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Microsoft’s Power BI is a data analytics tool that can be used for interactive data visualization, using data from various sources such as relational and NoSQL databases, flat files, web servers, etc.
Power BI visualizations are easy to plot and come with a variety of formatting options. Power BI comes in two flavors: Power BI Desktop and Power BI Service, which is a cloud-based Power BI Interface. See this article on Power BI licenses for more details.
In this article, you will learn how to plot Power BI Desktop visualizations and how to format them.
You will study the following formatting options:
Note: You can download Power BI Desktop using this link.
Before you apply formatting to a Power BI Desktop Visualization, you have to create a visualization.
Once you run the Power BI Desktop application on your computer, you should see the following dashboard. The first thing you need to do is to import the dataset.
On the above dashboard, click on the “Get Data” tab from the top menu. In the dropdown list that appears, click on “Web”. You should see the following dialogue. In the URL field, enter the following URL: https://raw.githubusercontent.com/aniruddhgoteti/Bank-Customer-Churn-Modelling/master/data.csv.csv. Click the “OK” button.
You will see the following window. Here you can see some of the columns in the dataset. You can scroll horizontally to see the remaining columns. The dataset basically contains information about bank customers.
The data for the “Exited” column of the dataset was recorded 6 months after the data had been recorded for the rest of the columns. The “Exited” column basically shows the information based on customers from 6 months ago, regardless of whether or not the customers left the bank 6 months after that. A value of 1 in the “Exited” corresponds to the case where the customer left the bank, while “0” belongs to the customers who stayed.
Click the “Load” button to load the data into your Power BI application without manipulating the data.
You should see the following window. Here, on the right side, you can see a pane named “Fields” where you can see all your column names.
On the extreme left, you can see three options. The option at the top, which is highlighted in yellow, is named “Report” and is used to open reports view. Click on it.
To create a new visualization, you have to select a visualization from the “Visualizations” window, as shown in the following screen. For the sake of this article, we will create a “Clustered column chart”, a “Pie chart”, and a “Donut chart”. First, click the “Clustered column chart”, which is highlighted in the following screenshot.
Next, drag the “Exited” column from fields into the Value field. For the Legend field, drag and add the “Gender” column. Finally, for the Axis field, add “HasCrCard”, as shown in the following screenshot.
You should see the following graph created in the Report view. The plot contains columns that show the total count for the male and female customers who exited and who stayed in the bank. The columns are further grouped into two parts: those with credit cards and those without credit cards.
From the following graph, you can see that for both customers with and without credit cards, the number of female customers who left the bank is larger compared to male customers.
Let’s add another plot. This time, a pie chart. Click on the “Pie chart” option from the visualizations. Add a “Balance” column to the Values field, and a “Geography” column to the “Legend” field. You will see a “Pie” chart that shows the total balance of the customers belonging to different geographical locations.
Now you should see the two following visualizations in the reports window.
If you click on the area for the French customer in the Pie chart (the one defined by yellow square), the column chart is updated to highlight the values only for the French customer. The rest of the chart is made semi-transparent.
We created Power BI desktop visualizations in the previous section. Let’s now see how to format them.
To open formatting options, click on the graph that you want to format. Below the Visualizations options, you should see three options. The option in the middle, which is highlighted in yellow in the following screenshot, is the “Format” option. Click on it.
You should see formatting options that appear as shown in the following screenshot.
Let’s first change the color of the clustered column chart. Click the chart and then click the “Format” option. Next, click “Data colors”. Since you only have two types of column charts, one for male and one for female, you will see two color boxes: one for each column type, as shown below.
Change the color as per your liking. The following figure shows the updated colors for the clustered column chart.
In the same way, you can change colors for the Pie chart, as shown below.
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1594501200
Microsoft’s Power BI is a data analytics tool that can be used for interactive data visualization, using data from various sources such as relational and NoSQL databases, flat files, web servers, etc.
Power BI visualizations are easy to plot and come with a variety of formatting options. Power BI comes in two flavors: Power BI Desktop and Power BI Service, which is a cloud-based Power BI Interface. See this article on Power BI licenses for more details.
In this article, you will learn how to plot Power BI Desktop visualizations and how to format them.
You will study the following formatting options:
Note: You can download Power BI Desktop using this link.
Before you apply formatting to a Power BI Desktop Visualization, you have to create a visualization.
Once you run the Power BI Desktop application on your computer, you should see the following dashboard. The first thing you need to do is to import the dataset.
On the above dashboard, click on the “Get Data” tab from the top menu. In the dropdown list that appears, click on “Web”. You should see the following dialogue. In the URL field, enter the following URL: https://raw.githubusercontent.com/aniruddhgoteti/Bank-Customer-Churn-Modelling/master/data.csv.csv. Click the “OK” button.
You will see the following window. Here you can see some of the columns in the dataset. You can scroll horizontally to see the remaining columns. The dataset basically contains information about bank customers.
The data for the “Exited” column of the dataset was recorded 6 months after the data had been recorded for the rest of the columns. The “Exited” column basically shows the information based on customers from 6 months ago, regardless of whether or not the customers left the bank 6 months after that. A value of 1 in the “Exited” corresponds to the case where the customer left the bank, while “0” belongs to the customers who stayed.
Click the “Load” button to load the data into your Power BI application without manipulating the data.
You should see the following window. Here, on the right side, you can see a pane named “Fields” where you can see all your column names.
On the extreme left, you can see three options. The option at the top, which is highlighted in yellow, is named “Report” and is used to open reports view. Click on it.
To create a new visualization, you have to select a visualization from the “Visualizations” window, as shown in the following screen. For the sake of this article, we will create a “Clustered column chart”, a “Pie chart”, and a “Donut chart”. First, click the “Clustered column chart”, which is highlighted in the following screenshot.
Next, drag the “Exited” column from fields into the Value field. For the Legend field, drag and add the “Gender” column. Finally, for the Axis field, add “HasCrCard”, as shown in the following screenshot.
You should see the following graph created in the Report view. The plot contains columns that show the total count for the male and female customers who exited and who stayed in the bank. The columns are further grouped into two parts: those with credit cards and those without credit cards.
From the following graph, you can see that for both customers with and without credit cards, the number of female customers who left the bank is larger compared to male customers.
Let’s add another plot. This time, a pie chart. Click on the “Pie chart” option from the visualizations. Add a “Balance” column to the Values field, and a “Geography” column to the “Legend” field. You will see a “Pie” chart that shows the total balance of the customers belonging to different geographical locations.
Now you should see the two following visualizations in the reports window.
If you click on the area for the French customer in the Pie chart (the one defined by yellow square), the column chart is updated to highlight the values only for the French customer. The rest of the chart is made semi-transparent.
We created Power BI desktop visualizations in the previous section. Let’s now see how to format them.
To open formatting options, click on the graph that you want to format. Below the Visualizations options, you should see three options. The option in the middle, which is highlighted in yellow in the following screenshot, is the “Format” option. Click on it.
You should see formatting options that appear as shown in the following screenshot.
Let’s first change the color of the clustered column chart. Click the chart and then click the “Format” option. Next, click “Data colors”. Since you only have two types of column charts, one for male and one for female, you will see two color boxes: one for each column type, as shown below.
Change the color as per your liking. The following figure shows the updated colors for the clustered column chart.
In the same way, you can change colors for the Pie chart, as shown below.
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1595926953
In analytics, Tableau is the leading visualisation tool. Its rich analytical features and attention to data details are the reason behind its popularity. Power BI, on the other hand, is preferred by professionals who are more comfortable with Microsoft Office365. The users can connect Excel queries, data models and are able to report to the dashboard.
While the usage of both these tools might depend on many factors, here is a quick comparison of the two popular tools on various functionalities.
To get in-Depth knowledge on Power BI you can enroll for a live demo on Power BI online training
1. Performance
One of the crucial differences between Tableau and Power BI is that Tableau is an extensible platform which not only provides visualisations but also helps in gaining a better understanding of the data. Both the tools are excellent in visualisation but when it comes to the depth of data, Tableau helps an analyst to dive deeper into the data by performing “what-if” analysis on the data.
2. Flexibility
A user can deploy tableau on-premises, on the public cloud on Microsoft Azure, Amazon Web Services, or Google Cloud Platform, or on Tableau Online. While PowerBI, an upgradation of Microsoft Excel can be said as not so flexible as it serves only as a software-as-a-service model.
Power BI vs Tableau: A Data Analytics Duel - TechnologyAdvice
3. User Interface
Tableau is mainly designed keeping data analysts in mind. The richer analytical capabilities for visualisation helps an analyst gain insight into large datasets. It allows the user to create customised dashboards which can be considered as more of a pro-level. Microsoft PowerBI is simpler than Tableau and offers a better intuitive interface, especially for the beginners. This tool can be used by a coder as well as a non-coder.
4. Visualisation
Power BI focuses on data modelling and offers features of data manipulation and then provides data visualisation while tableau strictly focuses on data visualisation. Learn more from Power BI online course
5. AI-Powered
PowerBI tool with its Microsoft Flow and its AI builder tool can help in building apps with a layer of intelligence. With the advantages of Microsoft AI, the user can prepare data, build machine learning models and gain insights from both structured and unstructured data. On the hand, Tableau is working on natural language capabilities to simplify analytics and help the users who have no prior data analysis experience, known as Ask Data. Recently, Tableau has also announced the beta version of Explain Data, a new AI-powered feature to help users understand the “why” behind unexpected values in their data.
6. Price
PowerBI offers two subscription offerings, Power BI Pro and Power BI Premium. Power BI Pro is priced at .99 per user per month which is a self-service BI where user can collaborate, publish, share and perform ad-hoc analysis. Whereas Power BI Premium is priced at ,995 per month per dedicated cloud compute and storage resource. Here, the user can perform big data analytics, advanced administration and more.
Tableau, on the other hand, offers three subscriptions — Tableau Creator, Explorer, and Viewer. Tableau Creator is priced at user per month and it includes Tableau Desktop, Prep Builder and one creator license of Tableau Server. Tableau Explorer is priced at per user per month where they can explore the trusted data with self-service analytics and the Tableau Viewer is priced at user per month and here the user can view and interact with dashboards and visualisations in a secured way. These pricings are for teams and organisations where multiple users/viewing is required.
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JIRA Software provides bug tracking, issue tracking, and project management capabilities for teams and organizations. The JIRA content pack for Power BI helps you quickly import JIRA data so you can get an instant dashboard to analyze workloads, see how quickly you’re resolving issues, visualize velocity over time, and more. Power BI helps you quickly filter by project or component to generate new insights into your JIRA data.
To get in-Depth knowledge on Power BI you can enroll for a live demo on Power BI online training
To connect to the JIRA content pack, simply choose JIRA from the list of available content packs. You will be asked to provide your JIRA URL and credentials. Once the connection has completed, Power BI will automatically create an out-of-the-box dashboard, report, and dataset with data from JIRA.
dashboard
The dashboard for the JIRA content pack shows you key metrics about your workloads, velocity over time, and the breakdown of your bugs and issues by status and assignee. Clicking on any of the dashboard tiles will open the JIRA content pack report, where you can interact and explore your data.
You can slice the data in the report using the ‘Item Type’ slicer on the top, so you can find exactly the items you are looking for. Power BI reports are interactive, so if you select a ‘Fix Version’, a ‘Component’, or an ‘Assignee’, the rest of the report page will update per the selection.Learn more from Power BI online course
The report has a second page that focuses on the velocity of creating and resolving issues, and also shows the list of recently resolved items.
After the initial import, the dashboard and the reports continue to update daily so you are always seeing up-to-date data. You can control the refresh schedule on the dataset, and configure it to refresh at the exact times you choose.
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