After ingesting, cleaning and transforming data, it is essential to visualize it in order to explore its patterns, trends and relationships. Visualizing data can help identify outliers, anomalies, clusters and correlations that might not be evident from numerical or textual data alone. Data visualization can also facilitate the communication and presentation of the results of data analysis to different audiences, such as stakeholders, customers or decision-makers. By using appropriate charts, graphs, maps or dashboards, data analysts can convey insights and recommendations in a clear and engaging way.

This blog post discusses using Power BI to handle lease accounting requirements involving recording ROU assets and liabilities as mandated by accounting standards such as ASC 842 and IFRS 16. 

Power BI has introduced an exciting feature that allows users to leverage the capabilities of Power Automate through buttons within Power BI reports. This enhancement significantly improves the user experience by enabling users to perform operations directly by clicking on a button from the report interface.

In this blog post, we’ll provide a step-by-step guide on how to utilize a Power Automate button to trigger automated tasks within a Power BI report. Here I have taken an example to demonstrate how a single click can send a new lead directly to an Excel spreadsheet.

Let’s see how we can implement this.

Hey there! Whether you're a seasoned pro or just dipping your toes into the world of data analytics, we all know there's a new player in town —Microsoft Fabric. Since the first Fabric Conference to the most recent updates, a lot of advanced capabilities have been introduced in the game. Let's take a moment to take a step back and brush up our Fabric basics, and ensure you are ready to revolutionize your data game.

Data plays an important role in decision making, and organizations that can harness its power can gain a competitive edge in the market. However, data alone is not enough. To extract value from data, organizations need to build end-to-end data analysis pipelines that can handle the entire data lifecycle, from data ingestion, data cleaning, data transformation, to data visualization and analysis. In this blog post, we will explore why end-to-end data analysis is important for organizations and how it can help them achieve their goals.

In Power Query, there are two functions to manage columns in a table, which are accessible through three different actions in the User Interface. Located on the Home tab, these actions allow you to perform the following operations:
👉 Choose Columns (which calls: Table.SelectColumns)
👉 Remove Columns (calls: Table.RemoveColumns) and
👉 Remove Other Columns (calls: Table.SelectColumns)

Choosing the right method depends on your specific needs. Let’s explore this with a practical scenario. Imagine you have an "Items" table from a small database. Most of your transformations are handled within a Dataflow using Power Query Online to prepare that table for easy use within various semantic models.

In Dataflows, you can opt for removing columns. This allows new columns "added" or made available at the source, to appear without needing to update the Dataflow manually, ensuring flexibility and reducing maintenance.

In semantic Models, you can opt for selecting columns early by choosing only necessary columns from the Dataflow "Items" table for that specific semantic model in development. This locks or limits columns, preventing unneeded columns from bloating the model.

To enhance reliability, make sure to pass an argument for the optional MissingField parameter, this enables you to specify how absent fields should be handled. For example:

• In Dataflows, use MissingField.Ignore to avoid errors when removing non-existent columns.
• In Models, use MissingField.UseNull to maintain a table's structure and allow investigation or reporting of completely empty columns.

Choosing the right method ensures your queries are more robust and reliable, while your models stay lean and manageable.

Learn more about the MissingField.Type

Take a look at straightforward solutions to top business intellignece (BI) planning challenges with tips on forecasting efficiency and strategic decision-making. The examples shared in this article hope to inspire creative thinking and problem-solving.

I recently came across a challenging task involving a Power BI semantic model with over 500 measures. Many of these measures contained hardcoded filter predicates. The data engineer had updated data in the database, which meant these hardcoded values were no longer valid. My job was to update all the affected measures with new values provided by the data engineer.

The problem was, I didn't know which measures needed updating, and I had just one day to complete the task. Despite my limited knowledge of this semantic model, I managed to complete the task on time using Power BI external tools. In this blog, I will explain the step-by-step process I followed to achieve this.

When working with Power BI, efficiently retrieving data from APIs is crucial for performance and reliability, particularly when handling large datasets. This guide examines two different approaches to fetch data from the NHS UK API and explains why one method is more effective after publishing the dataset.

Curious about PBIP folder structure in Power BI? Dive into the Mahabarata-inspired story on Power BI Developer Mode!

Buidl your own Real Time Intelligence Demo with Sample Data in Microsoft Fabric.

Slicing and dicing dates: A practical guide to the Power BI Timeline Slicer

When preparing data, we may meet a scenario that needs to split all values stored in a single column into structured rows and columns. Here I will share a simple method with M query.  

Scenario: 

In the use of Power BI Desktop, the Table visual is the first choice for most users to display data. However, there are some aspects of the Table visual that do not meet our needs well. For example, the font size cannot be changed according to the length of the word. Table visual can only set global font size. Or set the color of a part of the value according to the conditions. The conditional formatting settings of the Table visual affect the values in the entire cell. In this article, we will use DAX in conjunction with HTML to generate HTML Content visual similar to the Table visual to display data.

When working with customer data in Power BI, it's common to compare lists from different sources to identify missing entries. In this blog, we'll explore three different approaches to find missing customers from one table by comparing it with another using DAX functions.