business intelligence tools power bi free sample

Are you new to Power BI and you want to try it out, but you don"t have any data? Or maybe you"d like to see reports that illustrate some of the capabilities of Power BI. We"ve got you covered.

Power BI offers different kinds of samples for different purposes, including built-in samples and apps in the Power BI service, .pbix files, Excel datasets, and SQL databases. Here"s a collection of different samples:

Power BI report designers Miguel Myers and Chris Hamill created the Sales & Returns .pbix file to demonstrate many new features in Power BI, including buttons, drillthrough, conditional formatting, what-if, and customized tooltips.

Download the .pbix file and explore it in depth. Look "behind the curtain" to see how Miguel made it. This link opens the GitHub repo for Power BI Desktop samples. Select Download to download the Sales & Returns sample .pbix file to your computer.

The company obviEnce (www.obvience.com) and Microsoft teamed up to create samples for you to use with Power BI. The data is anonymized and represents different industries: finance, HR, sales, and more.

Each of these samples is available in several formats: as a built-in sample, as an Excel workbook, and as a Power BI .pbix file. If you don"t know what these things are, or how to get your hands on them -- don"t worry. This article explains it all. For each of these samples, we"ve created a tour. Tours are articles that tell the story behind the sample and walk you through different scenarios. One scenario might be answering questions for your manager, another might be looking for competitive insights, or creating reports and dashboards to share, or explaining a business shift.

The workbooks and data are property of obviEnce, LLC, and have been shared solely for the purpose of demonstrating Power BI functionality with industry sample data.

Let"s start with the built-in samples. The built-in samples are available in the Power BI service; you don"t have to leave Power BI to find them. These samples are each a bundle of one or more dashboards, datasets, and reports that someone creates and that can be used with the Power BI service. These built-in samples are still available, but are being deprecated. They aren"t available for Power BI Desktop.

Power BI imports the built-in sample and adds a new dashboard, report, and dataset to your current workspace. Use the samples to take Power BI for a test run.

Each of the built-in samples is also available as an Excel workbook. The Excel workbooks are designed to be used as a data source in the Power BI service or Power BI Desktop. If you"re an advanced Excel user, you can explore or edit the data models in the Power Pivot add-in to Excel.

You can use the files as data sources in Power BI Desktop, or Publish to Power BI from Excel to the Power BI service. When you publish, you choose one of these options:

(Optional) Want to understand how the data in these Excel workbooks gets converted to Power BI datasets and reports? Opening the Excel samples in Excel and exploring the worksheets provides some of the answers.

There"s only one Excel sheet, the Info sheet. It provides information about obviEnce, the company that created the sample, and explains how to see the data in Power Pivot.

Where"s the actual data? It"s in the Power Pivot data model. On the PowerPivot tab, select Manage. In Power Pivot, you can see the data in all the underlying tables, plus all the DAX formulas.

If you select Import, Power BI imports the sample workbook and adds it as a new blank report and dataset, in this case each named Procurement Analysis Sample.

Monitor system performance and usage with the enterprise BI capabilities of Power BI Premium. Adjust capacity as needed, allocate dedicated resources, and customize user settings and licenses for maximum efficiency.

Choosing the right business intelligence (BI) tool for your company can be a time-consuming process with many options that have similar features. A smart strategy for evaluating tools like business intelligence software is to have a clear understanding of why your business needs it and a solid set of criteria to help you review your choices.

Since the main function of BI is to help you analyze data for decision making, this is an important question. As you evaluate business intelligence tools, you’ll need to know details about your data. Is it structured or unstructured or both? Will your business intelligence software deploy your analytics on-premises, in the cloud, or a hybrid of the two? What pre-built connectors does it offer?

Much like with data integration, BI tools work seamlessly with software that users are already familiar with such as Microsoft Excel. Make a list of the commonly used tools that your BI software needs to connect with—don’t forget to include third-party apps, plug-ins, extensions, and connectors that your business regularly uses.

These are important factors to consider when evaluating business intelligence tools, especially if you work in a regulated industry like financial services or healthcare. Make sure your BI software includes features that: Allow IT to create a secure, governed environment.

Because business intelligence is versatile and can be used across the organization, many companies prefer a combination of self-service and enterprise BI tools that work for technical and non-technical users.

Next, take a look at how findings are presented through data visualization and data storytelling. These features typically use charts, graphs, and maps to surface insights that are hard to see on a spreadsheet. The best data visualization tools have an intuitive interface that lets users explore and present data in multiple ways, regardless of their technical skills.

For example, some BI tools let users make annotations right in the software, quickly embed reports into messaging and collaboration tools, and set permissions to distribute findings inside and outside of your organization.

Mobile features provide access to real-time data and allow you to make data-informed decisions on the fly when working remotely. Talk to your employees who work in the field or distributed locations to find out what level of mobile access they need. It could range from basic viewing of dashboards and reports to creating and editing analytics with mobile tools. You should also make sure the tool’s features are aligned to your company’s broader mobile strategy.

The goal is to find a cost-effective solution that provides business intelligence tools to your organization at the scale you need and has flexibility to grow with your organization.

As you evaluate BI tools, look for customer stories and case studies based on company size and industry. As you review customer challenges and solutions, you’ll get a better idea of whether or not this tool is effective for businesses that are similar to yours. You may also discover new ways to use business intelligence after reading the success stories of other organizations.

Preparing for your next BI developer interview? Check out these Power BI projects that will blow your mind with Power BI’s interactive dashboards, exceptional graphs and charts, and many more features.

We will look at some intriguing sample Power BI projects in this blog to help you better understand the role of Power BI in Data Science and how it can help businesses thrive.

MicrosoftPower BI is a Business Intelligence service that enables you to create visually rich and interactive dashboards and reports based on the raw business data acquired from various sources. Apart from the variety of apps, connectors, and services offered by Power BI, there are three basic elements integrated into Power BI-

Business users utilize these services to collect data and generate BI reports. These three components are all meant to assist in building, exchanging, and leveraging business insights in the most efficient way possible for any business. Some of the benefits of leveraging Power BI include-

Easy Interaction with Existing Applications: Power BI makes it far easier to implement analytics and reporting abilities since it seamlessly connects with your current business environment.

Customized Dashboards: The information dashboard can be tailored to meet the demands of a company. The application can simply include Power BI dashboards and reports to create a smooth user experience.

Advanced Analytics with R Integration:R programming language has several packages focusing on data mining and visualization. Data scientists employ R programming language for machine learning, statistical analysis, and complex data modeling. Data models created in R may be easily integrated into Power BI dashboards and turned into visualizations.

No Storage or Performance Limits: There are no memory or speed constraints when migrating an existing BI system to a robust cloud environment with Power BI integrated, ensuring that data can be fetched and analyzed efficiently.

There are various tools and techniques for analytics and machine learning in the fascinating and extensive realm of data science. Power BI is a high-level, all-in-one solution for data analytics in data science. Data science aids in the discovery of relevant and productive trends and insights. It involves analyzing the data and also assists us in identifying entirely new features in it.Business intelligence is sifting through data to extract meaningful organizational ideas and insights. BI enhances and strengthens the business infrastructure to get desired or projected results.

Many data sciences and analysis tasks can be automated with Power BI, eliminating the need for spreadsheets and static presentation tools. One of Power-most BI"s most impressive features is its ability to create stunning visualizations. The software is packed with excellent and eye-catching visualization templates. The integration of Power BI into Data Science holds great importance for businesses. This allows for smooth and effective data visualization, which plays a vital role in an organization’s success.

With the help of Power BI, visualization in Data Science can be taken a notch further. Businesses and Data Scientists rely heavily on Power BI-aided data visualization for various projects. Numerous visualization types and charts are available in Power BI for creating effective visualization fordata science projects.

There are two ways to generate visualization in Power BI. First, add items to Report Canvas from the right side pane. Another way you can do this is by dragging the fields from the right sidebar to the value axis under Visualization. By default, Power BI selects the table type visualization. To each axis, you can add as many fields as necessary. You can also click and drag your visualization to rearrange it on the reporting panel. You can easily toggle between various charts and visualizations from the Visualization window. Your specified fields are transformed to the new visual format as accurately as possible.

The first thing you need is data. Power BI can connect several data sources- Excel, Web, etc. The options from which data can be imported into the Power BI desktop are all visible once you click the Get Data icon. You can view the data in the Fields pane once it has been loaded.

After loading the sample data into the Power BI desktop, you can modify it with the help of Query Editor. Regardless of the data source, query editors are helpful for editing datasets. In the query editor, you can perform changes like renaming a dataset and removing one or more columns, among other things.

In Power BI, removing columns from the dataset or modifying the data types in the columns is relatively easy. You can remove columns by simply choosing the Remove Columns option after selecting the desired column. Likewise, the query editor makes it simple to perform a wide range of actions like removing and adding rows, transposing, pivoting, and splitting.

Once the dataset is complete and has undergone all necessary modifications, you can move on to creating the dashboard. Both bubble and shape maps are available for map visualizations in Power BI. To plot measure values, Power BI offers several combination chart types. Suppose you want to display overall sales and revenue on the same chart. The ideal option for this type of scenario is combination charts.

Additionally, the application has an analytics feature that allows you to draw lines for data visualization according to your preferences. Power BI also has the option to add various shapes, texts, and images when visualizing data.

This blog lists 15 Microsoft Power BI projects for you. We have categorized these Power BI examples into beginner, intermediate, and advanced levels. You can choose any of these power bi projects for practice to upskill yourself in the Data Science domain.

In this section, we have included some Power BI projects for students. These simple Power BI projects will enable you to understand business intelligence applications and build a successful career as a data scientist.

The customer churn analysis project is one of the easiest and most popular Power BI sample projects. Customer Churn Analysis reveals regional customers" product sales and profits. Analytical users can use it to analyze regional business growth across geographies to gain valuable insights and distribute profits among customers. They can receive extensive data by using the right visualizations and data structure. The project includes regional cash inflows and product-specific customer churn over time.

This sales data analysis project entails analyzing a company"s sales data and indicating profit by product, sales, and other significant factors that might influence the company"s performance. You can useMicrosoft"s sample dataset. The data set must be connected to Power BI Desktop to remove irrelevant data before visualizing and exporting the filtered data as dashboards. The dashboard could leverage Power BI visualization types such as Pie Charts, Bar Charts, Doughnut Charts, Funnel Charts, etc.

Use theMarketing Analytics dataset available on Kaggle for this beginner-level project. For the data visualization dashboard, you can explore many of the Power BI visualization types, such as Bar Charts for category-wise expenditures, Column Charts for campaign success rate, Smart Narratives for displaying the key highlights of the campaign, Bubble Charts for customer-wise spending, Cards for showing individual data insights, etc.

Financial performance analysis is one of the most intriguing Power BI project ideas for beginners. This business intelligence project approach is based on optimizing financial analysis for a firm that provides accounting services to clients who seek timely delivery of critical financial reports. You can set up the analysis to quickly access reliable financial data. The project might be used to: migrate traditional financial reporting from Excel to current BI dashboards and provide customers with an effective tool to track their financial health and productivity.

Refer to themulti-company financial dataset available on Kaggle. You can leverage Power BI data visualization in this project for three different cases-

You can refer to thepharma sales dataset available on Kaggle. For the data visualization on Power BI, you might use Tables for displaying the therapeutic group-wise sales, Column Charts for monthly sales trends; Bar charts for top and bottom-ranking cities; and also, you can include Treemaps, Cards, Smart Narratives, etc. You can also check out the Microsoft Power BI community for some beginner-friendly power bi project examples.

If you’re already well-versed with the Power BI data visualization tool and are willing to strengthen your data analytics skills further as a Data Scientist, here are some power bi projects for resume-

The first Power BI project idea we have come up with is Anomaly Detection in Credit Card Transactions. Anomaly Detection is a machine learning technique for detecting unusual things, events, or observations that differ considerably from the rest of the data and look suspicious. You can implement this machine learning method in three ways- supervised (for labeled datasets), semi-supervised (for normally trained datasets), and unsupervised (for datasets without any labels).

For this project, you can use thecredit card dataset by Delaware available on their open data platform itself or the credit cardfraud detection dataset from Kaggle. You must first import the dataset into the Power BI desktop, maybe via a web connector. You can then leverage Power BI to train your anomaly detector or use a pre-trained model. To label outliers in Power BI, you"ll need to run a Python script in the Power Query Editor and use the get_outliers() method. Finally, Power BI Dashboard can be used to visualize it. You could also train your anomaly detection model in any IDE or Notebook and then pass it to Power BI for labeling. You can do the data visualization in the Power BI dashboard with the help of Line Charts, Bubble Charts, TreeMaps, etc.

In this business intelligence project, you can work with themedical cost personal dataset from Kaggle. The business problem involves an insurance company that wishes to improve its cash flow projections by precisely estimating patient charges through demographic and primary patient health risk variables at the time of hospitalization. The first step is accessing Power BI Desktop, loading the dataset, and replicating it. The Python script may then be executed in Power Query, where the compare_models() method can be used to train different models, compare them, and evaluate their performance data. You may also use the automl() function to find the best-performing model out of all of them. For the resulting dashboard, you can leverage Power BI dashboard features such as Bar Charts, Bubble Charts, Tables, etc.

One of the most helpful Power BI project ideas is the Global Health Expenditure Analysis. This project idea is based on implementing clustering analysis in Power BI using PyCaret. Clustering is a method for bringing data items together that have similar features. These classifications help study a dataset, detect patterns, analyze data, and data clustering help in identifying underlying data structures.

In this case, use the current health expenditure dataset from the WHO Global Health Expenditure database. From 2000 to 2018, the dataset includes health expenditure as a percentage of national GDP for over 200 nations. Also, you could use the K-Means clustering algorithm for the clustering analysis. Visualize the cluster labels in Power BI Dashboard to gain insights after you have loaded the dataset in Power BI Desktop and trained your clustering model in Power BI. For the summary page dashboard, you might choose visualization chart types such as Filled Maps, Bar Charts, etc., while for the detailed visualization, you can use Point Maps.

This project concept entails evaluating loan application data to find abstract "topics," which are then used to assess the impact of specific topics (loan types) on the default rate. It is based on implementing the Latent Dirichlet Allocation (LDA) topic model in Power BI. Topic modeling aims to automatically analyze a collection of documents and determine their abstract ‘topics’.

For this project, you can use theKiva dataset on GitHub, which covers loan data for 6,818 accepted potential borrowers. The loan amount, nationality, gender, and some text data from the borrower"s application are included in the dataset. Once you have loaded the dataset in Power Bi desktop, trained your model, and the topic weights are added to the original dataset in Power BI, you can visualize it in the Power BI dashboard by employing the Word Cloud feature, Pie Charts on basic maps, Bar Charts, Scatter Charts, etc.

The movie sales visualization project is one of the most exciting Power BI project ideas. This project aims to take a dataset that shows movie sales over time and turn it into an interactive visual experience. You can use theIMDb dataset for 2006 to 2016, available on both IMDb and Kaggle. The dataset includes a list of movies having an IMDb score of 6 or higher and the parameters Budget, Gross, Genre, and Scores.

You can create a custom Radial Bar Chart and use Slicers to pick Genre, Country, and score range to be integrated directly into PowerBI. This would display parameters such as Average Score and Gross Collections for the selected set. Plotting a Histogram on the score variable using year and genre as slicers will show the frequency distribution of the IMDb scores. A KDE plot can provide a density graph and insights into the average rating for a specific genre and distribution for a given timeframe.

Lastly, we have listed some of the best power bi projects for professionals who need some interesting power BI projects with dataset to try their hands on.

For this project idea, you can use theAirline delays and cancellation dataset available on Kaggle. The dataset includes multi-year airline data from 2009 to 2018 to provide more time-series insights. For flight analysis, you can use Power BI visualization options like Cards, Bar Charts, Flow Maps, TreeMaps, and Tornado Charts. For passenger feedback, you might prefer to use Bar Charts, Column Charts, or Cards.

Covid-19 Insights Analysis is one of the most popular Power BI project ideas among individuals. The project aims to thoroughly overview the Covid-19 pandemic"s essential parameters, the latest situation, and detailed country-level evaluations. You can create a dashboard that gives valuable information regarding cases (active, deceased, or recovered), mortality, and recovery rates by nation and timeframe. Also, the dashboard might even include a management summary of the most important KPIs and a thorough analysis of individual report pages.

Refer to theCovid-19 dataset available on Kaggle for this project idea. As for the Power BI data visualization features, you can use- Bar Charts, Point Maps, Line Charts, and Column Charts for the overview page; Doughnut Charts for category-wise case analysis; and Decomposition Trees for country-wise case analysis. You might also use Heat Maps to enhance your project’s dashboard visualization.

For this project idea, use theSeattle building permits dataset from Kaggle. You can perform Power BI data visualization with the help of Regional Maps, Pie Charts, Bar Charts, Tables, Cards for the main page, Bar Charts, and Line Charts for depicting contractor competitions and category-wise growth, etc.

One of the most unique power bi projects ideas is the Global Energy Trade Analysis. This project concept includes various topics concerning global energy exchange and production. It addresses several topics, such as the expansion of wind energy, energy consumption as a different basis for comparing national economies, etc.

For this unique project idea, use theinternational energy statistics dataset from Kaggle. The resulting dashboard could display total energy statistics on production, exchange, and usage of primary and secondary energy, conventional and non-conventional energy sources, and new and renewable energy sources. For the dashboard, you can use Power BI visualization types such as Bar Charts, Flow Maps, Cards for the overview page, Ribbon Charts, Treemaps, Bar Charts for the energy production and exchange pages, etc.

Use thelife expectancy dataset by WHO on Kaggle for Life Expectancy Data Analysis. Power BI visualization types such as Gauge Charts, Pie Charts, Line Charts, and Point Maps can be used for the overview page, while Tornado Charts, Doughnut Charts, Treemaps can be used for depicting country-wise data, etc.

This project entails implementing an end-to-end Twitter data analysis/ETL pipeline. For this Power Bi project idea, use the Twitter data from Github. After extracting the data, you will transform it from JSON to CSV and create all the necessary derived attributes. You will then use NLP analysis to classify the tweets" content and determine their sentiment score. Once you finish the ETL process, you can move on to visualize your data using Power Bi reports. For creating the dashboard, you will use pie charts, bar graphs, line charts, tree maps, doughnut Charts, etc.

This unique Power BI project entails visualizing various information related to multiple OTT platforms such as Netflix, Hotstar, Amazon Prime, etc. You can access this project"s entire OTT media platform dataset from Github. Use the Query Editor in Power BI for data cleaning and preparation. Once your data is ready for visualization, you can display the visuals using various plots, graphs, cards, etc.

You can work with the AdventureWorks data available on GitHub for analysis & visualization. Perform the query editing in Microsoft SQL Server Management Studio and use Power BI for the visualization part. Also, use MS Excel and Power BI"s query editor for analysis.

These real-time power bi projects will help beginners and professionals upskill and master the ability to integrate business intelligence into Data Science. By working on these project ideas, you will gain a deeper understanding of leveraging Power BI for a data-driven approach to various data science industries and becoming job-ready. In case you are looking for some free Power BI projects for practice with solutions, you can head to open-source platforms likeGitHub orKaggle. ProjectPro offers more than 250 end-to-end project solutions around Data Science and Big Data, including some interesting data visualizations.

But it is not enough to collect all of this information. Companies will need to analyze it — and that is where data science and business intelligence tools come in. Open-source software is overtaking proprietary platforms, so I have compiled a comprehensive list of free and open-source BI tools in alphabetical order.

Jedox provides powerful planning and beautiful reporting on every desktop and mobile device. The platform aims to eliminate the headaches of Excel by providing a rich, interactive experience with real-time modeling. The cloud and premium on-premise versions have 14- and 30-day trials, respectively.

KNIME is an open source platform for data analysis that comes with more than 1,000 modules, hundreds of ready-to-run example analyses, a set of tools that is integrated into the software, and a lengthy selection of algorithms that users can chose to incorporate. KNIME is used by data scientists and BI executives.

The Pentaho Reporting platform is a suite of the company’s open source reporting tools that lets users create historical data reports in PDF, Excel, HTML, text, rich-text file, XML, and CSV formats. The computer-generated reports can take data from multiple sources and make it easier to understand.

Microsoft Power BI offers a free version of the platform with a 1 GB per user data capacity limit and once-per-day data-refresh schedule. Power BI’s dashboards can present insights from Salesforce, Google Analytics, and other platforms on desktop and mobile devices. Users can also query the software with natural language (in other words, plain English).

SpagoBI is an open source business intelligence suite that includes reporting, charting, and data-mining tools. It is developed by the Open Source Competency Center of Engineering Group, a large Italian software and services company that also offers professional services such as user support, maintenance, consultancy, and training.

In 2008, SQL Power Group open-sourced Wabit, which provides a single framework for all ad-hoc queries and OLAP analyses that works with almost any database platform. Wabit’s drag-and-drop interface can also tap into streaming data to create real-time dashboards. The community edition is free to deploy.

The benefits of Business Intelligence and Data Visualization are becoming increasingly evident to business organizations around the world. Power BI is a Business Intelligence service that is employed by many of these organizations to implement these useful techniques on their business data, maintained in the Cloud Data Warehouse and numerous other sources. Users use Power BI Reports to visualize their data and perform analysis.

After introducing Power BI and its various formats, in this article you will learn in detail about different parts of Power BI Report, some Power BI Reports Examples, and differences between Power BI and Tableau Dashboards.

Power BI is a collective group of an assortment of services and cloud-based apps that can help organizations at all levels to manage, analyze data from different data sources easily with the help of a very user-friendly interface.

The basis of Power BI lies in Microsoft Excel but is very powerful and provides hundreds of features making it a very useful tool for every level of organizations.

A Power BI report provides a very detailed overview of any dataset or data stream of interest in the form of different visualizations, filters, and parameters. It can vary depending upon one’s job role i.e. whether it is managing level or executive level.

Hevo Data,a No-code Data Pipeline, helps transfer data from 100+ sources to a Data Warehouse/Destination of your choice and visualize it in your desired BI tool such as Power BI.

Power BI provides a very detailed Financial Analysis Reporting including as many Financial Parameters as possible to understand the financials of a company & project the future directions.

Power BI helps in creating very detailed Digital Marketing Reports that involve all the important information about Digital Marketing parameters including Bounce Rate, CPM, CTR, Impressions, Conversions, etc.

Apart from the above-mentioned questions, there are many others that can be answered through Power BI reports. You just need to integrate your data source properly.

Tableau platform is primarily known for the vast data visualization functionalities that it offers mainly dashboards whereas Power BI handles a large number of data points to offer data visualizations with the help of powerful reports.

Overall, Power BI provides a very large number of functionalities for data visualization and reporting purposes. In this article you learned in detail about different parts of Power BI Report, some Power BI Reports Examples, and differences between Power BI Dashboards.

Hevo Data, a No-code Data Pipeline helps you transfer data from a source of your choice in a fully automated and secure manner without having to write the code repeatedly. Hevo with its strong integration with100+ sources & BI tools, allows you to not only export & load Data but also transform & enrich your Data & make it analysis-ready in a jiffy.

Data Visualization plays a pivotal role in Data Analysis as it helps all types of users build reports and dashboards to analyze data from multiple sources. One such BI (Business Intelligence) tool from Microsoft is Power BI. Power BI Dashboard Examples are some of the easiest and interactive tools for visualizing data.

Power BI Dashboard Examples aim to provide interactive visualizations and Business Intelligence capabilities with a UI simple enough to enable end-users to create their own reports and dashboards. As they are part of the Microsoft Power Platform, they can easily integrate with other Microsoft technologies and help you gain valuable and actionable insights from your customers.

In this article, you will be given a comprehensive overview of the Top 10 Best Power BI Dashboard Examples along with their features. You will also be given a brief introduction about Power BI and the importance of these dashboards so that companies can leverage the right dashboards to help them design accurate reports and dashboards. Read along to find out about the Best Power BI Dashboard Examples.

Power BI is a Business Intelligence tool from Microsoft. It helps users to analyze data present in various sources and build reports and dashboards based on that. Power BI is available as a stand-alone desktop application as well as a completely managed cloud-based service. While Power BI desktop comes as a free application, Power BI service is a paid offering based on subscriptions. Microsoft also offers Power BI mobile for people who want to keep an eye on the data on the move. Another offering is the Power BI embedded which helps developers embed Power BI analytical abilities into custom web applications. It integrates seamlessly with most of the enterprise Microsoft offerings and azure active directory-based authentication.

Power BI Dashboard Examples have a versatility that not only comes from their analytical abilities but also from their ability to connect most of the common databases even outside the Microsoft ecosystem. Organizations use Power BI for asking questions about various types of data like Sales Data, Marketing Data, or even Finance Data.

Power BI Dashboard Examples are nothing but a collection of visualizations that keep updating when the underlying data changes. They have development functionalities that allow visualization widgets to be dragged and dropped to the canvas. They also allow users to drag and drop fields directly into the canvas.

The software is intelligent enough to select the right visualization and then display it accordingly. With Power BI offering a large variety of visualizations including Cards, Tables, Geographical Plots, Different kinds of Charts, KPI Visualization, etc, the Power BI Dashboard Examples’s use cases are limited only to the creativity of the developer.

Its completely automated Data Pipeline offers data to be delivered in real-time without any loss from source to destination. Its fault-tolerant and scalable architecture ensure that the data is handled in a secure, consistent manner with zero data loss and supports different forms of data. The solutions provided are consistent and work with different BI tools as well.

Organizations use Power BI Dashboard Examples to analyze data in various domains. For example, a Sales Manager may use Power BI Dashboards to understand the performance of his Sales team. A Top-Level Executive may use it to visualize the profitability of the organization. A Digital Marketer may use it to understand the efficacy of his Social Media Campaigns.

You will now go through a curated set of Power BI Dashboard Examples that are used in Sales, Marketing, and Finance domains. All the Dashboards mentioned below can be found in Data galleries at the Power BI community portal.

This dashboard helps Senior Management understand how the company is performing in Sales compared to the previous year. It also gives information about the performance of different product segments and what channels are succeeding in bringing the revenue. The dashboard allows one to view the KPI’s (Key Performance Indicators) both for revenue and profit. You can also check out Power BI KPIto know more.

This dashboard is a variation of the Sales Analysis Dashboard that focuses more on the Sales Channels. These types of Power BI Dashboard Examples are particularly useful for organizations with an E-Commerce presence.

These Power BI Dashboard Examples are for organizations that market their products through mass emails. These dashboards display the proportion of emails that were delivered, clicked, and opened. The data for these dashboards generally comes from campaign management tools like Hubspot. They also provide how these indicators were changing over the relevant period.

These types of Power BI Dashboard Examples depict the fundamental Financial Indicators of the organization. Finance Dashboards display indicators like Revenue, Profit, Earnings before tax, Inventories, Securities, Accounts Payables, etc. The template can be found here.

This article gave a comprehensive list of the Top 10 Best Power BI Dashboard Examples and also gave an introduction to Power BI and its importance to any organization. Overall, Power BI Dashboard Examples help companies better visualize their data in order to gain actionable insights from their customers.

To make the best use of these dashboards, organizations need relevant data, and there lies a big challenge. Even though Power BI supports most of the common databases, it does not handle cloud-based data sources outside the Microsoft ecosystem well.

For example, to make use of the Email Campaign Dashboard, you will need support for fetching data from Sources like Pardot or Hubspot. In case you are constrained by the data source support or Power BI, you can consider a cloud-based ETL tool like Hevo that can bring data from almost any data source to PowerBI.

Hevo offers a faster way to move data from 100+ data sourcessuch as SaaS applications or Databases into your Data Warehouse to be visualized in a BI tool such as Power BI. Hevo is fully automated and hence does not require you to code.

There’s a broad spectrum of business intelligence (BI) tools out there, from highly technical and powerful platforms to user-friendly and lightweight dashboard builders. Choosing the right one depends on where your business is today, where you want it to end up, who needs access to the data, your tech stack, and so on.

Microsoft’s Power BI is a business intelligence tool whose main differentiator is the fact that it sits within the larger Microsoft ecosystem, integrating with Excel, Azure, Access, and more. While these integrations are a plus for many, Power BI has proven to be difficult for some to learn—and it has some unique quirks.

It’s not the easiest business intelligence tool to set up and maintain, so teams with little capacity to spare may want to look elsewhere. Once set up, it has a reputation for being more malleable than other massive business intelligence tools. One user on Quora used this comparison: Tableau is like iOS, while Power BI is like Android. The result is good modeling functionality that, again, requires some expertise to set up and utilize.

If you’re fully fluent in Excel, you won’t have to work too hard to understand Power BI. As Alainia Conrad of SelectHub says, “Users with experience in [Excel] will be able to adapt to [Power BI].”

Users of Power BI tend to praise its ability to handle the flow of data as well as its modeling capabilities. In their comparison between Power BI and Tableau, user Grovbolle on Reddit says, “Power BI is very strong on the data modeling and infrastructure, a bit less on visualization.”

Power BI has a steep learning curve, and it requires expert knowledge to set up. “You need to work with an IT person to interface Power BI with existing systems,” says Shreshthi Mehta in her TrustRadius review. On G2, Xinito L. says, “This is not an application for amateurs.”

It also has some quirks that’ll cost you time, as the good people of Reddit are quick to point out in r/PowerBI. Here is the top-rated post of all time in that community:

Jason Harris at Panoply explains it this way: “While [Chartio] may not have all the functionality that your data analysts are looking for, it’s well suited to business users.” On G2, one executive in financial services says, “[Chartio] has relatively fewer features than the other primary tools out there, like Tableau. I think in part, that’s what enables it to be user-friendly, so it’s a trade-off rather than a downside.”

Looker is a powerful tool for modeling data using its proprietary language, LookerML, that has limited visualization capabilities and data inputs. Google Cloud Platform acquired it in 2019, moving it into the Google walled garden, which means it may get combined with Google Data Studio in the near future,as explained in-depth here.

LookML provides a powerful modeling layer that some veterans enjoy. On Reddit,user rlaxx1 says, “The modeling layer allows you to basically turn SQL into object-oriented code.”

Google Data Studio has perhaps the lowest bar of entry for the business intelligence tools listed here. But it lacks deeper data functionality, relying on other Google services like BigQuery to fill in the gaps.

Tableau Desktop is the standalone data visualization tool from Tableau, a legacy giant among other business intelligence tools. Tableau was one of the first BI tools to lower the bar for entry into data visualization but still remains out of reach for the average business user due to its older feature set designed for large, expert data teams.

It’s very flexible in how you manipulate and use data, making it a powerful data visualization tool. One Capterra reviewer says, “The quality and variety of graphics that can be created with Tableau is vast, and that’s the best part of it.”

While Tableau has some very good legacy BI features, like visualization, it lacks some important features other business intelligence tools have innovated that have become fairly commonplace. Tristan Handy, CEO & founder of Fishtown Analytics, puts it this way: “Tableau, for all its impressive visualization capabilities, can’t really deal with production data: its drag-and-drop capabilities just don’t allow users to express the complicated business logic that is required in real-world BI.”

In particular, Domo targets the busy executive with its mobile-first philosophy and its segmentation tools by team. It’s good for large companies looking for data distribution over data analysis that can afford the sticker price and the time spent to get Domo’s system fully up and running.

Its laser focus on dashboard tools makes it a lifesaver for some, but a major pain for those looking todive deep into data. For companies with a solid data infrastructure already in place, it may be a good fit to help business users visualize data, but it’s not for those who need a tool dedicated to data.

It can also leave behind power users, as Peter Weinberg of Panoply says: “Advanced SQL users may find it tricky to learn the SQL-but-not-quite style data interface, but it’s not designed for them.”

All the business intelligence tools listed here have some form of a free trial, so it’s easy to dive in and try them out. Each has its strengths and weaknesses, but we encourage you to try out as many as you can. We guarantee one will feel much more natural to your business than the others.

Reports and dashboards across devices:Dynamic visuals are organized into interactive reports and dashboards, similar to other tools in our lists, and you can access them also on mobile and tablet devices (both Android and iOS).

Integration with other applications:You can integrate SAS with Microsoft Office applications such as PowerPoint, Word, SharePoint or Excel with their Office Analytics solution which enables you to view your results directly in Microsoft Office Suite.

SAP BusinessObjects is a business intelligence platform designed for comprehensive reporting, analysis, and data visualization. They provide Office integrations with Excel and PowerPoint where you can create live presentations and hybrid analytics that connects to their on-premises and cloud SAP systems. They’re focused on business categories such as CRM and customer experience, ERP and digital core, HR, and people engagement, digital supply chain, and many more. To be accurate, more than 170M users leverage SAP across the world, making it one of the largest software suppliers in the world. On Capterra, the company obtained a review of 4.2 stars, while in G2Crowd 3.8 stars with over 400 reviews, confirming its well-established place in the market since 1972.

Self-service, role-based dashboards:Analytics applications and data visualization are focused on self-service capabilities, similar to other tools, where you can build your own role-based dashboards and applications to assess risks, for example.

Integration with Office:By using Microsoft Excel with SAP, you can analyze larger volumes of data, and embed analytics in PowerPoint, making this solution easily integrated with Office.

Domo is a business intelligence software comprised of multiple systems that are featured in this platform, starting with connecting the data and finishing with extending data with pre-built and custom apps from the Domo Appstore. You can use Domo also for your data lakes, warehouses, and ETL tools, alongside R or Python scripts to prepare data for predictive modeling. Similar to other tools, you can connect the data across your enterprise, utilize their machine learning and artificial intelligence capabilities while enabling users to explore the data on their own. With a firm 4.2 stars rating on Capterra and an even better 4.4 in G2Crowd, this BI application is also recommended by many users across the world, even though the company is one of the younger on our list – founded in 2011.

Numerous pre-built cloud connectors:Data integration works similarly to other tools, as mentioned; you can connect to more than 1000 pre-built cloud connectors, on-premise with Domo Workbench, file upload such as Excel or Google Docs, proprietary systems, and federated connectors that will enable you to query the data where it’s hosted.

Magic ETL feature:Data transformation tools will enable you to prepare your data with a drag-and-drop Magic ETL, as Domo calls it, without the need to learn SQL.

Mr. Roboto as an AI engine:Predictive analysis is powered with Mr. Roboto, Domo’s AI engine, which enables data scientists to create predictive models and utilize artificial intelligence, machine learning, natural language processing, and other AI technologies that alert and notify about changes in KPIs, for example.

Oracle Business Intelligence is a portfolio of technology and applications with a focus on providing end-to-end solutions to help businesses optimize their performance and empower them to make faster and more informed mobile-enabled decision-making. Oracle has 4.2 stars rating on Capterra and a 4.0 in G2Crowd, and they offer a wide ray of features for data management such as machine learning, artificial intelligence, integrated array of querying, reporting, mobile analytics, among others. Since its foundation in 1977 Oracle’s mission has been to provide businesses with the tools to efficiently manage their data in a comprehensive and agile way.

We continue our BI tools list with Zoho Analytics. Although the company offers many products ranging from CRM, bundles, and apps, here we focus on their BI and analytics solutions as the most relevant for our topic. With more than 500 integrations for your business apps, more than 10 000 customers worldwide, and a strong 4.3 stars rating on Capterra and 4.2 on G2Crowd, this is one of the business intelligence reporting tools worth taking into consideration.

Blending and visualizing data:Similar to other tools on our list, their most prominent features focus on blending data from multiple sources, and visualizing them through reports and dashboards via their drag-and-drop designer. But not only, as you can also feed data from their online storage service Zoho Docs.

Intelligent assistant Zia:If you’re looking for artificial intelligence-powered analytics, Zoho has created Zia, an intelligent assistant that you can ask questions in form of natural language, and you will immediately receive the answer in the form of reports and KPI widgets. Zia is based on natural language processing and machine learning technologies to help the user search for data faster.

MicroStrategy is an enterprise business analytics software and mobility platform focused on hyperintelligence, federated analytics, and cloud solutions. Their mobile dossiers enable users to build interactive books of analytics that render on iOS or Android devices, with the possibility to extend the MicroStrategy content into their apps by using Xcode or JavaScript. You can download a sample app, MicroStrategy Mobile, or the Library app where you will enable you to deploy analytics on-the-go. Both Capterra and G2Crowd reviewers rate this tool with 4.2 stars, hence, this is one of our examples of business analytics tools having strong references on the BI market.

Federated analytics:It provides a common data glossary, no matter the tools you use, built on an enterprise semantic graph that indexes all the disparate data systems and enables visualizations of the same data.

Integration with voice technology:Powered by natural language processing and machine learning, you can also integrate voice technology and chatbots such as Alexa or Google Home.

The next tool on the list is Dundas BI. With a 4.5 rating in Capterra and 4.4 in G2Crowd, this business intelligence platform aims to make the entire analytics process more simple and flexible via interactive dashboards, reports, and visual analytics. The Software was founded in 1992 as a solution for data visualizations with the name of Dundas. In 2015, after many recognitions in the visualization industry, the tool mutated to Dundas BI an end-to-end analytics platform that empowers every level of user to visualize and analyze data with features such as report generation, ad hoc queries, data discovery, among others.

GoodData is a business analytics software that provides the tools for data ingestion, storage, analytic queries, visualizations, and application integration. You can embed their analytics into your website, desktop, or mobile application or create dashboards and reports for your daily activities, without the need to obtain a Ph.D., as stated on their website. Also, one of the younger software solutions on our list, founded in 2007, GoodData received a stable 4.3 stars review on Capterra paired to a 4.0 on G2Crowd positioning them as one of the great tools to manage your business.

A modular data pipeline:They also offer a modular data pipeline for fast data integration with an on-premise or cloud warehouse, no matter if the data is structured, semi-structured or unstructured. You can also use tools such as SQL, Python, R or Ruby for flexible data processing.

QlikView is one of the BI applications offered by Qlik as part of its data analytics platform focused on rapid development and guided analytics applications and dashboards. It’s built on an Associative Engine that allows data discovery without the need to use query-based tools, eliminating the risk of data loss and inaccurate results. With a decent rating of 4.3 stars on Capterra and 4.1 on G2Crowd, users are quite satisfied with this product and its features, making it one of the top BI tools on our list.

Developer’s platform:Various tools and resources are provided for developers, such as the Qlik Branch Community, the Qlik Knowledge Hub, the Qlik Branch Playground (which they announced soon to be retired) and the Qlik Core documentation.

Yellowfin signals via smartphone:Benefit from the automated detection of trends and anomalies in your data thanks to the Yellowfin signals, which are based on powerful, AI-controlled algorithms and enable immediate, personalized notifications directly to your smartphone.

Big data is all around us and steadily increasing with each year. By utilizing BI and business analytics tools, you stand to reap great rewards – your data management will become more cohesive, stable, agile, and predictable with numerous features that these tools have on offer. We aimed to help you consider the best tools on the market, and we hope we have provided an extensive review of each product that will inspire you to start exploring business intelligence tools and find a perfect fit for your company or department.

To help you process and remember all the information you just received, below we provide you with a visual summary of our 14 best business intelligence tools for 2022.

Data has become a ubiquitous part of business today, making it essential for businesses to understand how to gain value from the wealth of raw data available to them. The right information must be gleaned from the data and presented clearly for making well-informed business decisions. Because of this, business intelligence (BI) systems have gained tremendous traction that can assist an organization in discovering useful information, suggesting conclusions, and supporting decision-making. BI is a system that analyzes data, provides actionable information, and helps users to take informed business decisions. As a proven technology leader, Microsoft has propelled itself to the forefront with the introduction of its powerful analytics tool, Power BI.

Microsoft’s Power BI toolkit transforms your data into meaningful information, making it one of the most popular business intelligence tools in the world. The increasing popularity of Power BI has led to an increased demand for Power BI professionals and business analysts.

Are you intrigued? If so, we’ve created this detailed guide for you. In this article, we will discuss some Power BI projects ideas that you can use to boost your chances of becoming a Power BI professional. But before we start exploring Power BI projects and Power BI projects for practice, let’s take a look at exactly what Power BI is and why it is so important.

Power BI is a Business Intelligence and Data Visualization tool designed to analyze, visualize, and process enormous volumes of raw business data and transform them into actionable and interactive insights that help business managers, corporate executives, and other users to make better informed business decisions. Raw data can be stored in an Excel spreadsheet, cloud-based databases, or on-premises data warehouses. But, Power BI makes it easy to connect to your data sources, visualize it to find out what’s important, and share it with others. Using it, you can gain insight, draw conclusions, and share results across departments in the form of analytical reports or interactive dashboards.

Power BI is a BI solution by Microsoft that provides a simple yet powerful interface that even non-technical users can use to create dashboards and analysis reports. Besides offering easy drag-and-drop functionality, the tool also provides a range of interactive data visualizations for creating interactive reports and dashboards. Among all the apps, connectors, and services provided by the Power BI platform, the following key components stand out:Power BI Desktop (a Windows desktop application)

The following are some of the reasons why Power BI is widely considered one of the best business intelligence tools worldwide:Integrates seamlessly with existing systems: Power BI enhances analytics and reporting capabilities by seamlessly integrating with your existing business processes.

Connect seamlessly with data sources: Power BI can connect to a variety of data sources, making it possible to align data sets from different sources and generate compelling reports on the basis of that data. Over 70 connectors are available for extracting data from sources like Azure Data Warehouse, , Excel, CSV, OneDrive, Google Analytics, Dropbox, SQL databases.

No memory or speed constraints:Migrating a BI system to a robust cloud environment with Power BI integrated does not create memory or speed constraints, enabling the data to be retrieved and analyzed efficiently. Power BI uses the pivot data modeling engine, a columnar database that reduces data sizes from about 1GB to about 200MB, thereby improving performance.

Reports published securely:Power BI automatically refreshes data and publishes reports securely, ensuring that you always have access to the latest information.

Custom visualization:PowerBI offers a variety of predesigned data visualizations allowing you to create interactive reports or dashboards. In addition, we can add customized visualizations created by Power BI community members to enhance the reports.

Next, let’s talk about Power BI project ideas you can work on and include in your portfolio. Furthermore, these projects allow you to practice and acquire practical experience with the various tools used for data visualization.

In order to help you broaden your knowledge and enhance your skills in Power BI, we have listed 10 Power BI project ideas based on your level of expertise. Newbies can browse through the list of Power BI projects ideas for beginners, whereas intermediates and advanced users can browse through the list of Power BI projects for intermediates and advanced users. For practice, you can select any of these power bi projects for upskilling in the Data Science space and improving portfolio.

For beginners, it’s important to improve data analytics and visualization skills, as well as how to use different techniques to make reports more appealing. Here are some Power BI project ideas for beginners:

Businesses should keep detailed records of their sales because these records can provide valuable insight into how well their business is performing, which items are proving successful, and what changes can be made. Businesses with good records are more likely to succeed. The problem arises when there is a lot of data, and keeping track of everything can become a challenge. This is where Power BI came into play.

Using Sales Data Analysis Project, companies are able to keep track of their sales and get answers to all of their questions about how they performed. As part of this project, we’ll be visualizing Microsoft’s sample dataset to show a profit by product and sales, as well as other key factors that may affect a company’s performance. However, the data set needs to be connected to Power BI Desktop so that irrelevant data can be removed before visualization and exporting of the filtered data as dashboards. There are various Power BI visualization types you could use for the dashboard, including Pie Charts, Bar Charts, Doughnut Charts, Funnel Charts, etc. Using the same sample dataset (Microsoft’s sample dataset), more Power BI projects can be developed and advanced visualizations can be made.

An effective marketing campaign is a great way to reach consumers, clients and leads. An analysis of your campaign data can provide you with valuable insight into your target audience, marketing channels, and budget. Then you can figure out how (or how not) to run your next campaign. This is where Power BI came into play.

We propose this project to show off the efficiency of various marketing campaigns and the features performance analysis of products and platforms can be done. ​You can use this project to assess the success of marketing campaigns and various activities carried out under his management. This beginner-level project can be done with the Marketing Analytics dataset (this project provides insight into the customer’s profile preferences and channel performance). This dataset can be used for EDA, statistical analysis, and visualizations. A Power BI dashboard could have several types of visualization, such as Bar Charts for category-wise expenditures, Smart Narratives for highlighting key aspects of the campaign, Bubble Charts for customer-wise spending, Column Charts for campaign success rates, Cards for highlighting individual insights, etc.

Microsoft Power BI is used for financial analysis to gather and analyze KPIs (Key Financial Indicators), charts, and financial statements. The purpose of this BI project is to optimize financial reporting in a firm that provides accounting services to clients seeking timely delivery of critical financial reports. Through this analysis, you will be able to access reliable financial reports quickly and efficiently. Multi-company financial datasets may be utilized for this project.

The project outlined here can also be applied to the migration of traditional financial reporting from Excel to BI dashboards, allowing customers to track their financial health and productivity more effectively. ​In this project, Power BI data visualization options can be utilized for three scenarios as given below:Funnel charts, combo charts (such as column charts, waterfall charts, line charts) for the summary page or overview page;

A major challenge that modern enterprises face is customer migration (churn). Churn, or customer attrition, is the act of customers stopping purchasing from a business or interacting with it. What can we do to overcome this challenge? The idea is to know the reasons why customers churn, the factors that impact that, so that appropriate measures can be taken to retain them. This is where Power BI comes into play.

Through this Customer Churn analysis project, one can uncover what causes your customers to stop using your product or service. Business leaders, managers, or analytical users can use this Power BI project to analyze regional business growth and the profit distribution among customers. With the right visualization and data structure, they can receive extensive data. As part of the project, regional cash inflows will be considered, as well as product-specific churn over the course of time. To complete this beginner-friendly project, you will need the customer segmentation dataset. ​In this project, Power BI data visualization options can be utilized for different scenarios as given below:Combo Charts, Bar Charts, Line Chart, Cards, Tables, etc., for overview page.

You may already be familiar with the Power BI tool and are interested in strengthening your skills further as a Data Scientist. Check out these Power BI project ideas for your resumes:

A global health expenditure analysis provides comparative data on health expenditure for 192 countries over the last two decades. In this project, PyCaret (Machine learning library in Python) is used for implementing clustering analysis in Power BI. Clustering involves gathering data items having similar features. These classifications aid in examining datasets, detecting patterns, and analyzing data, while data clustering assists in identifying underlying data structures.

For this project, you can use the current health expenditure dataset from the WHO (World Health Organization) Global Health Expenditure Database. You could also use the K-Means algorithm to conduct your clustering analysis. Once the dataset has been loaded in Power BI Desktop and trained your clustering model has in Power BI, you can visualize the cluster labels in Power BI Dashboard in order to gain insights. You might choose visualization chart types such as Bar Charts, Filled Maps, etc., for the summary page dashboard, while you can use Point Maps for the