Trending March 2024 # Dax Calculate Function, Dax Formula Writing Techniques In Power Bi # Suggested April 2024 # Top 7 Popular

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In this tutorial, we’ll talk about DAX formula writing techniques and how to simplify models in Power BI.

We’ll discuss the key functions and methods to organize and make our model’s interface friendlier and easier to operate.

The methods we’re going to go through are formula syntax, measure groups, and formatting DAX codes in Power BI. It’s crucial that we understand these three topics in order to master DAX calculations and formula writing in Power BI.

We’ll discuss each of them and see their unique contributions and importance.

The formula syntax that we’ll be discussing is a bit different compared to other formula languages. But this is essential for our models in Power BI.

We’ll call this new measure Total Sales. Next, type SUM.

Information boxes are also present to explain the functions.

With DAX formulas, we have to focus on the tables and columns. Focus on the table we need to reference and the column within it.

Now, input Total Revenue inside the SUM function.

In Power BI, referencing the table always comes first, the column comes after.

However, there are formulas, like the Total Quantity measure, that only require referencing the table.

If we use the COUNTROWS function, we can see that it’s only asking for a table.

Next, reference the Sales table, and we’ll now have another measure that counts the total quantity we sold.

There is another measure in this Power BI example called Total Costs.

For this measure, we use the iterating function SUMX. This function returns the sum of an expression evaluated for each row in a table.

Next, reference the Sales table. Then for the expression, reference the Order Quantity column. Lastly, reference the Sales table again with the Total Unit Cost column.

That is going to give us our Total Costs.

In Power BI, measure groups are used to organize DAX calculations. It’s highly recommended that we use them in our model as we start creating measures.

For us to run more analyses in our Power BI models, we need to create a lot of measures.

However, creating plenty of measures could give us a busy-looking model. So, we need to create measure groups to avoid mixing our measures and data tables.

That table will then be in our report.

Once the measures are in the Key Measures table, we can now delete the dummy column or Column1.

It will sort out and change the icon of the measure group like so:

This measure group is just one example. In Power BI, there are other groups like time comparisons group and moving averages.

In some showcase models in Enterprise DNA, we’ll see that we can have 6-8 groups or more.

Utilizing measure groups to organize our measures makes our model look clean and seamless.

Formatting a formula makes things simple in our model and doesn’t over-complicate our measures in our formulas and reports.

Then, write Formula Example. Next, use the CALCULATE function and then add in Total Quantity.

After that, use the FILTER function for the Sales table. We’ll make the Customer Name Index greater than 5.

The Customer Name Index must also be less than 20. So, add another FILTER function to go through the Sales. Lastly, we only need to equate the Channel to the Wholesale.

Once we finish writing the DAX formula, we can now see the results. It’s just like the SUM formula in MS Excel, however, it’s a little complicated in Power BI.

It’s important to format and organize formulas in our model.

It’s also recommended that on different rows, we place different key functions with different indentations. This makes it easy to understand what we’re trying to calculate if the functions are separate.

To do that, hold shift and press enter. Indent and place things on a new row when there is a key formula introduced.

We can see that the function CALCULATE is on a different row as well as the FILTER functions. They are arranged so it can be read easier. This avoids confusion when making analyses for our model.

We just have to keep indenting every time we add more key functions. We won’t be disoriented with the dozens of calculations in our model.

In Power BI, we encounter a lot of models, functions, and formulas. With these writing formula techniques, we can improve how the calculations and models are presented.

What we’ve learned here are just some methods, like measure grouping and formatting DAX calculations, to help compute, simplify, and organize our analyses efficiently for a better presentation.

We can use them to have a better grasp of what’s happening in our data model.

All the best,


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Bank Risk Analysis Reports In Power Bi

This Power BI Showcase focuses on bank risk analysis and the key factors to look for in a bank. These factors could be deposits, loans, interests, or floats. You may watch the full video of this tutorial at the bottom of this blog.

A float is the difference between the deposits and loans caused by delays in processing checks.

Ordinarily that would be in the bank’s equity fund. It could come from several different locations, and also be capitalized on a stock market.

Here are the reports under this showcase:

In this first report, we’re looking at the key banking relationships across different areas of the bank.

There’s commercial, institutional, private bank, and retail. With this, we’re able to quickly have a look at the current risk per region.

We’ve associated a risk weighting on each client, which would ordinarily be the case in a banking setting.

The credit department would then identify whether a person is a low credit risk or a high credit risk.

In this case, we’ve termed “high credit risks” as “5”.

By selecting a bank area and client, we can further dive into a detailed outlay of their status and associated risk.

In this example, we’ve selected the Commercial area and the clients based in Auckland.

Most of the clients within this range have a risk weighting of level 2.

We can further dive into the information concerning our high-risk clients.

By zooming in on the map, we can easily monitor our clients’ business status.

We can easily look at their financial information, such as, income, and assets. This is a great source of analysis for a commercial manager.

The quick snapshot we get from this report helps identify where we should be directing our resources to maximize our performance. 

The second report provides a more granular perspective on each client.

Similar to the previous report, we’re using 1-5 as a gauge of the different risk levels.

We can also see a simple summary of our banking relationship and float by city.

This gives us a breakdown of where we should allocate additional funding from the bank’s equity.

If we dive into a specific city, we quickly get a list of all the client details. This includes their Total Deposits, Loans, and Properties.

If we want to follow up on each client, we can easily export the data from Power BI to an external file.

The next three reports give focus on each specific key business area.

This report focuses on Retail. 

We can look at the breakdown of all the bank deposits by client, along with their loans.

In this chart, we get a good look at the cluster of our deposits versus loans.

This next report focuses on the Commercial area of the business.

It has a similar layout to the previous report. This makes it easy to make comparisons between key business areas.

The last report in this showcase focuses on the Institutional area of the business.

This bank risk analysis Power BI Showcase is a great guide for businesses that are closely involved in the banking industry.

Reports like these are reliable sources of information on the status of an organization’s deposits, loans, and floats which make it easier to perform in-depth bank risk analyses.

All the best,


Dynamic Tooltip In Power Bi With Embedded Charts

I want to show you an awesome trick for the visualizations in your reports. You can use a dynamic tooltip in Power BI to highlight your visuals. This has been a relatively recent update embedded into the Power BI suite. You may watch the full video of this tutorial at the bottom of this blog.

When I did the challenge myself, I went for a totally different route from Paul Ross who utilized this dynamic tool tip in Power BI.

I thought that this was such a unique way to showcase information. This is a really cool technique when you’re showing a table.

You’ll see that within the tooltip itself, you can see the key information about the patient. We used a patient data set for this challenge, so we get to see the overview of a particular patient and their visits to an optical clinic.

Let’s say we’re on a call with the patient and we want to see granular details like their left eye and right eye scores. We can quickly see the information we need to answer with this type of report.

So how do you actually create this visualization? You can do this within the table visualization.

Previously, when you go to the Tooltip section and turn it on, the default option used to pop up. But now you can actually bring up a report page.

Once you select the Report page option, it will show you the pages that you can bring into the tooltip. In this example, we choose the page called Patient Tooltip.

If we go to the Patient Tooltip page, you’ll see below that this page is actually hidden when you’re online.

If you choose Tooltip, this will show up on the main page. After that, you’ll just need to work on the different metrics that you want to show.

On the top is a table with some check and x marks that show if they’re a Driver, Smoker, Private, or Subsidized.

Below that is another table with a range of other information about the patients, which came from the appointment table.

The entire table visualization was made using data bars in conditional formatting. Once you’re able to embed this type of visual into your own data sets and reports, consumers can easily see this dynamic information.

So once you’re done with the metrics and format, go back and switch to the Report Page and Patient Tooltip (which we’ve already done earlier).

You can also customize a few things here to change the overall look of your report.

Now, when you hover over the name of a patient, it showcases their information. This is an incredible feature that I’m confident not many of you are using.

There are many different ways you can use this technique. You could use this in a bar chart or donut chart to showcase trends. You can incorporate this into your line charts to show your cumulative totals.

Aside from the tooltip in Power BI, another awesome feature of this report is the ability to drill through another page that showcases patient information like eye test scores over time.


In terms of ease of use, there are many positives in this report. There’s the ability to drill into certain aspects of patient information. When you’re talking to a patient over the phone, you can see all this information quickly.

This is a great job from Paul who submitted this for the Power BI challenge. I’m relatively confident that Paul learned a lot by actually participating. And that’s what I recommend you do as well.

Simply visit the Enterprise DNA forum to check out the historic challenges and submissions. There’s so much to learn just by reading this stuff, and it’s also important to get involved as well. The Power BI challenges in the forum is probably one of the best learning experiences that’s out there at the moment.

Dummies Guide To Writing A Custom Loss Function In Tensorflow

This article was published as a part of the Data Science Blogathon.


Have you ever encountered a situation where you felt to use a custom loss function in your machine learning model? Maybe, you had to experiment with a new loss function while writing a research paper or to handle a new business case. Writing a custom loss function for the machine learning models is not very difficult. This article will teach us how to write a custom loss function in Tensorflow. We will write the custom code to implement the categorical cross-entropy loss. Then we will compare its result with the inbuilt categorical cross-entropy loss of the Tensorflow library.

Through machine learning, we try to mimic the human learning process in a machine. Like us, machines also learn from past mistakes. A loss function is used to evaluate the machine’s learning quality. It shows how well the machine learning model can predict the outcome from a given feature set. Building any machine learning model intends to predict the probabilistic target value as accurately as possible. So, the loss function can measure how far the predicted value is from the actual value. The loss function is not fixed and changes based on the task. The goal of an optimization procedure is to minimize the loss function.

Loss Functions in Tensorflow

Tensorflow is a widely used Python-based machine learning platform. Tensorflow library can be used for developing machine learning models across tasks. But this library has a certain focus on developing deep learning models efficiently. Tensorflow provides many inbuilt and optimized loss functions for developing machine learning models. Some commonly used loss functions in regression tasks are Mean Squared Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Huber Loss, etc. Common loss functions in classification tasks are binary cross-entropy, categorical cross-entropy, etc.

Categorical Cross-entropy

We use categorical cross-entropy loss when we need to predict two or more target classes (multi-class classification). Here the model is trained to predict a class from many classes. If we consider the actual target value is y, the predicted value is, and there are C number of classes, then the Categorical Cross-entropy (CE) loss can be defined as:

Usually, an activation function (Sigmoid/Softmax) is applied to the scores before the Cross-entropy Loss is computed. Categorical Cross-entropy loss is a generalized version of Binary Cross-entropy loss. In Binary Cross-entropy loss, C = 2 since there are only two classes. Hence the loss becomes:

Since there are only two possible classes,  and .

Custom Loss Function in Tensorflow

We will write the categorical cross-entropy loss function using our custom code in Tensorflow with the Keras API. Then we will compare the result between this custom categorical cross-entropy function and Tensorflow’s inbuilt categorical cross-entropy function.

Once trained, every model produces a predicted value of the target variable. For a loss function, we need the model’s actual value and the predicted value to compare and calculate the loss value. In Tensorflow, we will write a custom loss function that will take the actual value and the predicted value as input. This custom loss function will subclass the base class “loss” of Keras. For best performance, we need to write the vectorized implementation of the function. We will also use basic Tensorflow functions to get benefitted from Tensorflow’s graph feature.

class Custom_CE_Loss(tf.keras.losses.Loss): def __init__(self): super().__init__() def call(self, y_true, y_pred): log_y_pred = tf.math.log(y_pred) elements = -tf.math.multiply_no_nan(x=log_y_pred, y=y_true) return tf.reduce_mean(tf.reduce_sum(elements,axis=1))

Here, we can see that the Custom_CE_Loss function is subclassed from the base class “Loss”. We are overriding the call method that takes the true value and predicted value as input. We are also using Tensorflow’s inbuilt math functions for calculating log, multiplication, sum, mean, etc.

The multiply_no_nan function computes the product of x and y and returns 0 if y is zero, even if x is NaN or infinite. The reduce_sum function computes the sum of elements across dimensions of a tensor. The reduce_mean function reduces input_tensor by computing the mean of elements across the dimensions given in the axis.

Comparing the Custom Loss Function

Let’s assume in a multiclass classification problem, there are five class labels. There are two data points where the target classes are 4 and 1. We need to first convert this class vector (integers) to a binary class matrix using the to_categorical function. The predicted values are in a vector called y_pred, which is the softmax output of a classifier.

y_true = tf.constant(tf.keras.utils.to_categorical([4, 1])) y_pred = tf.constant([[0 , .7 , 0 ,0 , .3], [0 , .6 , .3 ,0 , .1]])

We will run the Custom_CE_Loss function mentioned above and TensorFlow’s CategoricalCrossentropy loss function and compare the results.

print('Tensorflow CE : ',tf.keras.losses.CategoricalCrossentropy()(y_true, y_pred).numpy()) print('My CE : ', Custom_CE_Loss ()(y_true, y_pred).numpy())

Both the results should come as 0.8573992.

Let’s implement this custom loss function in a Neural Network for a multiclass image classification problem. We will use Tensorflow’s pre-trained VGG16 model to classify CIFAR-10 images. The CIFAR-10 dataset consists of 60000 32×32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.

import tensorflow as tf from tensorflow.keras import datasets from keras.layers import Dense, Dropout, Flatten from keras.models import Model ​ (train_images, train_labels), (test_images, test_labels) = datasets.cifar10.load_data() #Normalize the pixel values train_images, test_images = train_images / 255.0, test_images / 255.0

The target classes are numerical values of the class label. We need to encode one-hot and make them float.

train_labels = tf.keras.utils.to_categorical(train_labels) test_labels = tf.keras.utils.to_categorical(test_labels) train_labels = tf.convert_to_tensor(train_labels, dtype=tf.float32) test_labels = tf.convert_to_tensor(test_labels, dtype=tf.float32)

Let’s load Tensorflow’s pre-trained VGG16 model. We will not include the top layers (full-connected layers) since we will train them for this task (CIFAR-10 classification). The convolution and pooling layers are all kept pre-trained and this is called transfer learning.

base_model = tf.keras.applications.vgg16.VGG16(input_shape = (32, 32, 3), include_top = False, weights = 'imagenet') base_model.trainable=False model=base_model.output model=Flatten()(model) model=Dense(4096, activation='relu')(model) model=Dropout(rate=0.5)(model) model=Dense(4096, activation='relu')(model) model=Dropout(rate=0.5)(model) model=Dense(10, activation='softmax')(model) model=Model(inputs=base_model.inputs, outputs=model) model.summary()

Let’s compile the model with this custom cross-entropy loss taking “accuracy” as metric. We will run the training for 10 epochs and evaluate the model on the test dataset.

loss=Custom_CE_Loss(), metrics=[‘accuracy’]) history =, train_labels, epochs=10, validation_data=(test_images, test_labels)) test_loss, test_acc = model.evaluate(test_images, test_labels, verbose=2)


This article taught us about loss functions in general, common loss functions, and how to define a loss function using Tensorflow’s Keras API. We wrote

We learned what the categorical cross-entropy loss is, how it works and how it generalizes the binary cross-entropy loss.

We learned to write a categorical cross-entropy loss function in Tensorflow using Keras’s base Loss function.

We compared the result with Tensorflow’s inbuilt cross-entropy loss function.

We implemented the custom loss function for a multiclass image classification problem using a pre-trained VGG16 model.

Like the cross-entropy loss recreated above, any other loss function can also be written easily in Tensorflow.


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Power Bi Themes: User Guide With Examples

Power BI is a powerful business analytics tool that helps you visualize and analyze data from various sources. One of the most useful features of Power BI is the ability to apply themes to your reports and dashboards.

Power BI themes allow you to customize your reports and dashboards to match your organization’s branding or personal preferences. You can choose from a variety of pre-built themes or create your own custom theme using the built-in theme generator. Once applied the themes, all visuals in your report will use the colors and formatting from your selected theme as their defaults.

In this article, you’ll learn how to apply themes to your entire report or dashboard to maintain consistency and branding across all your visualizations, making them look more professional and polished.

Power BI themes are standardized color schemes and formatting options that can be applied to your entire report, including visuals, text, and shapes.

With Power BI themes, you can easily apply design changes to your entire reports, such as changing the color scheme, font type, and background color.

Themes in Power BI can be created using a JSON file that contains all the color codes and formatting options.

Power BI themes have several benefits that can help you create professional-looking reports quickly and easily. Some of the benefits of using Power BI themes are:

1. Consistency: Applying a theme to your report ensures that all the visuals, text, and shapes have a consistent look and feel. This can help make your report more professional and easier to read.

2. Branding: You can use your company’s branding colors and fonts in the theme to create a report that aligns with your company’s brand guidelines.

3. Time-saving: Creating a theme once and applying it to multiple reports can save you a lot of time. You don’t have to manually change the colors and formatting options for each report.

4. Accessibility: Power BI themes also include accessible color schemes that can help make your report more accessible to people with color vision deficiencies.

Power BI themes are a powerful tool that can help you create professional-looking reports quickly and easily.

Whether you’re creating a report for your company or for personal use, using a theme can save you time and ensure consistency throughout your report. We’ll go over creating custom themes in the next section.

If you want to create a custom theme in Power BI, there are several factors you need to consider such as background, formatting, shapes, color palette, header, contrast, text color, and more.

Here are some sub-sections to guide you through the process:

The background of your report should be consistent with your corporate colors. To set the background color, go to the View ribbon and select the Themes section.

From there, you can choose from a range of predefined color schemes or just select Customize current theme to create your own Power BI theme.

Formatting is an essential part of creating a custom theme. You can change the font family, font size, and font color to match your brand.

Additionally, you can customize tooltips, wallpaper, and filter pane to give your report a cohesive look and feel.

Shapes can be used to highlight specific data points or to add visual interest to your report. You can customize the shapes in your report by using the theme JSON file.

If you want to create a custom theme, you can start by selecting a pre-built default theme that is close to what you are looking for. From there, you can use the “Customize current theme” option to make adjustments to the color palette, foreground, and data colors.

The Power BI community is an excellent resource for finding inspiration and getting help with your custom theme. You can browse the Theme Gallery to find pre-built themes or ask for help in the community forums.

Color is an essential part of any custom theme. You can use a color palette to ensure that all the colors in your report are consistent with your brand. You can also use the color palette to create contrast and highlight specific data points.

The header of your report is an excellent place to showcase your brand. You can customize the header by adding your logo or by changing the font and font color.

The color theme of your report should be consistent with your brand. You can create a color theme by selecting a base color and then using shades of that color to create contrast.

Contrast is an essential part of any custom theme. You can use contrast to highlight specific data points or to draw attention to important information.

Text color is an important part of any custom theme. You can use text color to create contrast and to make sure that your report is easy to read.

If you are new to creating custom themes, you can use a theme generator to help you get started. A theme generator will guide you through the process of creating a custom theme and will provide you with a range of options to choose from.

Creating a custom theme in Power BI can be a daunting task, but it is essential if you want to create a report that is consistent with your brand.

By following the guidelines outlined in this section, you can create a custom theme that is both visually appealing and easy to read. In the next section, we’ll explore using built-in themes.

If you want to quickly change the appearance of your Power BI report or dashboard, using built-in themes is a great option.

Here’s what you need to know about using them:

Built-in report themes come with predefined color schemes and are accessible from the Power BI Desktop menu.

They provide a quick way to change the look and feel of your report or dashboard without having to customize everything from scratch. You can also use built-in dashboard themes to change the appearance of your dashboard.

While built-in themes are a great starting point, they do have some limitations. For example, you can’t customize the background color or fonts of the visualizations in a report. You also can’t change every visual property using a built-in theme.

If you need more granular control over the look and feel of your report or dashboard, you’ll need to create a custom report or dashboard theme.

Power BI provides a variety of built-in themes that are accessible to everyone. These themes are designed to be visually appealing and accessible to a wide range of users. Some of the themes available include Azure, Colorblind, and Purple Rain.

If you need to create a report or dashboard that is accessible to users with visual impairments, you can use the High Contrast theme. This theme uses high-contrast colors to make it easier for users to distinguish between different elements in the report or dashboard.

If you want to create a custom report or dashboard theme, you’ll need to use the JSON format. This format allows you to specify the colors, fonts, and other visual properties of your theme. You can also use a theme generator to create a custom theme without having to write the JSON code yourself.

Using built-in themes is a quick and easy way to change the appearance of your Power BI report or dashboard.

While they do have some limitations, they are a great starting point if you don’t need a lot of customization.

If you need more granular control over the look and feel of your report or dashboard, you’ll need to create a custom theme using the JSON format.

Now that we have covered using the built-in themes, we’ll go over applying themes to Power BI themes.

By applying themes to your Power BI reports, you can maintain consistent branding, align with company styles, or create visually appealing reports that match your preferences.

Here are some things you should know about when applying themes to Power BI reports:

Power BI themes are standardized color schemes and formatting options that can be applied to your entire report, including visuals, text, and shapes.

You can use a theme to maintain consistency throughout your report without having to individually change each element. This section will guide you through the process of applying themes to your Power BI reports.

When you apply a report theme, all visuals in your report use the colors and formatting from your selected theme as their defaults.

This means that you can quickly change the look and feel of your report by selecting a different theme. You can choose from pre-built themes or create your own custom theme using the JSON theme file.

To apply Power BI report themes, simply open your report in Power BI Desktop and select the “Switch Theme” option from the “View” tab.

From here, you can choose from a variety of pre-built themes or import your own custom JSON theme file. You can also customize your theme by changing the color palette, font, and visual styles.

If you have any feedback or suggestions for improving Power BI themes, you can submit them to the Power BI product team through the Power BI Ideas forum. This is a great way to share your ideas with the Power BI community and help shape the future of the product.

For more information on Power BI themes, you can visit the chúng tôi website, which provides a comprehensive guide to using themes in Power BI. You can also refer to the official Power BI documentation for detailed instructions on applying themes to your reports.

In summary, applying themes to your reports in Power BI is a simple and effective way to maintain consistency and improve the overall design of your reports.

By selecting a pre-built theme or creating your own custom theme, you can quickly and easily change the look and feel of your report to match your brand or personal style.

If you want to learn more about Power BI themes, there are several resources available online that can help you. Here are a few that you might find useful:

Microsoft Power BI Community: The Power BI community is a great place to find information about Power BI themes. You can browse through the Themes Gallery to see examples of custom themes created by other users, or you can ask questions in the forums to get help with creating your own custom themes.

Color Themes: If you’re looking for inspiration for your Power BI themes, there are several websites that offer pre-made color schemes that you can use. Some popular options include Adobe Color, Color Hunt, and Coolors.

Theming: Theming is the process of applying a consistent visual style to your Power BI reports. This can include things like color schemes, fonts, and formatting options. By creating a custom theme, you can ensure that your reports have a consistent look and feel.

Color Blindness: When creating Power BI reports, it’s important to consider users who may be color blind. You can use color schemes that are designed to be accessible to people with color blindness, or you can use other visual cues (such as patterns or textures) to convey information.

Consistency: Consistency is key when it comes to creating effective Power BI reports. By using a consistent theme throughout your reports, you can make it easier for users to understand the information you’re presenting.

Custom Themes: If you want to create your own custom theme for Power BI, there are several tools available that can help. The Power BI Theme Generator is a popular option, as it allows you to create a custom theme based on an existing color scheme.

LinkedIn: If you’re looking to connect with other Power BI users, LinkedIn is a great place to start. There are several Power BI groups on LinkedIn where you can ask questions, share tips and tricks, and connect with other users who are passionate about Power BI.

Power BI themes provide a convenient way to customize the visual appearance of your reports. By applying a theme, you can ensure consistency across multiple reports and dashboards by providing a unified visual style.

It saves time and effort as you can easily apply a theme to a report instead of manually adjusting each formatting element. Themes also allow you to quickly switch between different visual styles or apply custom themes for specific projects or clients.

Whether you are a business user creating reports for your organization or a developer building Power BI solutions for clients, leveraging themes can enhance the overall look and feel of your reports, making them more engaging and impactful for the audience.

If you want to learn more about Power BI, you can watch the video below:

Power Bi App: Changing The Paradigm In Data Management & Transformation

However, these are now a thing of the past. Excel inefficiencies are no longer a reality for firms embracing Power BI. With the aid of the Power BI app, creating reports that are both visually appealing and scalable is now easy to produce.

Power BI has created a new paradigm in managing, analyzing, and distributing information.

Power BI not only impacts your organization from a visualization perspective, but it’s also a driving force in effective information management.

Power BI is revolutionizing information management and data transformation.

The entire Power BI suite has been built in a comprehensive way that allows integration between workflows and processes.

This is a list of the key points as to how Power BI is becoming a driving force in effective information management:

Now let’s discuss this one by one.

Power BI has the ability to effectively consolidate information from a range of sources.

It also has an amazing distribution system within its powerful visualization engine. You can create a report and then upload it to the cloud and enable users to access it anywhere in the world. You can also refresh and update data automatically.

If you were to access a tool of similar quality to Power BI five years ago, you would need to pay 10-20 times more than its current price.

But at present, tools such as Power BI have been democratized by giving them an affordable price point, including its supporting applications.

With the benefits it brings to the organization, it has been proven to bring a high return on your investment.

Power BI has almost an unobtainable learning curve. Anyone with an Excel or PowerPoint background can learn to build Power BI Reports.

Since Power BI is a Microsoft product, it has the ability to connect to other products from the same provider. You can connect to Office 365 and Microsoft Teams.

This allows teams and groups within your organization to have real-time discussions backed with real data and visualizations.

The ability to integrate various software together increases the value of all of these tools combined.

But with Power BI, there has been a significant improvement in business continuity. The ability to build robust models and reporting applications that can be passed from one employee to the next brings more scale to the workforce.

Power BI can also be integrated into the core of any organization. It can be connected to different IT infrastructures such as SQL databases and SAP.

The ability to integrate Power BI into different applications is second to none. There’s nothing prevalent out there that Power BI can’t connect to. There are APIs you can create and data pipeline tools that you can utilize to connect Power BI to basically any reporting and analytical software.

Over the years, Microsoft has completely committed to making Power BI a core part of businesses around the world. They’re putting a huge amount of investment into Power BI because they believe in its capabilities. Once Power BI is embedded into your organization, you’ll immediately see its value.

You may think that using Power BI ties you to Microsoft products. However, there are a variety of alternatives that you can use.

In addition, Microsoft’s Power Platform has gone through a few iterations over the last few years. Tools such as Power Apps, Power Automate, AI Builder, and Virtual Agents will work in combination with the entire Microsoft Suite. Other than Power BI, there isn’t any application out there that has this wide scope of vision around all of these data processing and automation tools.

Power BI is changing the paradigm in data management and transformation by providing a user-friendly interface for creating interactive and visually appealing reports and dashboards. With Power BI, users can easily connect to a wide variety of data sources, including Excel, SQL Server, and various cloud-based services.

Additionally, Power BI has a robust set of data transformation and manipulation features, allowing users to clean, shape, and model their data in a way that makes it easy to understand and analyze.

Hopefully, the 9 key points discussed in this blog have helped you realize the potential of Power BI and what it can do for you and your organization.

All the best,

Sam McKay

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