business intelligence tools power bi in stock

The stock market app shows you multiple KPIs to start your analytics journey in Power BI. You can use it to track end-of-day quotes as well as weekly, monthly, or yearly trends for popular stocks and ETFs. The app shows you Power BI in action, with tracking of stock highs and lows, moving averages, sector-wise distribution, Bollinger bands, and even performance comparisons for popular stocks over time.

Power BI –As an Investor, you might have used many tools for stock market analysis including screener, portfolio tracker etc. Most of them are online, paid or available with a set of limitations. Today I will introduce you with a powerful tool that will empower you for conducting your own stock market research and analysis. I am using this tool from past month. The name of the tool is Power BI. It is the latest Microsoft Business Intelligence Tool that provides you facility of creating own visualization and dashboard with a click of a button. Sounds Interesting right! Read On, to introduce yourself to a new world of Intelligence Power BI.

Power BI is a user-friendly, free and easy to use Business Intelligence and analytics tool provided by Microsoft. Power BI is available in various versions. For the purpose of stock market analysis, you will need Power BI Desktop. Power BI Desktop Free version can be downloaded from Microsoft site – https://powerbi.microsoft.com/en-us/pricing/

On clicking “Get Data”, you will be taken to a tab where you can give your data source. Power BI supports multiple data sources like MS Excel, Text, XML, SQL Database, website etc. In this post, we will take a popular stock market website – Money Control as a source to pick up stock market data for analysis. The main reason for selecting website as a source is doing analysis on the dynamic data. This means if data on the website gets changed your dashboard report also reflect the changes.

Power BI is powerful tool that can be used of making dashboard and report for stock market analysis.  Apart from that you can also make Power BI dashboards about your investment, stock portfolio, profit and loss etc.

Since I am always charting the same financial ratios & metrics, I was thinking if there is a way to automate this. Tinkered around with Python, but it didn’t really go well. So I tried playing around with Power BI and realised how easy this can be. It is probably the best tool to do this.

I am using Power BI on a day-to-day basis for my job. The way I would explain Power BI is just like Tableau, it is a data visualisation tool to generate beautiful dashboards from messy data. Both of them are competitors that fall under the category of Business Intelligence in Data Science.

Microsoft Power BI is recognised as a leader in Gartner’s 2020 Magic Quadrant for Analytics and Business Intelligence Platforms. So it is a good skill to learn & acquire if you want to go down the analytics path in your career.

Power BI is created by Microsoft and it is sort of like an extension of Microsoft Excel’s Power Query. The software is free to download for all and it is simple to use. As long as you know some basic Excel formulas, you are good to go. Do download it here if you are also interested to get started.

In this article, I used Microsoft (MSFT) as a case study to create the Power BI dashboard. To import MSFT’s income statement over the past 5 years, you just need to follow 3 simple steps.Copy the URL link of MSFT’s Financials on Reuters.

That’s the power of Power BI. It can automatically detect tabular data without having to write lengthy web-scraping codes. Importing financial data takes less than a minute which would otherwise have taken me an hour if I were to do it in Python.

Power BI has its own programming language known as Data Analysis Expression or DAX. The syntax for DAX is quite similar to Excel functions, so it should be easy to follow since we are not writing complicated functions.

To do this, you can change the original URL source link when we import in the financial statements. This can be found under the Power Query Editor of Power BI.

Next, we have to ask Power BI to change the data types of all columns again, this time with FB new column names. To do that, select all columns and click “Detect Data Type”. This would automatically change all the columns into their respective data types.

To summarise, if you want to change a stock quote symbol, go to the edit query page, click on source settings, change the URL link, undo the step, select all columns and ask Power BI to detect data type again.

Nevertheless, here is a glimpse of how Power BI can be used for stock market analysis. If you want a more granular view, you can just change the URL link to a quarterly format on Reuters.

In this sample Power BI report, DaTaxan analyse performance of key US stock indexes like S&P 500, Dow Jones, Nasdaq and VNIndex (for Vietnam stock market) in each month to understand the investment adage “Sell in May and go away“.

In accordance to Investopedia, investors should divest their stock holdings in May and wait to reinvest in November. From 1950 to around 2013, the Dow Jones Industrial Average posted lower returns during the May to October period, compared with the November to April period. Let’s do the analysis in Power BI with us now!

DaTaxan also analyses Key factors impacting stock prices. AI powered Key Influencers from Power BI suggests that transaction volume has strong correlation with stock prices.

Our Power BI templates provide you with ideas for a standardized layout, visualization settings, DAX Measures and color theme, and you are ready to go with the valuable insights for your businesses.

What if there were a tool available that empowered you to conduct your own analysis of stocks such as trends over time and high level forecasting (the magic word)? Would you consider investing? Or perhaps you’re already an investor and would like to add another tool to your trading arsenal? Microsoft’s latest Business Intelligence tool, Power BI, does all the above and more without overcomplicating the process.

Power BI is a lightweight, easy to use, free / inexpensive self-service business intelligence tool provided by Microsoft. For more details on pricing, check out the Power BI official page here: https://powerbi.microsoft.com/en-us/pricing/. For the purposes of this blog, all you will need is Power BI Desktop, which can be downloaded for free from the above link.

After launching PBI Desktop, you’ll want to Select Get Data. Power BI makes it extremely easy to connect to a variety of data sources, but for this blog we’re going to focus on connecting to Web and Excel sources.

You will also want to link your Company and Historical Data tables together by creating a new column on the Historical table. Power BI makes this pretty easy as well. Navigate to the Add Column tab, select Custom Column from the ribbon, name the column appropriately, and in the Custom Column Formula simply set it equal to 1 then select Ok. When finished, rename your table to something more meaningful than “Table 1” by double clicking on the table name from the left-hand side. The finished product should look something like this:

Power BI enables you to manage relationships between tables directly inside of PBI Desktop. There are a couple of ways to do this, but for simplicity sake we will be looking at the Relationships tab on the left side of PBI Desktop:

One of the best things about Power BI is that it’s incredibly user friendly. The drag-drop interface makes it simple for even the most entry level users to quickly create useful insights. There are two key visualizations that I’m going to touch on and the rest, I’ll leave up to you to explore and discover on your own.

Now let’s add a trend line to the line chart. To do this, navigate to the analytics menu, select Trend Line, then select Add. Power BI will automatically plot a trend line for you on the line chart. Here, we can also add Forecasting to our chart by selecting Forecast and Add. In this example, there is not enough historical data to successfully Forecast. I will show an example of Forecasting from another demo in the summary.

Power BI also allows you to quickly customize your visualizations with titles, data labels, colors, backgrounds, and borders from the Format menu of the visualization pane. I won’t go into detail here, but go crazy!

The second visualization that I want to highlight is a newly added feature called the Relative Date Slicer. This visualization allows you to analyze data over periods of time such as rolling averages and is currently still in preview, but I doubt it will be for long. To enable features that are in preview navigate to File, Options and Settings, Options, and Preview Features. Select all that you would like and click Ok. You’ll need to save and restart your instance of Power BI Desktop for the changes to become active.

While the content presented has been extremely high level, and continuous updates being pushed out every month, we’ve only began to scratch the surface of what Power BI can do. For more advanced users, PBI presents itself as a power house of functionality. DAX, the language specific to PBI enables power users to create complicated, comprehensive expressions for reporting. For those that are familiar with color palette optimization and themes, PBI also offers the ability to create custom themes to be used in reporting. If the out-of-the-box visualizations aren’t enough, you can get ahold of custom visualizations from the community here: https://app.powerbi.com/visuals/. You can also create your own custom visualizations if you can’t seem to find what you’re looking for.

I guess what I’m trying to say is that Power BI meets the needs for any and every type of user, regardless of skill level or business need. On that note, I’ll leave you with a more detailed look into the potential of Power BI and Market Analysis. Cheers!

Power BI is a range of software services, apps, and connectors that work in conjunction to turn unrelated data sources into insights that are cohesive, interactive, and visually immersive. The data may be a collection of cloud-based data warehouses, on-premise hybrid data warehouses, or an Excel spreadsheet. The Power BI tool allows easy connection to the data sources; it also allows the visualization and identification of what is important, and share that with anyone.

The way to use Power BI depends on one’s role in a project or team. People may use Power BI differently according to preference. Power BI can be very flexible for users in this way.

For instance, Power BI can be used for viewing reports and dashboards. It can also be used for number-crunching and generating, publishing, and viewing business reports. A sales professional can use the Power BI phone app to monitor progress on sales quotas and drill into the details of a new sales lead.

Power BI developers may use Power BI APIs to push data into data sets or embed reports and dashboards into custom applications. It is also possible to create a new visual according to one’s ideas and share it with others. One may also implement each element of Power BI at different times depending on the end goal of a project.

As you can see, the usage of the Power BI tool can vary depending on the feature or service that works best for the situation. For example, Power BI Desktop helps in creating reports and statistics, monitoring the progress of manufacturing in a real-time dashboard in the Power BI service, viewing inventory, etc. Based on a Power BI data set, one can also create a paginated report of mailable invoices.

Power BI is a cloud-based BI service that was released by Microsoft in 2014. It uses years of experience in SQL Server, Access, MS Excel, etc. It enables businesses to clean and transform data into meaningful insights by thoroughly analyzing the data.

Power BI has a very easy-to-use interface. Even without prior knowledge and experience in programming, one can use Power BI. Its inbuilt intelligence allows one to choose attributes for reports by suggesting the best reporting element.

Here is an example of how easy is Power BI. After choosing the right data source, when opting for sales and category, the tool will identify the column chart on its own. Similarly, for sales and location, it will pull out the map chart automatically.

The user interface (UI) in Power BI is very simple and easily connects to the data source. On selecting the data source, a simple drag and drop allows the selection of attributes for the report.

Additionally, QA makes it extremely convenient and easy for one to have their written questions answered by Power BI through values or graphs based on the question asked. For example, a question like “What was this year’s revenue by month?” will return a graph showcasing the monthly revenue.

Power BI was built based on the founding platform of MS Excel and follows a similar approach for designing reports. Excel is a widely used software around the world, which makes Power BI easy to pick up as well. Microsoft SQL Server and Microsoft Access database served as the foundation for

Power BI comes with options that make it really easy to collaborate. Users can collaborate with others to compile interactive reports and dashboards in app workspaces.One can even publish them to a larger audience. Sharing these dashboards or reports with a smaller audience is even possible over the mobile app with Power BI.

The reports can be printed by the user as well as exported in the form of a PowerPoint presentation. The reports and dashboards can be published to public websites and anyone in the world can access and interact with them.

Power BI Desktop is available for free and the user can create simple or complex reports and dashboards. Not only that, but the pro licenses of Power BI are quite affordable at US$10 per month). For a larger audience, Power BI has a premium option allowing customization of cost based on usage.

Power BI comes with a wide array of connectors for data sources like MySQL database, SQL Server database, Oracle database, IBM Informix, Microsoft Excel, IBM DB2 database, MailChimp, Facebook, GitHub, IBM Netezza, PostgreSQL database, SAP HANA, Sybase database, Amazon Redshift, Azure SQL Database, Azure SQL Data Warehouse, Azure Analysis services database, Azure Blob Storage, Salesforce, and many more.

Visualization:Microsoft’s SDK in Power BI contains a huge library to create custom visualizations. This allows the users to customize the UI as per their requirements.

Data shaping:Power BI’s Query Editor tool is very flexible and comes with a ton of features. It is self-documenting and offers the opportunity to go deeper in the DAX language for data modeling.

Data modeling:The data modeling options offered by Power BI are very efficient. It is derived from experiences in SQL database and Cube technology, and this makes Power BI a powerful solution.

If you look at the Gartner Magic Quadrant again, you will see that there are quite a lot of competitors of Power BI such as IBM Watson Analytics, Google Analytics, Sisense, and ZOHO reports to name a few; but, Power BI stands tall in the market mainly because of its ease of use and prompt help available from Microsoft.

Ultimately, Power BI is able to drive better decision-making in businesses through its ability to provide insights in visually impressive and interactive reports. It established a data-driven culture with BI for everyone. Additionally, it keeps the data secure and includes end-to-end encryption and sensitivity labeling as well as provides real-time access monitoring.

Power BI is Microsoft’s interactive data visualization and analytics tool for business intelligence (BI). With Power BI, you can pull in data from a wide range of systems in the cloud and on premises and create dashboards that track the metrics you care about the most. You can even drill down into your data and (literally) ask questions about it.

Power BI’s rich reports or dashboards can be embedded in reporting portals you already use. And while its dashboards, reports, and visualizations can go far beyond bar and pie charts, you don’t need to be a designer to create them. You can also use Power BI to prepare and manage high-quality data to use across the business in other tools, including low-code apps. Here’s how to get more insights from the information you already have, in more areas than you might expect.

Power BI has hundreds of content packs, templates, and integrations for hundreds of data services, apps, and services that include pre-set reports and visualizations. If you use Xero for accounting, or K2 Cloud to build business processes, or Adobe Marketing Cloud, SAP HANA, Salesforce, MailChimp, Marketo, or Google Analytics, you can use Power BI to visualize the data you have in those services, create reports against them, and bring them together in a custom dashboard. You can also set up the on-premises gateway to use Power BI to explore data sets on your own servers. That way you can compare website visitors with sales, or see which promotions have brought in new customers. You can create your own reports and visualizations, perform calculations (Power BI calls these calculated measures), and set access levels for individual users, data sources, or specific dashboards and reports to control who can view more sensitive information.

Charts are great for numbers, but if you want to show information that changes over time in a way that’s easy to understand, Power BI’s new Timeline Storyteller is for you. With this tool, you can create a linear list of dates or times, or lay them out in circles, spirals, grids, or custom shapes. You can also show a chronological list, a sequence that shows the duration of events, or pick relative or logarithmic scales. Pick how to best represent, scale, and lay out your data, and Power BI will build a timeline from it. You can then use that to tell the history of your business, show how demand is growing, or explain anything else in which the sequence of events matters.

You can compare scenarios in Excel, but Power BI lets you do it by dragging a slider bar to show changes. Add a calculated measure for a figure such as revenue and you can use the New Parameter button in Power BI Desktop to add parameters that change in your What-if scenario. That creates a calculated measure you can reference elsewhere; so if you create a What-if parameter for the number of customers who respond to a particular promotion you can plug that into a formula you create to show how many customer support tickets you can expect to have to deal with. Tick “Add slider to this page” in the What-if parameter dialog to add a slider bar that you can drag to show the difference when the number of customer responses is higher or lower.

You can also use the natural language features of Power BI to ask questions and get visualizations in response. Specify how the data should be presented — ask for “total sales by region by month as a line” — or let Power BI pick a layout that suits the data with a more general question like, “What were the sales numbers for last quarter?”

Power BI Q&A works in the Power BI website and the iOS Power BI app. It can work on data stored in an Excel table (or in a database via the on-premises gateway if you enable Q&A for the data set) or you can use Power Pivot to optimize the data set for Q&A. Make sure all the tables in your data set are joined correctly, check data types for dates and numbers, and create the default field set for columns and default label for tables to tweak the columns displayed and the type of graph or chart Q&A will show.

Power BI includes a range of visualizations, and you can add more, either by downloading them from the Office Store or by creating your own with the open source Power BI Custom Visual Tool. The Office Store includes vizualizations from Microsoft, such as word clouds, a correlation plot based on R script, and a “box and whisker plot” that highlights outliers, clusters, and percentiles, as well as visualizations created by Power BI customers.

You can also link Visio diagrams to Power BI to use as custom visuals, if you want to analyze progress through workflows and processes. If you have Excel analytics models, you can turn them into custom Power BI visualizations using Frontline’s Analytic Solver. What you get isn’t a static report; it’s a dynamic model that you can drag and drop Power BI data sets onto to simulate or optimize various options.

Several of the Power Bi’s interactive visualizations use machine learning to identify insights that would usually require a data scientist. Key drivers help identify and rank contributing factors, such as what influences products to be on back order. The decomposition tree helps you perform root cause analysis, guiding where to drill into the data. Anomaly detection looks at time series data such as line charts and identifies outliers and other anomalies, and suggests explanations. Smart Narratives can pull out key takeaways and trends and wrap them with autogenerated text to build data stories for you.

Most BI is done on data extracted from a database at scheduled intervals. If you want to analyze data from ecommerce sites or operational technology systems that have sensors, you need access to real-time streaming data. Usually that requires some development to extract the data, but streaming dataflows in Power BI can connect to Azure Streaming Analytics, enabling business analysts to combine batched and streaming data in the same reports to find exceptions, trigger actions, and react more quickly to changes in physical systems.

If your organization spends most of the day in Teams, bringing Power BI reports to where everyone is working (and talking about work) makes it more useful. According to Microsoft, usage of data in Power BI almost doubles when the app is pinned in Teams. If the IT organization has invested time and money rolling out Power BI, enabling Teams integration gets more out of that investment.

If you share data in Power BI, it’s also available for people to use inside Excel. Power BI can also power data types in Excel, giving you a single, authoritative source of data for entities such as customers, suppliers, products, and other business information that will be used across the organization. You get a shared source of truth and Excel users don’t have to learn Power BI to take advantage of it. They can type in information they want to look up such as a customer name, mark the range, and click on a tool tip to insert new columns from the data set to work with in Excel.

Power BI’s Dataflow helps you automate data preparation and enrichment, making Power BI a good place to keep data sets that will be used for machine learning. Its integration of Azure Machine Learning AutoML means business analysts can also take advantage of machine learning without needing a data scientist — or an Azure subscription. Define what you want to predict, such as whether a product will be out of stock, and AutoML suggests what columns of data to use for the model, selects and tunes the algorithm automatically, and includes the performance and reliability of the model created, along with what features influence the predictions it makes for which products are most likely to be out of stock at particular distribution centers.

You can embed Power Apps into Power BI reports and set up Power Automate workflows from inside Power BI. So if there’s an action that makes sense to take after getting insights from data, such as adding a customer to an email marketing campaign or making a budget request, you can put the app or flow for doing that in the report where you get the insights — and the filters and selection you make in Power BI carry over to the app or workflow. For mobile users who are more likely to be working from a Power app, you can embed the Power BI report into the app instead.

Different BI users need different levels of information in their visualizations. Managers and business analysts may want a lot of details, but if your executives are tracking 20 or 30 key metrics for multiple regions around the world, it’s better to present that at a glance with a simple view that shows the target and the actual figure rather than a more complex visualization. That way you can look up information quickly in a meeting without getting lost in too many charts and figures. The Power KPI custom visualization combines multiple report types into a single tile.

Making a data-driven culture effective means using data to measure how well decisions are working out for the business. Instead of paying for a specific tool to build dashboards for tracking performance and achievement on key metrics, use the Goals hub in Power BI Premium to connect scorecards to Power BI reports. For goals such as revenue, sales, hiring, or user numbers, you fill in when you need to achieve the result by, how you measure it, and select the relevant data points on a chart in a Power BI report. As well as seeing progress in the Goals hub, you can also use Power Automate to trigger alerts or schedule meetings if performance towards a goal is falling behind.

When you’re putting confidential company data in Power BI, CIOs and CISOs can make sure only the right staff have access by applying the same Microsoft Information Protection sensitivity labels as in Office, SharePoint, and other tools. Those labels enable auditing, enforce access in Power BI, and follow the data if it’s exported to Excel or PowerPoint for end-to-end data leakage protection.

Power BI isn’t just for business users, as you can use it to visualize data for IT monitoring tools. Power BI’s solution template for Azure Activity Logs uses an Azure SQL database and Stream Analytics to collect logs and display them using prebuilt Power BI Desktop reports, so you can look at trends in usage and problems. There’s also a set of prebuilt Power BI reports for the Intune Data Warehouse that shows device details such as configurations and compliance state, and a solution template for System Center Configuration Manager with a dashboard that covers client and server health, malware protection levels, software inventory, and which devices are missing updates. There are templates for a range of other tools, and you can build your own dashboards and reports for other tools, as long as you can get the data into a SQL Server or Azure SQL database.

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.

Microsoft Power BI is a suite of business intelligence (BI), reporting, and data visualization products and services for individuals and teams. Power BI stands out with streamlined publication and distribution capabilities, as well as integration with other Microsoft products and services. But is it a good choice for your organization?

"Power BI," Microsoft says, "is a business analytics solution that lets you visualize your data and share insights across your organization, or embed them in your app or website." The solution comprises several products and services, and value and versatility comes from leveraging the individual elements, and taking advantage of how they work together.

Power BI service is a secure Microsoft hosted cloud service that lets users view dashboards, reports, and Power BI apps — a type of content that combines related dashboards and reports — using a web browser or via mobile apps for Windows, iOS, and Android.

Power BI Desktop is a free, self-service data analysis and report authoring tool that you install on a Windows computer. It can connect to more than 70 on-premises and cloud data sources to turn information into interactive visuals. Data scientists and developers work with Power BI Desktop to produce reports and make them available to the Power BI service.

Power BI Pro is cloud-based software that comes with a monthly fee of $10 per user. The biggest difference between Power BI Desktop and Power BI Pro is the ability to collaborate with other Power BI users and distribute reports and visualizations to other Power BI subscribers across the organization (see chart below).

Unlike Power BI Desktop and Pro, Power BI Premium is not an application. Premium gives an organization space and capacity in a Microsoft-hosted cloud to share reports. An organization can choose how to apply its dedicated capacity by allocating it based on the number of users, workload needs, or other factors — and scale up or down as needed.

If your organization has many people who create reports and visualizations, and who don"t share information often, a Pro subscription may be sufficient. However, if you must share the information both inside and outside of your organization, you"ll need a Premium subscription. Power BI Premium is priced based on the number of virtual cores Microsoft dedicates to the service. You can see prices at the Power BI pricing page.

Report Server is an on-premises report server. You can create reports in Power BI Desktop or Pro, and viewers can use Report Server to access those reports on a web browser or mobile device, or they can receive them as an email. Report Server would be useful for a company that has restrictions on cloud usage.

Power BI Embedded allows developers to embed Power BI dashboards and reports into other applications, either within their own organization — which requires users to sign in to a Power BI account — or in an application for a client or customers who don"t have a Power BI account.

How do you know whether Microsoft Power BI is right for your organization? Here are seven reasons to choose Power BI — and one reason you may want to choose something else:

Streamlined publication and distribution. Instead of emailing large files or putting them on a shared drive, analysts upload reports and visualizations to the Power BI service, and their data is refreshed whenever the underlying dataset is updated.

Ability to customize Power BI app navigation. An "app navigation experiences" feature gives report developers the power to customize navigation to help viewers find content quickly and understand the relationships between different reports and dashboards.

Cortana integration. Power BI works with Microsoft"s digital assistant, Cortana. Users can verbally ask questions in natural language to access charts and graphs. This can be especially helpful for users with mobile devices.

Artificial Intelligence. Power BI users can access image recognition and text analytics, create machine learning models, and integrate with Azure Machine Learning.

So, why would you want to pass on Power BI? Well, the online Power BI service — including Pro and Premium — is accessible from any web browser, but the Power BI Desktop application is not available for Linux or Mac operating systems. If you"re in a Mac-only environment, Microsoft Power BI Desktop may not be right for you.

Before you analyze your data with Power BI, you"ll need to replicate data from all of your sources into a data warehouse. Using an ETL tool to replicate data into a cloud-based data warehouse, such as Microsoft"s Azure Synapse, makes it easy to combine data from all of your sources for a holistic view of your business.

You can simplify and streamline data ingestion by using a cloud-based ETL service like Stitch that automates the process of connecting to and extracting data from sources and loading the data into your destination. From there you can use Power BI to perform the in-depth analysis you need.

Our approach is simple, straightforward, and ready to go right out of the box. Try Stitch for free and start getting data-driven insights from Microsoft Power BI tomorrow.

In this 1 hour long project, you will build an attractive and eye-catching personal stock dashboard that is able to fetch the prices of stocks and cryptocurrencies in real-time. We will be using one of the best finance APIs to fetch real-time stock prices. We will begin by importing relevant financial data using the finance API. We will import two different data: one for stock summary and another for historical prices. We will then create our dashboard. In the final tasks, we will automate the dashboard so that you can get live prices and data for any of your favourite stocks or cryptocurrencies within a few seconds. By the end of this course, you will be confident in importing financial data using finance API, creating dashboards and live tracking of all of your favourite stocks in real-time using Power BI.

In this blog, I’ll show you how to create a dynamic stock quote app in Power BI. This interesting technique came out from a post in the Enterprise DNA forum.

The member wanted to know how we go about starting with online data and pulling that into Power BI and then analyzing it from there instead of starting with what we typically do, which is an Excel file or a CSB file.

And so, I wanted to show you how to do this and how easy it is. It shows how powerful Power BI is in terms of web scraping and automated data poll capabilities.

This post is a comprehensive guide to inventory management using Power BI. Here, I share with you different techniques you can use in Power BI to give you a detailed analysis with lots of valuable insights for an optimum inventory management.

The first video is all about managing your inventory and finding insights in an almost real-time basis. This inventory management solution in Power BI enables you to monitor inventory levels in warehouses versus trends for revenue across sales channels, review short-term cash requirements for upcoming stock re-order programs, and analyze key vendors, and look for procurement discounting opportunities. Moreover, you can review real time stock-take analysis and evaluate value of inventory sitting on warehouse floors.

This next video shows you how to achieve that by utilizing the DAX formulas in Power BI. In this video tutorial, I make a comparison between historical sales and the current stocks. That’s exactly how you should manage your inventory.

Fortunately, I have a video tutorial on how you can make your Power BI models, specifically with inventory management data, which is very compelling and extremely insightful.

The key to inventory management analysis is to really have a good understanding of the data model and make use of relevant DAX calculations. It"s also essential to create high-quality and appealing visualizations. The application of these techniques within different areas of Power BI is what you ultimately need to get amazing insights. This is the real power in using Power BI as an analytical tool.

Access your data from anywhere with the Power BI app. Get notifications, annotate and share, and dive deep into your data with powerful features for decision making on the go.

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.