks putting you in a position where your BI solution contains many different reports, some of which may only include a meagre amount of visualisations. I’m not sure about you, but my preference would be more towards the first option, as opposed to building out an overtly complex BI solution; but the limitations that Power BI datasets introduce for this particular scenario does present some challenge in sticking to this mantra.

For example, assume we have the following Stream Analytics query that outputs Request information from Application Insights into a Power BI dataset:

SELECT 
    requestflat.ArrayValue.id AS RequestID,
    requestflat.ArrayValue.name AS RequestType,
    requestflat.ArrayValue.responseCode AS ResponseCode,
    requestflat.ArrayValue.success AS RequestSuccessful,
    requestflat.ArrayValue.url AS URL,
    requestflat.ArrayValue.urlData.base AS BaseURL,
    requestflat.ArrayValue.urlData.host AS URLHost,
    requestflat.ArrayValue.durationMetric.value AS Duration,
    r.internal.data.id AS ID,
    r.internal.data.documentVersion AS DocumentVersion,
    r.context.data.eventTime AS EventTime,
    r.context.data.isSynthetic AS IsSynthetic,
    r.context.data.syntheticSource AS SyntheticSource,
    r.context.data.samplingRate AS SamplingRate,
    r.context.device.type AS DeviceType,
    r.context.device.roleName AS SlotName,
    r.context.device.roleinstance AS RoleInstance,
    r.context.session.isFirst AS IsFirstSession,
    r.context.operation.id AS OperationID,
    r.context.operation.parentID AS OperationParentID,
    r.context.operation.name AS OperationName,
    GetRecordPropertyValue(GetArrayElement(r.[context].[custom].[dimensions], 0), 'Platform') AS Platform,
    GetRecordPropertyValue(GetArrayElement(r.[context].[custom].[dimensions], 1), 'Browser') AS Browser,
    GetRecordPropertyValue(GetArrayElement(r.[context].[custom].[dimensions], 3), 'UserAgent') AS UserAgent,
    GetRecordPropertyValue(GetArrayElement(r.[context].[custom].[dimensions], 4), 'Browser_Version') AS BrowserVersion,
    GetRecordPropertyValue(GetArrayElement(r.[context].[custom].[dimensions], 5), 'Referrer') AS ReferralURL,
    r.EventProcessedUtcTime AS RequestEventProcessedUtcTime,
    r.context.[user].anonId AS AnonymousID,
    r.context.location.continent AS ClientLocation,
    r.context.location.country AS ClientCountry
INTO [PowerBIRequestsOutput]
FROM [Requests] AS r
CROSS APPLY GetElements(r.[request]) AS requestflat

Having the data in this format provides us with the most flexibility when tailoring things on the Power BI side of things. But what if you wanted to perform some ranking on the data, based on a distinct category value – for example, ranking each of the Browser values in popularity order, based on each visitor to the website? While it is certainly possible to do this via a Stream Analytics query, you would end up having to group the data, thereby reducing the wider usage that the dataset could accommodate. Fortunately, thanks to the fact that we can create DAX Measures, it is possible to overcome this to generate a ranking per category and then display the most popular browser as part of a Card visualisation. We first need to create the following Measure within Power BI Desktop:

Browser Ranking = RANKX(
                        ALLSELECTED(PowerBIRequestsOutput[browser]), 
                        CALCULATE(
                                DISTINCTCOUNT(
                                    PowerBIRequestsOutput[anonymousid]
                                    )
                                ),,,Dense
                            )

We can confirm this works as expected by dropping a quick table visualisation in and verifying that each Browser is being ranked correctly, based on the count of the anonymousid field:

So far, so good šŸ™‚ And this is potentially a visualisation that has a good usage case solely on its own; but, with an additional DAX Measure, we can return the highest ranked value above, IE, via the following Measure:

Most Used Browser = TOPN(1, FILTER(VALUES(PowerBIRequestsOutput[browser]), [Browser Ranking] = 1))

Now, the thing to mention here is that the above does not explicitly handle ties in any sophisticated way; therefore, there is no guarantee over which value will display in the event of a draw for the top ranking. Nevertheless, it is encouraging to know that DAX provides us with the types of capabilities we need when we find ourselves unable to do the kind of manipulation we would want to, either via a SQL query or Power Query manipulation.

For the past 13 weeks on the blog, I have delivered a series of posts concerning Microsoft Exam 70-778, specifically focused towards providing a set of detailed revision notes that cover the broad array of Power BI features assessed as part of the exam. To round things off, today’s blog will bridge together everything I have discussed thus far in the series; with the hopeĀ being that this post can be a single reference point for those who have not been following the series to date.

Microsoft Exam 70-778 Overview

The exam, with its full title Analyzing and Visualizing Data with Microsoft Power BI, is targeted towards Business Intelligence (BI) and data professionals who are looking to validate their skills in working with Power BI. The exam is a necessary component, alongside Exam 70-779: Analyzing and Visualizing Data with Microsoft Excel, in attaining the Microsoft Certified Solutions Associate (MCSA) certification in BI Reporting. Successful candidates can then (optionally) pass an additional “elective” exam to gain the Microsoft Certified Solutions Expert (MCSE) certification in Data Management and Analytics.

Skills Measured in the Exam

The skills measured are outlined below, alongside links to the relevant posts from the series and the list of essential points to remember:

Consuming and Transforming Data By Using Power BI Desktop

Connect to data sources.
Skills Measured

May include: Connect to databases, files, folders; import from Excel; connect to SQL Azure, Big Data, SQL Server Analysis Services (SSAS)

Revision Notes

Exam 70-778 Revision Notes: Importing from Data Sources

Key Takeaways
  • Power BI supports a broad range of database systems, flat file, folder, application and custom data sources. While it is impossible to memorise each data source, you should at least broadly familiarise yourself with the different types at our disposal.
  • A crucial decision for many data sources relates to the choice of either Importing a data source in its entirety or in taking advantage of DirectQuery functionality instead (if available). Both routes have their own defined set of benefits and disadvantages. DirectQuery is worth consideration if there is a need to keep data regularly refreshed and you have no requirement to work with multiple data sources as part of your solution.
  • Live Connection is a specific data connectivity option available for SQL Server Analysis Services. It behaves similarly to DirectQuery.
  • It is possible to import an existing Excel BI solution into Power BI with minimal effort, alongside the ability to import standard worksheet data in the same manner as other flat file types.
Perform transformations
Skills Measured

May include: Design and implement basic and advanced transformations; apply business rules; change data format to support visualization

Revision Notes

Exam 70-778 Revision Notes: Performing Data Transformations

Key Takeaways
  • The Power Query M formula language is used to perform transformations to data once loaded into Power BI. Although it is possible to do this via code, Power BI allows us to define all of our required data changes from within the interface, without the need to write a single line of code.
  • Each data source connected to represents itself as a Query within Power BI. There are many options at your disposal when working with Queries, such as renaming, merging, duplication and the ability to disable or reference as part of other Queries.
  • There are wide-range of column transformations that can be applied, which are too numerous to mention. The Transform tab provides the best means of seeing what is available, with options ranging from formatting through to grouping and pivoting/unpivoting.
  • New columns are addable via the Add Column tab. You can choose to base new columns on calculations, conditional logic, other column values or as a defined list of ascending numbers, which may be useful for indexing purposes.
  • It is possible to merge or append queries together to suit your specific requirements. Merging involves the horizontal combination of Queries, whereas appending represents a vertical combination.
  • Parameters can be used to help optimise any complex filtering requirements.
  • Where possible, Power Query will attempt to use the most optimal query for your data source, based on the transformation steps you define. This action is known as Query Folding and, in most cases, SQL-derived data sources will support this option by default.
Cleanse data
Skills Measured

May include: Manage incomplete data; meet data quality requirements

Revision Notes

Exam 70-778 Revision Notes: Cleansing Data

Key Takeaways
  • Data can be filtered directly within Power Query, using Excel-like functionality to assist you in only returning the most relevant data in your queries. The data type of each field plays a particularly important part of this, as only specific filter options will be at your disposal if, for example, you are working with numeric data.
  • From a data quality perspective, you typically will need to handle column values that contain one of two possible value types:
    • Errors: This will usually occur as a result of a calculated column field not working correctly. The best solution will always be to address any issues with your calculated column, such as by using a conditional statement to return a default value.
    • Blanks/NULLs: A common symptom when working with SQL derived data sources, your real problems with blank values start to appear when you attempt to implement DAX custom columns/Measures outside of the Power Query Editor. It is, therefore, recommended that these are dealt with via a Replace action, depending on your fields data types. For example, a number field with blank/NULL values should be replaced with 0.
  • The Remove Rows option(s) can act as a quick way of getting rid of any Error or Blank/NULL rows and can also be utilised further to remove duplicates or a range of rows. In most cases, you will have similar options available to you with Keep Rows instead.
  • There are a variety of formatting options available to us when working with text/string data types. These range from fixing capitalisation issues in data, through to removing whitespace/non-printable character sets and even the ability to prepend/append a new value.

Modeling and Visualizing Data

Create and optimize data models.
Skills Measured

May include: Manage relationships; optimize models for reporting; manually type in data; use Power Query

Revision Notes

Exam 70-778 Revision Notes: Create and Optimise Data Models

Key Takeaways
  • Relationships form the cornerstone of ensuring the long-term viability and scalability of a large data model. Assuming you are working with well-built out, existing data sources, Power BI will automatically detect and create Relationships for you. In situations where more granular control is required, these Relationships can be specified manually if needed. It is worth keeping in mind the following important features of Relationships:
    • They support one-to-one (1:N), one-to-many (1:N) and many-to-one (N:1) cardinality, with many-to-many (N:N) currently in preview.
    • Filter directions can be specified either one way or bi-directionally.
    • Only one relationship can be active on a table at any given time.
  • It is possible to sort columns using more highly tailored custom logic via the Sort By Column feature. The most common requirement for this generally involves the sorting of Month Names in date order but can be extended to cover other scenarios if required. To implement, you should ensure that your data has a numbered column to indicate the preferred sort order.
  • Moving outside of the Power Query Editor presents us with more flexibility when it comes to formatting data to suit particular styling or locale requirements. While the majority of this functionality provides date/time and currency formatting options, for the most part, it is also possible to categorise data based on Location, the type of URL it is or on whether or not it represents a Barcode value; these options can assist Power BI when rendering certain types of visualizations.
  • There may be ad-hoc requirements to add manually defined data into Power BI – for example, a list of values that need linking to a Slicer control. The Enter Data button is the “no-code” route to achieving this and supports the ability to copy & paste data from external sources. For more advanced scenarios, you also have at your disposal a range of M code functionality to create Lists, Records and Tables, which can be extended further as required.
Create calculated columns, calculated tables, and measures
Skills Measured

May include: Create DAX formulas for calculated columns, calculated tables, and measures; Use What If parameters

Revision Notes

Exam 70-778 Revision Notes: Using DAX for Calculated Columns

Key Takeaways
  • DAX is the primary formula language when working with datasets outside of Power Query. It includes, to date, more than 200 different types of functions that can assist in all sorts of data modelling.
  • An important concept to grasp within DAX is context and, specifically, row context (formulas that calculate a result for each row in a dataset) and filter context (formulas that automatically apply any filtering carried out at report level).
  • The sheer amount of DAX functions available makes it impossible to master and remember all of them, particularly when it comes to the exam. Your learning should, therefore, focus on learning the general syntax of DAX and the general types of functions available (aggregation, date/time etc.)
  • There are three principal means of utilising DAX with Power BI:
    • As Measures: These typically present a scalar value of some description, often an aggregation or a result of a complex formula. Using them in association with a Card visualization type is recommended, but this is not a strict requirement.
    • As Calculated Columns: Similar to the options available within Power Query, Calculated Columns provide a dynamic and versatile means of adding new columns onto your datasets. Compared with the options available within Power Query and the complexity of the M language, DAX Calculated Columns might represent a more straightforward means of adding custom columns onto your datasets.
    • As Calculated Tables: A powerful feature, mainly when used in conjunction with Calculated Columns, you have the ability here to create entirely new datasets within the model. These will typically derive from any existing datasets you have brought in from Power Query, but you also have functionality here to create Date tables, sequence numbers and manually defined datasets as well.
  • What-if Parameters provide of means of testing DAX formulas, as well as allowing report users to perform predictive adjustments that can affect multiple visualizations on a report.
Measure performance by using KPIs, gauges and cards.
Skills Measured

May include: calculate the actual; calculate the target; calculate actual to target; configure values for gauges; use the format settings to manually set values

Revision Notes

Exam 70-778 Revision Notes: Utilising KPIs with Gauge Visualisations

Key Takeaways
  • There are two principle visualization types available within Power BI to help track actual-to-target progress – KPIs and Gauges.
  • KPIs provide a more visually unique means of a binary success/fail determination when tracking towards a target. It is also possible to use KPI’s to track variance over time via the Trend axis. The Indicator will typically be the result of some form of aggregation or Measure.
  • Gauges provide a less visually distinctive, but non-binary, mechanism of viewing progress towards a target. Gauges support more potential field well values when compared with KPIs, nearly all of which are optional in some way. You can also manually define some of these values, for situations where your data model does not contain the required information.
  • All visualizations within Power BI are modifiable from a display or formatting perspective. The same basic options will generally be supported – such as changing a font type or background colour – with more specific configuration properties available per unique visualization type. For example, a KPI visualization can be customised to hide the background Trend Axis entirely. All of these options are designed to give developers greater control over the look and feel of their reports and to mirror them as closely as possible to any potential branding requirement.
  • When building out a solution designed to monitor progress within Power BI, the steps involved will typically be more in-depth than merely creating a new visualization. In most cases, there will be a requirement to bring together a lot of the other skills that have been discussed previously within this series – such as creating DAX formulas, modifying data within Power Query or bringing together different data sources into a single model. It is essential, therefore, not to underestimate the amount of time and effort involved in creating a practical solution that takes advantage of KPIs or Gauges.
Create hierarchies
Skills Measured

May include: Create date hierarchies; create hierarchies based on business needs; add columns to tables to support desired hierarchy

Revision Notes

Exam 70-778 Revision Notes: Creating Hierarchies

Key Takeaways
  • Hierarchies within Power BI provide a means of logically categorising data into an order of preference or precedence, providing greater flexibility to Power BI report users when they interact with visualizations.
  • Date Hierarchies are created and managed automatically by Power BI for each Date or Date/Time field defined within your model. These automatically create fields that contain the Year, Quarter, Month & Day values from the respective date fields. These fields can then be utilised as part of a Table visualization or within a DAX formula. Date Hierarchies can also be completely disabled if required.
  • Custom (or User-Defined) Hierarchies need to be created manually and provide additional customisation options when compared to Date Hierarchies, such as the number of fields they contain, the order and its name. A Custom Hierarchy will typically make use of one of several Parent/Child DAX functions, such as PATH or PATHITEM.
  • Including a hierarchy as part of a chart visualization, such as a Pie chart or Donut chart, opens up other drill-down capabilities around your data. Indicated by the additional arrow icons included at the top of the visualization, they provide the means for users to interrogate data points that interest them the most straightforwardly.
Create and format interactive visualizations.
Skills Measured

May include: Select a visualization type; configure page layout and formatting; configure interactions between visual; configure duplicate pages; handle categories that have no data; configure default summarization and data category of columns; position, align, and sort visuals; enable and integrate R visuals; format measures; Use bookmarks and themes for reports

Revision Notes

Exam 70-778 Revision Notes: Create and Format Interactive Visualizations

Key Takeaways
  • Power BI delivers, out of the box, a range of different visualizations that cater towards most (if not all) reporting requirements. Should you find yourself in need of additional visualizations, then Microsoft AppSource is your go-to destination for finding visualizations developed by others. If you have experience working with either Node.js or R, then these can be used to build bespoke visualizationsĀ also.
  • When first developing a report, you should be able to match a requirement for a specific visualization type, to ensure that you are delivering a solution that is both meaningful and useful. From an exam perspective, this becomes a more critical consideration, and you should be prepared to suggest the most optimal visualization to use when given a specific scenario.
  • After adding visualization’s to your report, you have additional options available to customise them further. For example, you can specify a preferred sorting order for your data, override any summarizations used and move/align your visual on the report page.
  • By default, visualizations in Power BI are designed to change automatically, based on how users interact with the report. All of these options are controllable via the Edit interactions button, allowing you to specify your preferred cross-filtering and cross-highlighting conditions.
  • There is a range of report page customisation options available to developers. It is possible to resize a page to any possible height/width, allowing you to optimise your report for specific devices.Ā Also, you can modify the colour of a page (or its wallpaper) or add an image instead. Pages can also be renamed, reordered or duplicated.
  • Measures can be formatted in the same way as calculated columns, meaning you can specify a data type or, for numerics, modify the number of decimal places.
  • Bookmarks allow developers to set up “checkpoints” within a report, based on how a report page has been filtered. These can then be used to automatically navigate the user through a report, applying these filtering steps automatically. This feature can help transform your report into an interactive story.
  • Visualizations will automatically inherit their various colour properties from the currently selected report theme. Although these can be modified granularly, the fastest and most consistent way of making these changes en masse is to change the Theme. Power BI includes some Themes out of the box, but you also have the option of building your own using a custom JSON file; this can then be imported into different reports, providing a portable means of enforcing a particular branding requirement.
Manage custom reporting solutions
Skills Measured
  • May include: Configure and access Microsoft Power BI Embedded; enable developers to create and edit reports through custom applications; enable developers to embed reports in applications; use the Power BI API to push data into a Power BI dataset; enable developers to create custom visuals
Revision Notes

Exam 70-778 Revision Notes: Managing Custom Reporting Solutions

Key Takeaways
  • Power BI Embedded is an Azure hosted offering that allows you add Power BI Report content into bespoke applications. This deployment option can be incredibly useful if you wish to make available your Power BI solution to users outside of your organisation or if you have an existing, bespoke application system that can benefit from utilising Power BI content. An Azure subscription is required to begin working with Power BI Embedded and you are billed based on node size, not individual user licenses. All Power BI content requires publishing to the online service before its contents become available for Power BI Embedded to access. Report developers will, therefore, need granting a Power BI Professional license to carry out these activities.
  • The Power BI API grants access to developers to perform automation or administrative actions programmatically against the Power BI Online service. Utilising a REST API, developers can determine the optimal programming language of choice to interact with the API, allowing them to streamline the deployment of Reports or Dashboards to the Power BI service or leverage additional functionality when utilising Power BI Embedded. The API can also cater to specific data load requirements, although more complex needs in this area would require addressing via alternate means (SSIS, Azure Data Factory etc.)
  • Developers can add their own bespoke visualizations to a Power BI Report by either developing them using Node.js or using the R language. The first of these options facilitate a more streamlined deployment mechanism and allows developers to add their visualizations to AppSource, whereas the second option may be more useful for complex visualization types with an analytical or statistical function.

Configure Dashboards, Reports and Apps in the Power BI Service

Access on-premises data
Skills Measured

May include: Connect to a data source by using a data gateway;publish reports to the Power BI service from Power BI Desktop; edit Power BI Service reports by using Power BI desktop

Revision Notes

Exam 70-778 Revision Notes: Report Publishing, On-Premise Gateway & Creating Dashboards

Key Takeaways
  • The Power BI On-Premise Gateway provides a streamlined route to working with non-cloud data sources within Power BI, Microsoft Flow and PowerApps. As a lightweight and easy-to-configure client application, it supports a wide variety of data sources, making them accessible as if they were in the cloud. Once set up, corresponding Data Sources are then made available for configuration and for leveraging as part of any Power BI Dataset.
  • Reports can be published into Power BI Online, meaning that they become accessible online and to a broader group of users, without requiring access to Power BI Desktop. Reports need deploying into a Workspace, which can be created manually or derived from an Office 365 Group. Each Report contains a corresponding Dataset, where all queries defined within Power BI Desktop exist.
  • Reports that already exist on Power BI Online can be updated by just publishing a new version of the Report from Power BI Desktop. It is also possible to modify Reports from directly within the browser and by downloading a copy of the .pbix Report file as well, which can then be altered and re-published.
Configure a dashboard
Skills Measured

May include: Add text and images; filter dashboards; dashboard settings; customize the URL and title; enable natural language queries

Revision Notes

Exam 70-778 Revision Notes: Report Publishing, On-Premise Gateway & Creating Dashboards

Key Takeaways
  • Dashboards provide a means of grouping together various content as tiles, designed for at-a-glance analysis and optimal end-user experience.
  • The list of content that can be pinned to a Dashboard includes:
    • Visualizations
    • Web content
    • Images
    • Text boxes
    • Videos
    • Custom streaming data
  • Pinned content can be re-arranged on Dashboard via drag and drop functionality. It is also possible to resize tiles to any given height/width.
  • Within the settings of a Dashboard, it is possible to enable/disable features such as natural language queries (Q&A’s) and Notes.
  • Some features of a Dashboard are only available if you have a Power BI Professional subscription, such as sharing and email subscriptions.

 

Publish and embed reports
Skills Measured

May include: Publish to web; publish to Microsoft SharePoint; publish reports to a Power BI Report Server

Revision Notes

Exam 70-778 Revision Notes: Publish and Embed Reports

Key Takeaways
  • The Publish to web option allows for non-licensed, external users to view a Power BI Report in its entirety. A URL and IFrame embed code can be generated for this at any time within the portal and then dropped into virtually any website. Although you will lose some functionality when deploying a Report out in this manner, you can expect that users will be able to perform most types of interactions with visualizations, Report pages and other components, as if they were accessing the Report through Power BI Online. In some cases, you may be unable to use the Publish to web option if your Report uses certain kinds of features, such as R Visuals or row-level security. You must also take into account any privacy or data protection concerns, as Reports deployed out in this manner will be publically accessible; where this is an issue, the Embed option is available as a secure alternative.
  • There are three steps involved if you wish to add a Report to SharePoint. First, you must generate the unique SharePoint embed URL within Power BI. Secondly, you then need to add on the dedicated control for this feature on your target SharePoint page and configure the relevant display options. Finally, you then need to ensure that all SharePoint users have been granted access to the Report, either at a Workspace level (recommended option) or by having the Report shared with them. By implication, in this scenario, all SharePoint users would have to have at least a Power BI Professional license to take full advantage of this functionality.
  • Publishing a Report to Power BI Report Server is mostly the same as if you were to do the same with the online version of the product. Instead of selecting a Workspace to add the Report to you, specify the name of the Report Server folder where the Report will reside. From a development standpoint, the dedicated Power BI Desktop for Power BI Report Server must be used and may differ in functionality from the “normal” version of the tool. There is also no option to edit a report from within Power BI Report Server like you can through the online version.
Configure security for dashboards, reports and apps.
Skills Measured

May include: Create a security group by using the Admin Portal; configure access to dashboards and app workspaces; configure the export and sharing setting of the tenant; configure Row-Level Security

Revision Notes

Exam 70-778 Revision Notes: Securing Power BI Dashboards, Reports and Apps

Key Takeaways
  • Workspaces act as a container for the various components that form a Power BI Reporting solution. Within a Workspace, you will find all of the Dashboards, Reports, Workbooks and Datasets that developers have published content to. Each User has a Workspace created for them in Power BI when they first access the service. Additional Workspaces can be added through Office 365 Groups or by installing a Power BI App from AppSource. Dashboards and Reports created within your a Users Workspace are shareable to other Users, provided that your account has a Power BI Professional license assigned to it.
  • To help manage permissions to Dashboards/Reports in a more efficient manner, Administrators can create Security Groups on the same Office 365 Tenant where Power BI Online resides. These can contain multiple groups of Users, allowing administrators to minimise the amount of effort involved in managing Dashboard/Report access. Most crucially, this will also enable Users that do not have an Exchange Online mailbox to access Dashboards/Reports when they are shared out in this manner.
  • Administrators have a whole host of options available to them within the Tenant settings area of the Admin Portal. These include, but are not limited to:
    • Export and Sharing Settings
    • Enable/Disable Content Sharing
    • Enable/Disable Publish To Web
    • Enable/Disable Export Reports as PowerPoint Presentations
    • Enable/Disable Print Dashboards and Reports
    • Content Pack and App Settings
    • Integration Settings
    • Custom Visuals Settings
    • R Visuals Settings
    • Audit and Usage Settings
    • Dashboard Settings
    • Developer Settings
  • All of these settings can be enabled for a specific security group, the entire organisation (excepting specific security groups) or allowed for particular security groups, excluding all others in the organisation.
  • Row-Level Security (RLS) allows report developers to restrict data, based on Roles. Row-level DAX evaluation formulas are used to achieve this, which filters the data that is returned, depending on a TRUE/FALSE logic test. To utilise the feature, you must define both the Roles and DAX formulas for each query within your data model. Then, after deploying your Report to Power BI Online, you then assign Users or Security Groups to the Role(s) created within Power BI Desktop. It is possible to view the effect of a Role at any time, within Power BI Desktop or Online, via the View As Role functionality. With the wide-array of DAX formulas available, including specific ones that return the details for the current user accessing a Report, it is possible to define very granular filtering within a Power BI report, to suit particular security or access models.
Configure apps and apps workspaces.
Skills Measured

May include: Create and configure an app workspace; publish an app; update a published app; package dashboards and reports as apps

Revision Notes

Exam 70-778 Revision Notes: Working with Apps and App Workspaces

Key Takeaways
  • Workspaces act as a container for the various components that form a Power BI Reporting solution. Within a Workspace, you will find all of the Dashboards, Reports, Workbooks and Datasets that developers have published content to. Each User has a Workspace created for them in Power BI when they first access the service. It is also possible to create additional Workspaces, either through the Power BI Online interface or by creating an Office 365 Group. A new experience for creating Workspaces is currently in preview which, once released, would negate the need for each Workspace to have an associated Office 365 Group.
  • When creating a Workspace, you can define various settings such as the type of access each user has (read-only or ability to modify its content), its members and whether it requires assignment to a Power BI Premium node. It is not possible to change the access type for a Workspace after creation, but you can freely change its name or modify its membership at any time.
  • The contents of a Workspace can be published as an App, enabling you to expose your solution to a broader audience within or outside your organisation. Once published, users navigate to the Power BI AppSource store for their tenant, which lists all Apps available for installation. Once installed, they will then become visible from within the Apps area of the application. You can update content within an App at any time by republishing its corresponding Workspace. It is also possible to define individual properties within an App, such as its description, access rights and landing page. To install and use Apps, the user in question must have a Power BI Professional license.

Additional Preperation Resources

The official Microsoft exam reference book is a helpful learning aid for this exam, particularly given that it includes numerous exercises that you can work through to familiarise yourself with different Power BI functionality. There is also an online course available on the edX website which, despite not covering the whole exam syllabus, does provide a useful visual aid and includes a lot of the features you are expected to know for the exam. Finally, nothing beats actually working with the product itself and trying out the various features yourself. Power BI Desktop is a free download and, with access to one of the sample databases provided by Microsoft, you can very quickly provision an environment on your own home computer to enable you to experience everything that Power BI has to offer.

Exams are always a nightmarish experience, both when preparing for them and when you are sat there in the test centre. I hope that this post, and this whole series, proves to be useful in helping with your exam preparation and getting you ready to pass the exam with flying colours šŸ™‚

Welcome to the twelfth and penultimate post in my blog series concerning Microsoft Exam 70-778, where I hope to provide a revision tool for those planning to take the exam or a learning aid for those looking to increase their Power BI knowledge. We’re on the home stretch now and, after reviewing last week the various options available to publish Power BI Reports both online and on-premise, we now take a deep dive into some vital security concepts as part of the Configure security for dashboards, reports and apps theme, which covers the following skill areas:

Create a security group by using the Admin Portal; configure access to dashboards and app workspaces; configure the export and sharing setting of the tenant; configure Row-Level Security

Before exploring these topics further, however, it is essential to outline a concept that this series has continually skated around – Power BI Workspaces.

Workspace Overview

We’ve seen so far in the series how it is possible to deploy Power BI Desktop Reports into Power BI Online. As part of this process, you must define a Workspace where your Reports and Datasets will appear after publishing. There are three types of Workspaces:

  • My Workspace – Each user, by default, will have a personal Workspace, which cannot be deleted or changed.
  • Office 365 Group Workspace
  • App Workspace

Workspaces are, for the most part, a logical grouping of all the components that you need to start building out a BI solution. They are worked with from within Power BI Online only (meaning that they do not exist as part of Power BI Report Server) and can be interacted with from the left-hand pane within Power BI Online:

As indicated above, each user’s Workspace can contain:

  • Dashboards – These are created within the Power BI service, as we saw a fortnight ago.
  • Reports – These are built out in Power BI Desktop or uploaded directly into Power BI Online from a .pbix file.
  • Workbooks – These will show a list of Excel workbooks that have been uploaded into Power BI, allowing you to leverage an existing solution built out using Excel PivotTables/PivotCharts almost immediately through Power BI. For this exam, it is not something you need to worry about necessarily, but be aware this topic does crop up within Exam 70-779.
  • Datasets – Contains a list of all data models uploaded/created for Power BI Reports or Workbooks.

It is possible to share out Dashboards and Reports to other Users/Security Groups, and we will see how this can be done with the example later on in this post. One consideration to bear in mind is that, when sharing Reports, this does not share out any Dashboards that reference it. Content shared to you will become visible within the Shared with me tab on Power BI Online:

Next week’s post will go into further detail on how to create and manage Workspaces, and how to handle access to App Workspaces.

Office 365 Security Groups

Those who have experience administrating on-premise Active Directory (AD) domains will have full familiarity with the concept of Security Groups – logical containers of Users that can then be assigned file/folder privileges, group policy objects and access to other principals on the domain. Given that Power BI uses Azure Active Directory (AAD) as its identity provider, the same kind of concepts come into play when you start to determine how to manage access to Power BI Dashboards, Reports and Datasets to specific groups of Users. Office 365 Security Groups are virtually identical to their on-premise AD equivalent; the primary difference being is that Administrators must create them from within the Office Microsoft 365 Admin Center. It is also possible to add them through Microsoft Azure as well, so your choice here really comes down to preference. In either case, you must ensure that you have the relevant administrator privileges on your AAD tenant to create and manage them. Once created and defined with your required list of Users, they then become available as a shareable object within Power BI Online.

In the example towards the end of this post, we will walk through how to create a Security Group and how this can then be used to share out a Dashboard.

Managing Export and Sharing Settings

With the introduction of GDPR last year, data privacy concerns remain a paramount concern for organisations. These concerns can often come into conflict with new functionality that technology solutions can offer us such as, for example, the ability to export a Power BI Report as a PowerPoint presentation. To help with these considerations and in line with Microsoft’s overall commitments from a GDPR standpoint, Power BI Online provides several options that allow you to granularly define various actions that Users can and cannot do, such as using custom visuals in reports, accessing audit/usage information and the ability to use preview features, such as dataflows. The list of settings most relevant to data sharing can be found under the Export and sharing settings section on the Admin Portal -> Tenant settings area of Power BI Online:

Each of the listed features can be enabled or disabled globally on the Office 365 tenant. Alternatively, by utilising Security Groups, you can grant or curtail specific functionality to a group/department within an organisation. You have no option to specify individual User access as part of this, so it becomes a requirement to have your required Security Groups defined within Office 365 before you can start working with this feature.

Row-Level Security

Granting global allow/deny privileges at a Report level may not be sufficient for specific business requirements. It could be, for example, that a single Sales report is in place for both junior and senior sales professionals, and there is a need to only present data that is most relevant to their role. Or, for example, there is a need to show data that has the most relevance for an individual’s particular geographic region. In these situations and, to avoid a scenario where you would have to define separate queries to segregate this data appropriately, Row-Level Security (or RLS) becomes a significant asset. It allows you to set Roles linked to DAX expressions, which tell Power BI which data to show to a particular group of Users.

There are two steps involved as part of implementing RLS. First, you must create a Role that defines the list of privileges for one or multiple Users. This step can be achieved by navigating to the Modeling tab within Power BI Desktop and selecting the Manage Roles button, which will open the appropriate dialog window:

Next, you must define a DAX Expression for each table that requires filtering as part of the Role. These can be set up for as many Tables as you like, but the critical thing to remember is that the DAX Expression must conform to a TRUE/FALSE equality check. The example below – whether it will either be TRUE or FALSE that the TotalSales value on a row will be greater than or equal to 500 – meets this requirement:

With the Role defined, it is then possible to test it locally from within Power BI Desktop by using the View as Roles button to select your corresponding Role:

With everything built out and working with Power BI Desktop, the second step is to publish your Report to Power BI Online and then assign the Role to Users or a Security Group by navigating to the Dataset in question:

It is also possible to use the Test as role feature within Power BI Online, which behaves identically to its Desktop client equivalent:

To help leverage additional functionality out of RLS, Microsoft provides the following two DAX functions:

  • USERNAME() – Returns the domain name of the User accessing the Report. For Desktop Reports, this will typically be in the format <Domain>\<User Name>; when viewing the Report online, the value rendered instead will either be the user’s email address or onmicrosoft.com account name.
  • USERPRINCIPALNAME() – Returns the User Principal Name (UPN) of the User accessing the Report. The UPN will almost always be the user’s email address or, in some cases for Power BI Online, their onmicrosoft.com user account name.

By using these functions in tandem with IF DAX constructs, you have the additional capability to restrict access to specific data, based on user account names. All in all, RLS is a powerful feature to have at your disposal but, as highlighted in last week’s post, you should be aware of its limitations. RLS is incompatible when there is a need to Publish to web a report and the feature is also not available if you are querying a SQL Server Analysis Services data source via a live connection.

Example: Sharing a Power BI Dashboard with a Security Group

The steps that follow will show how to create an Office 365 Security Group and then share out a Dashboard to it from within Power BI. To complete the steps outlined, you should ensure that you are assigned either the Global administrator or User management administrator role in Office 365 and that your user account has a Power BI Professional license:

  1. Navigate to the Admin Center within Office 365, expand the Groups tab on the left-hand pane and select Groups:
  2. The main window should refresh, displaying the list of Groups setup on the AAD tenant. Select the Add a group button:
  3. Define the settings as indicated in the below screenshot, making sure that the Type selected is Security, and press Add:
  4. You will then receive confirmation that the Security Group was added successfully to your tenant:
  5. With the main Groups window, select the new Security Group and then click the Edit button on the right-hand details pane:
  6. Then, select the Add members button to add in the required list of Users:
  1. Press Save to commit any changes:
  2. Navigate back to Power BI Online and to the Dashboard that needs sharing. Select the Share button at the top right of the screen:
  3. Within the Share dashboard pane, begin typing in the name of the Security Group created in the previous steps. Power BI will automatically detect and auto-complete the name of the group for you. Before pressing the Share button, you can also include a custom message to recipients that will be sent via an email and also toggle whether they will also be able to Share the dashboard themselves. A URL link generates at this point as well, allowing you to copy/paste this into an email, IM message etc.:
  4. Once the Dashboard is Shared, you can then navigate to the Access tab to review the list of Users/Security Groups that have access to your Dashboard. It is also possible to modify their access levels or remove access entirely by clicking on the ellipses button next to each Name:

Key Takeaways

  • Workspaces act as a container for the various components that form a Power BI Reporting solution. Within a Workspace, you will find all of the Dashboards, Reports, Workbooks and Datasets that developers have published content to. Each User has a Workspace created for them in Power BI when they first access the service. Additional Workspaces can be added through Office 365 Groups or by installing a Power BI App from AppSource. Dashboards and Reports created within your a Users Workspace are shareable to other Users, provided that your account has a Power BI Professional license assigned to it.
  • To help manage permissions to Dashboards/Reports in a more efficient manner, Administrators can create Security Groups on the same Office 365 Tenant where Power BI Online resides. These can contain multiple groups of Users, allowing administrators to minimise the amount of effort involved in managing Dashboard/Report access. Most crucially, this will also enable Users that do not have an Exchange Online mailbox to access Dashboards/Reports when they are shared out in this manner.
  • Administrators have a whole host of options available to them within the Tenant settings area of the Admin Portal. These include, but are not limited to:
    • Export and Sharing Settings
    • Enable/Disable Content Sharing
    • Enable/Disable Publish To Web
    • Enable/Disable Export Reports as PowerPoint Presentations
    • Enable/Disable Print Dashboards and Reports
    • Content Pack and App Settings
    • Integration Settings
    • Custom Visuals Settings
    • R Visuals Settings
    • Audit and Usage Settings
    • Dashboard Settings
    • Developer Settings
  • All of these settings can be enabled for a specific security group, the entire organisation (excepting specific security groups) or allowed for particular security groups, excluding all others in the organisation.
  • Row-Level Security (RLS) allows report developers to restrict data, based on Roles. Row-level DAX evaluation formulas are used to achieve this, which filters the data that is returned, depending on a TRUE/FALSE logic test. To utilise the feature, you must define both the Roles and DAX formulas for each query within your data model. Then, after deploying your Report to Power BI Online, you then assign Users or Security Groups to the Role(s) created within Power BI Desktop. It is possible to view the effect of a Role at any time, within Power BI Desktop or Online, via the View As Role functionality. With the wide-array of DAX formulas available, including specific ones that return the details for the current user accessing a Report, it is possible to define very granular filtering within a Power BI report, to suit particular security or access models.

Putting some thought into Power BI’s security and access components early on when developing your solution will allow you to best take advantage of features such as RLS, which then benefit further when utilised alongside the other functionality described this week. The final post in the series next week will provide a more detailed description of Workspaces and how these can be used to create Apps for both internal and external consumption.

The New Year is almost upon us, meaning its time to put in place some resolutions for the year ahead. I can think of no better commitment then to learn more about Power BI in 2019, which is hopefully the reason why you are reading this right now šŸ™‚ . Welcome to the eighth post in my series concerning Microsoft Exam 70-778, where I hope to provide a learning/revision tool for anyone who is taking the exam or looking to increase their Power BI expertise. Last week, we investigated how to manage Key Performance Indicator (KPI) reporting using Power BI. We now move into another topic area that is also tied closely to visualizations – Create hierarchies. The related skills for this exam area are:

Create date hierarchies; create hierarchies based on business needs; add columns to tables to support desired hierarchy

In the sections that follow, I will provide an overview of the two different types of Hierarchies configurable within Power BI, before then providing a step-by-step guide on how to create one. As with previous posts in this series, this subject does bring together some other skill areas, such as importing data with Power Query and using DAX calculated columns. Knowledge of these topics will hold you in good stead when starting with hierarchies.

What is a Hierarchy?

Hierarchies form the cornerstone of a broad aspect of human existence, which makes it natural they are a common theme when it comes to Business Intelligence (BI) solutions. A hierarchy is definable as a logical, often visual, representation of an order of precedence. Hierarchies, in strict Power BI terms, do not differ much from this general definition; they allow developers to order data by preference, priority or anything in between. When configured and used in isolation, they offer minimal benefit to Power BI report consumers. They start to become really valuable when utilised alongside visualizations, providing an additional interaction point for key data points and allowing report users to tailor a visualization to suit their needs. Some potential usage scenarios for hierarchical data may include:

  • Providing top-level and subcategory classifications for product records.
  • Modelling a business reporting line hierarchy, from CEO down to Developer.
  • Splitting sale date by quarter, year or even month.

Hierarchies come in two flavours within Power BI – Date Hierarchies and Custom (or User Defined) Hierarchies. The next two sections delve deeper into the inner workings of each.

Date Hierarchies

Date Hierarchies are best described as a logical breakdown of the constituent components of a date value, based on four different levels:

  • Year
  • Quarter
  • Month
  • Day

For each field that contains a Date Hierarchy, the appropriate value for each of the above is exposed out for utilisation across Power BI Desktop. So, for example, the underlying hierarchy values for the 3rd March 2017 would be:

  • Year: 2017
  • Quarter: Qtr 1
  • Month: March
  • Day: 3

All columns with a data type of Date or Date/Time will have a Date Hierarchy created for them automatically. The hierarchy will then become accessible for use in the following areas of Power BI Desktop:

  • When building out formulas using DAX. For example, the screenshot below shows how it is possible to access the hierarchy field values listed above from the Date/Time field LastEditedWhen:
  • When working with a Table visualization. Adding a Date or Date/Time column into the Values well will automatically create a table containing all of the hierarchy fields. An example of how this looks for the LastEditedWhen field is seen in the image below:

It is possible to disable the automatic creation of Date Hierarchies within the File -> Options area of Power BI Desktop, by toggling the Auto Date/Time option. Take care when toggling this though, as doing so will remove any existing Date Hierarchies within your model:

This fact is confirmed when returning to the Table created using the LastEditedWhen field, which automatically reverts to the base column value when theĀ Auto Date/Time option is disabled:

Custom Hierarchies

For more bespoke requirements, a Custom Hierarchy affords the same kind of functionality discussed in the previous section. They can be created from the right-hand Fields pane by selecting a field within a Power BI table and choosing the New hierarchy option:

Once established, you can then:

  • Rename the hierarchy. By default, it will be named using the convention <Field Name> Hierarchy.
  • Include additional fields by dragging and dropping them into the hierarchy.
  • Reorder the hierarchy, by dragging and dropping the fields into your preferred order, from top to bottom.
  • Delete the hierarchy through right-clicking it and selecting the Delete option. All fields included in the Hierarchy will remain as part of the underlying query.

A Custom Hierarchy typically relies on a self-relationship that a query might have on itself. An excellent example of this, already alluded to, is an Employee table, where an individuals Manager is trackable via a ManagerID column, that resolves back to an EmployeeID record. In these cases, there are several DAX functions available that will assist in getting custom columns set up to support your hierarchy, described collectively as Parent and Child Functions. Usage of these functions is essential when building out Hierarchies involving parent/child relationships.

TheĀ exercise at the end of this post will go through the detailed steps involved in creating a Custom Hierarchy.

Using Hierarchies with Visualizations

A good reason to include hierarchies as part of your Power Bi Reports is the options they unlock from a data drill-down perspective. We’ve seen already the behaviour Date Hierarchies adopt when using the Table visualization, which offers nothing in this respect. Other visualization types support, by comparison, far richer options for “homing in” on a particular piece of data, epitomised by the following buttons that appear at the top of the supported visualization:

In order, from left to right, these let you:

  • Drill up your data one level in the hierarchy.
  • Enable the Click to turn on Drill Down feature, allowing you to click on any part of a visual to drill-down to the next level of the hierarchy.
  • Go to the next level in the hierarchy.
  • Expand all down one level in the hierarchy. This behaves differently to the Click to turn on Drill Down option mentioned already, by grouping together the previous hierarchy level each time you drill-down.

An example of how all this works as part of a Pie chart visualization is viewable in the sequence below:

As should hopefully be clear, hierarchies are very much the icing on the cake in building an engaging and wholly interactive reporting solution within Power BI.

Example: Creating a Hierarchy and adding it to a Visualization

The steps that follow provide instructions on how to build out a product categorisation hierarchy, using sample data, and then how to apply this to a Donut chart visualization. All that is required to work through these steps is access to the Power BI Desktop application:

  1. In Power BI Desktop, click onĀ Edit Queries to open the Power Query Editor. Navigate to the New Source button and select the Blank Query option:
  2. Select the newly created Query1 in the Queries pane and click the Advanced Editor button. Copy and paste the following M code into the window and press Done:
    1. let
          Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("nZNNbsMgEIWvgrxqJRb438mybZZRonrpZoGScYNiYwvsqu11epOerBjstHKwE3WBhJj3vjdoIMsc18HO4/MabXjBOCzRijcgasEkoDtJy7qA+5sUgVrfXwEOCXF2OHO8kWsrqhykZBWnxRR5SmPYHo6jRLP9kS9tKD9QcZji2uqGGeE4cTUz6D0piDe2v7i85ThSS1tDtVm974+Uv0Kf+Vc3Uzojus0mz7sEPwptafPVgROPlC1rJinj2sBIfnVPIE9NVVsIlsrgX1yq8kqgNTtI9gnopSXEiyZe0X99iZ5mgheumaZL7LC0pEWBHlqpBiGlenBQsra80sF1k4kPfM+Ed38qPVIB24rxxjL32WKkYS4h2Pf623SfKT191KD7OXdiAd8iMgEhDn2F3/0A", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type text) meta [Serialized.Text = true]) in type table [ProductID = _t, Name = _t, #"Product ID" = _t, Parent = _t, TotalSales = _t]),
          #"Changed Type" = Table.TransformColumnTypes(Source,{{"ProductID", Int64.Type}, {"Name", type text}, {"Product ID", type text}, {"Parent", Int64.Type}, {"TotalSales", Currency.Type}}),
          #"Replaced Value" = Table.ReplaceValue(#"Changed Type",null,0,Replacer.ReplaceValue,{"TotalSales"})
      in
          #"Replaced Value"
      
  3. This will then load up a table object that resembles the below, which derives from the sample Product data from Dynamics CRM/365 Customer Engagement:
  4. Right-click the Query1 query and use theĀ Rename option to change its name to Products. Select the Close & Apply button to exit the Power Query Editor.
  5. Open the Data pane, select the Products query and use the following DAX formulas to create New Columns for the table:
    • ProductHierarchy = PATH(Products[ProductID], Products[Parent])
    • Product Category = LOOKUPVALUE(Products[Name], Products[ProductID], PATHITEM(Products[ProductHierarchy], 1, INTEGER) )
    • Product Grouping = LOOKUPVALUE(Products[Name], Products[ProductID], PATHITEM(Products[ProductHierarchy], 2, INTEGER) )
    • Base Product = LOOKUPVALUE(Products[Name], Products[ProductID], PATHITEM(Products[ProductHierarchy], 3, INTEGER) )
  6. The first field creates the required hierarchy list in a delimited format; the remaining columns then list out the three levels of the hierarchy as separate column values. The data in your table should resemble the below if done correctly:
  7. Right-click the Product Category field in the Fields pane and select New Hierarchy, to create a new hierarchy as indicated below:
  8. Modify the newly created hierarchy so that:
    • It is named Product Hierarchy
    • It contains, in addition to the Product Category field, the Product Grouping and Base Product fields.
    • The order of the newly added fields reflect the following:
      • Product Category
      • Product Grouping
      • Base Product
  9. If done correctly, the Hierarchy should resemble the following:
  10. Click on the Report tab and add an empty Donut chart visualization to the report. Populate the Field well values as shown below:
  11. The Donut chart should update accordingly, and with the appropriate drill-down options available at the top of the visualization. Notice also that hovering over each section of the Donut chart displays an aggregated total for that level of the hierarchy:

Key Takeaways

  • Hierarchies within Power BI provide a means of logically categorising data into an order of preference or precedence, providing greater flexibility to Power BI report users when they interact with visualizations.
  • Date Hierarchies are created and managed automatically by Power BI for each Date or Date/Time field defined within your model. These automatically create fields that contain the Year, Quarter, Month & Day values from the respective date fields. These fields can then be utilised as part of a Table visualization or within a DAX formula. Date Hierarchies can also be completely disabled if required.
  • Custom (or User-Defined) Hierarchies need to be created manually and provide additional customisation options when compared to Date Hierarchies, such as the number of fields they contain, the order and its name. A Custom Hierarchy will typically make use of one of several Parent/Child DAX functions, such as PATH or PATHITEM.
  • Including a hierarchy as part of a chart visualization, such as a Pie chart or Donut chart, opens up other drill-down capabilities around your data. Indicated by the additional arrow icons included at the top of the visualization, they provide the means for users to interrogate data points that interest them the most straightforwardly.

The past couple of posts have already started to introduce some of the visualization options available within Power BI. In next week’s post, we will take a much closer look at all of the options available within the application to display data, as well as look at features such as Bookmarks and the various report page customisation tasks available to developers when building out a report.

As we move into the festive period, now is the time to put your feet up, relax, take stock for the year ahead…or, if you are reading this over Christmas, grab the opportunity to learn more about Power BI šŸ™‚ . In the seventh post in my series concerning Microsoft Exam 70-778, we move away from the suitably large subject area of DAX into a topic much more visually focused and accessible – Measure performance by using KPIs, gauges and cards. The related skills for this exam area are:

Calculate the actual; calculate the target; calculate actual to target; configure values for gauges; use the format settings to manually set values

As part of this week’s post, I hope to delve deeper into each of these skill areas, with the aim of providing a revision tool for the exam or a general learning aid for those getting to grips with Power BI for the first time. To follow on as part of any examples that follow, make sure you have downloaded the WideWorldImporters sample database and hooked up Power BI Desktop to the tables described in my first post in this series.

KPI Overview

A standard reporting requirement, and one which typically forms the basis of any contractual performance monitoring is the studying of Key Performance Indicator (KPI) figures. These are designed to provide an executive level view to answer questions such as “How is our sales pipeline progressing?” or “Have we met our objectives to reduce the number of monthly complaints down to X number?“. The whole process of collating together diffuse data sources to present this information may, in the past, have been exhausting. With Power BI, it is possible to deploy a dedicated KPI visualization that allows you to straightforwardly and consistently report headline figures, track variance over time and receive immediate visual cues to flag up any potential issues.

To get going with your first KPI visualization, you must supply two critical pieces of data:

  • Indicator: This is the “actual” value that needs reporting against a target, and will typically be some form of aggregation contained within a Measure.
  • Trend axis: Representing the performance of your indicator based on a range of data, the most typical axis type to use here would be some form of date value – such as month or year.

A KPI configured with just these two properties will work but looks…well…bland and not very useful at all:

This is why a Target Goal should additionally be specified. Adding this will allow for the appropriate colour to be applied to the visualization, to indicate how well the Indicator is performing against your target. The great thing about this is that up to 2 Target Goal values can be specified if needed. You potentially lose some functionality here, as the Distance percentage value will no longer display correctly; but this may be useful if, for example, you have an aspirational target that there would be a benefit in hitting, but is not a strict requirement. When the value of one Target Goal is determined to be fulfilled, but the other isn’t, the Visualization will display Amber by default, as indicated below:

The example at the end of this post will walk through the steps involved in setting up a KPI.

Gauge Visualizations

We got a sneak peek into Gauge’s when working with What-If Parameters in last week’s post, but a more in-depth discussion regarding them is necessary. Gauges provide a different means of viewing how a subset of data is performing against a target. They differ from KPI’s primarily due to the additional configuration options they afford and the potential they have to provide a faster means of interacting with key data points on the visualization. The configurable field well properties for a Gauge is viewable below, in the screenshot and descriptive bullet point provided:

  • Value: This is the value that requires tracking, similar to the Indicator within KPI’s.
  • Minimum value: The minimum amount that needs to be hit by the Value before the Gauge will be filled in.
  • Maximum value: The maximum amount that needs to be hit by the Value before the Gauge stops filling (i.e. a Gauge with a Value of 105 and a Maximum value of 100 would display as full).
  • Target value: The target that needs hitting, which will be presented as a black line on the Gauge, as shown below:
  • Tooltips: These are additional field values that will be displayed to the user when hovering over the Gauge. These fields can either be aggregated variants of columns or a Measure.

Gauges behave differently from KPI’s in that they will “work” with only one field well specified. For example, adding a Measure with a value of 8 million as the Value will display a half-full Gauge, as indicated below:

Notice that, in this scenario, the Gauge assumes the maximum amount to be double of what is specified in the Value field well – in this case, 16 million. A Gauge configured so frugally has little purpose and you should, as a minimum, ensure that the Maximum value and Target value field wells are also set, as demonstrated below:

A nice little feature of Gauges is the ability to specify any of the potential field well values manually, within the Formatting options (discussed in the next section).Ā  TheĀ Value field well must be populated already within your Gauge to support this feature. You will then have the ability to manually specify the other values within the Gauge axis options area:

Any manually defined figure will be automatically overwritten and deleted if you choose to use a field from a table instead, so take care here to avoid any data loss.

Gauges address a similar need to KPI’s, in that they allow you to view possible progress against a maximum or target value. A significant downside in using them is that they present a less visual means of showcasing potential issues with your data. You should weigh these advantages/disadvantages up when determining whether to use a Gauge or a KPI as part of your report.

Visualization Format Settings

All Visualization’s within Power BI can be customised, often to the extent where they can look indistinguishable from when you first add them onto your report. The Formatting tab on the right-hand pane is your go-to destination in this regard, and is accessible by clicking the paintbrush icon while selecting any Visualization:

The types of things that are achievable via these options include, but are not limited to:

  • Modifying all aspects of the visualizations Title, such as its visibility, the text displayed, font colour/size/type and alignment.
  • Adding a colour background to the visualization.
  • Including a description for the visualization.
  • Toggling a border for the visualization and its colour.
  • Fine-tuning the exact location of the visualization on the report, based on its X & Y Position values.

Each Visualization will also have a set of specific, unique options. We can see an example of how this looks by going back to KPI’s again and examining the top four options listed:

  • Indicator: This area provides options on how to display the Indicator field value on the KPI. It is possible to round up figures to the thousands, millions and even trillions, and also to adjust the number of decimal places shown. Auto is the default option used and will generally assign the best rounding option, depending on the underlying value.
  • Trend Axis: Here, it is possible to enable/disable the trend visual on the KPI. The example below demonstrates how this looks when disabled:
  • Goals: With the Goal toggle, it is possible to remove the Goal figure underneath the Indicator value completely; the Distance toggle will remove the percentage distance value as well. It is possible to mix and match options here, as indicated in the example below:
  • Color coding: The default RAG (Red, Amber, Green) traffic light system should be suitable for most situations but, if you have a specific branding requirement, it is possible to override the Good, Neutral and Bad colours with a custom Hex colour value. The Direction option also lets you reverse how the KPI works. So, for example, if raising more than 5 IT service requests would lead to a Bad outcome, any number underneath this would appear as Good instead.

When it comes to this subject area for the exam, there is no need to study the whole range of formatting options available; however, a general awareness will hold you in good stead.

Example: Creating a KPI

The process involved in building out a KPI can be a lot more involved then you may suspect, based on the descriptions provided so far. Therefore, the example that follows is designed to show you the type of preparatory modelling steps that will be needed to put in place a working solution utilising KPIs. To follow through these steps, make sure you have connected Power BI up to the WideWorldImporters sample database and that the Sales.OrderLines table is within your Power BI data model:

  1. In Power BI Desktop, on the Sales OrderLines table, use the New Column button to add on the following new calculated columns:
    • GrossPrice = ‘Sales OrderLines'[UnitPrice] * ‘Sales OrderLines'[Quantity]
    • NetPrice = ‘Sales OrderLines'[GrossPrice] + (‘Sales OrderLines'[GrossPrice] * (‘Sales OrderLines'[TaxRate] / 100))
    • OrderDate = RELATED(‘Sales Orders'[OrderDate])
  2. Next, create a Calculated Table via the New Table option, that uses the following DAX formula:
    • SalesOrderAgg2016 = FILTER(SUMMARIZE(‘Sales OrderLines’,’Sales OrderLines'[OrderDate], “Total Gross Price”, SUM(‘Sales OrderLines'[GrossPrice]), “Total Net Price”, SUM(‘Sales OrderLines'[NetPrice])), ‘Sales OrderLines'[OrderDate] >= DATE(2016, 1, 1) && ‘Sales OrderLines'[OrderDate] <= DATE(2016, 12, 31))
  3. Doing this will create a new table object that looks similar to the below, providing a total sum of the calculated columns created in step 1), grouped by OrderDate. I would also recommend, at this stage, to change the format of the new columns to your preferred Currency value:
  4. Add a new Calculated Column to the SalesOrderAgg2016 table to get the Month Name label from the OrderDate column:
    • OrderDateMonthName = FORMAT(DATEVALUE(SalesOrderAgg2016[OrderDate]), “MMMM”)
  5. With the base data ready, we can now look at creating an Actual and Target Measure on the SalesOrderAgg2016 table, using the following DAX formulas:
    • Actual Total Net Price = SUM(SalesOrderAgg[Total Net Price])
    • Target Total Net Price = 5750000
    • Actual Total Gross Price = SUM(SalesOrderAgg[Total Gross Price])
    • Target Total Gross Price = 5500000
  6. On the Report tab, under the Visualizations area, click on the KPI icon to add an empty KPI visualization to the report:
  7. Click on the newly created Visualization and, under the Fields area, drag and drop the appropriate SalesOrderAgg2016 fields into the wells indicated below:
  8. The visualization will then update accordingly, showing us the figure trend over each month and coloured red to indicate that this KPI is currently off target:
  9. To see how a KPI looks when ahead of target, we can repeat steps 5) and 6), but this time using the Net figures instead:

Key Takeaways

  • There are two principle visualization types available within Power BI to help track actual-to-target progress – KPIs and Gauges.
  • KPIs provide a more visually unique means of a binary success/fail determination when tracking towards a target. It is also possible to use KPI’s to track variance over time via the Trend axis. The Indicator will typically be the result of some form of aggregation or Measure.
  • Gauges provide a less visually distinctive, but non-binary, mechanism of viewing progress towards a target. Gauges support more potential field well values when compared with KPIs, nearly all of which are optional in some way. You can also manually define some of these values, for situations where your data model does not contain the required information.
  • All visualizations within Power BI are modifiable from a display or formatting perspective. The same basic options will generally be supported – such as changing a font type or background colour – with more specific configuration properties available per unique visualization type. For example, a KPI visualization can be customised to hide the background Trend Axis entirely. All of these options are designed to give developers greater control over the look and feel of their reports and to mirror them as closely as possible to any potential branding requirement.
  • When building out a solution designed to monitor progress within Power BI, the steps involved will typically be more in-depth than merely creating a new visualization. In most cases, there will be a requirement to bring together a lot of the other skills that have been discussed previously within this series – such as creating DAX formulas, modifying data within Power Query or bringing together different data sources into a single model. It is essential, therefore, not to underestimate the amount of time and effort involved in creating a practical solution that takes advantage of KPIs or Gauges.

I hope that this weeks post has been a little easier to bear when compared with DAX šŸ™‚ . In next weeks post, we will take a closer look at data hierarchies and how to apply these to visualizations within Power BI.