You may run into this error when loading Power BI:
"load was cancelled by error in loading a previous table"If you do get this error, keep scrolling down to see what the “inducing” error is. This message is an indication that there was an error previous to getting to the current table in the process. The real, initial error will be more descriptive. Start with resolving that error(s), and then this one will go away.
I hope you found this helpful.
I was getting this error message when I attempted to refresh a Power BI application:
"Column 'Date' in table 'Date Dim' contains blank values and this is not allowed for columns on the one-side of a many-to-one relationship or for columns that are used as the primary key of a table"However, despite what the message indicated, I double-checked and confirmed that I did not have any blank values in the ‘Date Dim’ table.
It turns out that you may also get this error (although incorrectly worded in my opinion) if the blanks are in the joining table. In my case, I had blanks in a ‘Snapshot Date’ column in the fact table that was joined to the ‘Date Dim’ table. Once these blanks were filled, the refresh ran without error.
One thing to look out for in these cases (since this is what happened in my case), if your source is Excel, undo all filters to make sure that you do not have any rows being filtered out when checking for blanks values across your columns, because this could potentially inadvertently hide the rows with the blank values and cause you to miss them.
I hope you found this helpful.
When to use: To track how a measure changes over days, months, or years.
Best charts:
When to use: To compare values across distinct groups (e.g., sales by region, revenue by product).
Best charts:
When to use: To see whether two measures are related (e.g., advertising spend vs. sales revenue).
Best charts:
Sometimes you don’t need a chart—you just want a single number to stand out. These types of visuals are great for high-level executive dashboards, or for the summary page of dashboards in general.
Best visuals in Power BI:
When to use: To see how data is spread across categories or ranges.
Best charts:
When to use: To identify anomalies or areas needing attention across a large dataset.
Best charts:
When to use: To dive into raw data while keeping formatting and hierarchy.
Best visuals:
When to use: To see how individual parts contribute to a total.
Best charts:
| Scenario | Best Visuals |
|---|---|
| Tracking trends, forecasting trends | Line, Area, Sparklines |
| Comparing categories | Column, Bar, Stacked |
| Showing relationships | Scatter, Line + Scatter, Line + Column/Bar |
| Highlighting metrics | Card, KPI, Gauge |
| Analyzing distributions | Histogram (columns with bins), Box & Whisker, Pie/Donut (for few categories) |
| Identifying problem areas | Heatmap (Matrix with colors), Treemap, Scatter |
| Exploring detail data | Table, Matrix |
| Showing part-to-whole | Stacked Column/Bar, 100% Stacked, Treemap, Pie/Donut |
The below graphic shows the visualization types available in Power BI. You can also import additional visuals by clicking the “3-dots” (get more visuals) at the bottom of the visualization icons.
Power BI, and other BI/analytics tools, offers a rich set of visuals, each designed to represent data in a way that suits a specific set of analytical needs. The key is to match the chart type with the story you want the data to tell. Whether you’re showing a simple KPI, uncovering trends, or surfacing problem areas, choosing the right chart ensures your insights are clear, actionable, and impactful. In addition, based on your scenario, it can also be beneficial to get feedback from the user population on what other visuals they might find useful or what other ways they would they like to see the data.
Thanks for reading! And good luck on your data journey!
Microsoft Fabric OneLake Catalog is the next generation, enhanced version of the OneLake Data Hub. It provides a complete solution in a central location for team members (data engineers, data scientists, analysts, business team members, and other stakeholders) to browse, manage, and govern all their data from a single, intuitive location. It provides an intuitive and efficient user interface and truly simplifies and transforms the way we can manage, explore, and utilize content in Fabric. Usage is contextual and it has unified all Fabric item types (including Power BI items) and expanded support to all Fabric item types, integrating experiences, and providing detailed views of data subitems. It is a great tool.
This tool will make your work within Fabric easier, and it will reduce duplication of items due to improved discoverability, and it will enhance our ability to govern data objects within the platform. So, check out the resources below to learn more.
Here is a link to a detailed Microsoft blog post introducing the OneLake Catalog:
And here is a link to a Microsoft Learn OneLake Catalog overview:
And finally, this is a link to a great, short (less than 5 min) video that gives an overview of the OneLake Catalog:
Thanks for reading! Good luck on your data journey!
Power BI allows us to connect to many different data sources – from relational databases, NoSQL databases, files, and more – to source data for consumption in Power BI. From the data sourced, you can create additional data (new calculated columns, metrics, transformed data, etc.), build data models, and create reports and dashboards.
There are a few storage modes related to how the data is retrieved, stored, and processed in Power BI. The storage modes are Import, DirectQuery, Live Connection, and Dual. The storage mode is set at the table level for each table in the Power BI data model. I will now describe these modes.
Import
With the Import storage mode, Power BI imports and caches the data from the sources. Once the data import is complete, the data in Power BI will remain the same until is refreshed by the Power BI refresh process for that dataset.
This storage mode allows for the usage of the most Power BI features for data modeling and analysis. For example, Import mode is required for using two of the popular Power BI features, Quick Insights and Q&A. Also, this mode is almost always the best for performance. However, it’s not necessarily the best option in all scenarios. Since the data is imported, the file size can get large and can sometimes take a considerable amount of time to load. But generally, for relatively static, low volume data, it is the preferred choice.
Queries submitted to an imported dataset will return data from the cached data only.
DirectQuery
With the DirectQuery storage mode, no data is cached in Power BI, but the metadata of the source tables, columns, data types, and relationships is cached. Instead, the data is directly queries on the source database when needed by a Power BI query, such as when a user runs a Power BI report that uses the data.
For Since the data is not imported, if all the tables in the data model use DirectQuery, the Power BI file size will be very small compared to a model with imported data.
Live Connection
The Live Connection storage mode is a special case of the DirectQuery mode. It is only available when sourcing from Power BI Service datasets or Analysis Services data models. There are limitations when using this mode. Data modeling is limited to creating measures, and therefore, you cannot apply transformations to the data, and you cannot define relationships within the data. And you can only have one data source in your data model.
Dual
With the Dual storage mode, a table may use Import mode or DirectQuery mode, depending on the mode of the other tables included in the query. For example, you may have a scenario in which you have a Date table that is connected to one transaction table that needs to reflect the data in the source, and is therefore set to DirectQuery mode, and also connected to another transaction table that only has less than 100,000 rows and is set to Import storage mode. By setting the Date table to Dual storage mode, Power BI will use DirectQuery when the query involves the date table and the first transaction table, while using Import mode when the query involves the date table and the second transaction table.
The below table summarizes the Power BI data storage modes:
| Import | DirectQuery | Live Connection | Dual |
| -Data is imported and cached in Power BI -Preferred for static, relatively small datasets -All Power BI functionality is available – including DAX, Calculated tables, Q&A and Quick Insights -Can connect to Analysis Services but Live Connection is preferred -Can have unlimited data sources -Typically provides the best performance | -Data is queried on the source when needed -Use for large datasets and when data changes in source need to be updated immediately -Features such as Q&A, Quick Insights, Calculated Tables, and many DAX queries are not supported -Limited data transformation functionality -Parent-child functionality not supported -For relational databases -Not supported for Analysis Services -Performance greatly dependent on the source data source | -A special case of DirectQuery -Used for connecting to multi-dimensional data sources, such as Analysis Services -Can be used only with Power BI datasets and Analysis Services -Can have only one data source -No data transformation available -Q&A and Quick Insights not available -Can create measures | -A combination of Import and DirectQuery -Power BI will choose the appropriate option based on the storage mode of the tables involved in the query -Can improve performance |
Note: the content in this post is relevant for the PL-300 Analyzing Data with Microsoft Power BI certification exam.
Thanks for reading! I hope you found this information useful.
Good luck on your analytics journey!
Power BI has 4 roles. Those roles, in order of increasing access/capabilities, are Viewer, Contributor, Member, and Admin. Before granting roles to users in your environment, it’s best to have a solid understanding of what each role has access to and is capable of doing.
The table below provides a list of capabilities of each role. As you will see, each roles “absorbs” or “inherits” the capabilities of all the roles below it in the hierarchy – for example, the Contributor can do everything the Viewer can do plus more, and the Member can do everything the Contributor can do plus more.
The Power BI Workspace roles
| Viewer | Contributor | Member | Admin |
| View dashboards, reports, and workbooks in the workspace | Everything that the Viewer can do | Everything that the Contributor can do | Everything that the Member can do |
| Read data from dataflows in the workspace | Add, edit, delete content workspaces | Add other users as members, contributors, or viewers to the workspace | Update and delete the workspace |
| Row-level security applies to viewers | Schedule refreshes and use the on-premises gateway within workspaces | Publish and update the workspace app | Add and remove other users of any role from the workspace |
| Feature dashboards and reports from workspaces | Share and allow others to reshape items from the workspace | ||
| Have access to the lineage view | Feature the workspace app | ||
| Have full access to all datasets within a workspace |
A few things to keep in mind regarding roles:
This article was intended to be an easy read; more detailed information regarding Power BI roles can be found here on the Microsoft site.
Thanks for reading!
Our team at work recently started using the Power BI platform. We are just getting going but I am already loving this tool. Our current enterprise BI platforms are Qlik and OBI (Oracle Business Intelligence), however, Power BI has has gained significant traction in business teams over the last couple years where it used for departmental reporting and analysis.
I see why the business teams love this tool and am excited about bringing it into our portfolio of tools for delivering analytic solutions across the company. These are some of the reasons I like Power BI:
Power BI has a very intuitive and well laid out interface. You can easily switch between the visualizations, the data, and the data model. And within each of those tabs, you easily navigate using the well-placed objects and menu items. I found the interface easy to get accustomed to.
and there are many more!
Some notable connectors are SQL Server Analysis Services, PostgreSQL, Amazon Redshift, Google BigQuery, Snowflake, various Azure data sources, Salesforce, Spark, GitHub, Databricks, and many more.
And you have the ability to “get more” from the marketplace.
I look forward to the Power BI journey and the ongoing quest to make our data as valuable as possible for our company.
There is an “issue” or “security feature” (depending on how you look at it) that exists in OBIEE 12c (Oracle Business Intelligence) and in OAS (Oracle Analytics Server). The OBIEE or OAS dashboard pages do not display external embedded content in most browsers.
We use multiple BI platforms, but wanted to avoid sending users to one platform for some reporting and to another for other reporting. This can be confusing to users. To provide a good user experience by directing users to one place for all dashboards and self-service reporting, we have embedded most of the QlikView and Qlik Sense dashboards into OBI pages. With that, the users can be provided with one consistent training and have one place to go.
However, the Qlik embedded content only shows when using the IE (Internet Explorer) browser and the others give some “error” message.
Or you may get other messages, such as (from Oracle Doc ID: 2273854.1):
This situation, although not ideal, has been fine since our company’s browser standard is IE and we provided a work-around for users that use other browsers to access the embedded content. But this will change soon since IE is going away.
There are 2 solutions to address the embedded content issue.
(from Oracle Doc ID: 2273854.1):
For security reasons, you can no longer embed content from external domains in dashboards. To embed external content in dashboards, you must edit the instanceconfig.xml file.
To allow the external content:
<ServerInstance>
…
<Security>
…
<InIFrameRenderingMode>allow</InIFrameRenderingMode>
<ContentSecurityPolicy>
<PolicyDirectives>
<Directive>
<Name>child-src</Name>
<Value>’self’ http://www.xxx.com http://www.yyy.com</Value>
</Directive>
<Directive>
<Name>img-src</Name>
<Value>’self’ http://www.xxx.com http://www.yyy.com</Value>
</Directive>
</PolicyDirectives>
</ContentSecurityPolicy>
…
</Security>
…
</ServerInstance>
Engage the teams responsible for enterprise browser settings or other appropriate teams at your company as necessary.
After upgrading from OBIEE to OAS (Oracle Business Intelligence to Oracle Analytics Server), the prompts started showing NULL values in the drop downs. This was not happening in OBI because we had the <ShowNullValueWhenColumnIsNullable> config parameter set to “never” for prompts.
This setting looked something like this in OBIEE (note the first line after the <Prompts> tag):
<ServerInstance>
…
<Prompts>
<ShowNullValueWhenColumnIsNullable>never</ShowNullValueWhenColumnIsNullable>
<MaxDropDownValues>256</MaxDropDownValues>
<ResultRowLimit>65000</ResultRowLimit>
<AutoApplyDashboardPromptValues>true</AutoApplyDashboardPromptValues>
<AutoSearchPromptDialogBox>true</AutoSearchPromptDialogBox>
…
</Prompts>
…
</ServerInstance>
In OAS, this parameter needs to be set in the new analytics/systemsettings page. Go to that page and set the option. Then restart by clicking on the Restart button on that page. After a restart, it resolved the issue for us.
We had a similar resolution to an issue we had with “not able to save analyses that contained HTML markup“.
We recently upgraded from OBIEE 12 to OAS 5.5. (Oracle Business Intelligence to Oracle Analytics Server). After the upgrade, we were not able to save analyses that contained HTML markup. We were able to do this before the upgrade.
Turns out, the configuration parameter for this now needs to be set in the new analytics/systemsettings page. Go to that page and enable the option “Allow HTML Content”. Then restart by clicking on the Restart button on that page.
After a restart, it resolved the issue for us.
If this doesn’t resolve it for you, you may need to remove the parameter from the instance config file and try again.
Back up your instanceconfig.xml file. Then edit it by removing the element “EnableSavingContentWithHTML” from the Security section and save the file. You will be removing a line that looks something like this:
“<EnableSavingContentWithHTML>true</EnableSavingContentWithHTML>”
Then go back to the analytics/systemsettings page, confirm “Allow HTML Content” is enabled, and restart again. This hopefully should resolve your issue.
The Data Community 