Data Connectivity
When it comes to business intelligence, you want to make sure you’re analyzing all of your data to get the most detailed, reliable information possible. To do this, the solution must be able to link to all of your company’s data sources.

Many different types of data sets and data sources are supported by Power BI. It ensures seamless access to existing data analytics investments with native integration of Microsoft technologies such as Excel and strong support for a variety of other platforms. Power BI can be integrated with nearly any Microsoft application, providing a vast library of potential collaboration options. It can also extract data from Google Analytics, MySQL, Oracle, Salesforce, MailChimp, Facebook, and Zendesk, among other programs. Its strength comes from links to on-premise and cloud-based outlets, as well as desktop and browser-based authoring, both of which are part of a hybrid integration strategy based on Microsoft Azure cloud APIs.
Tableau users have access to hundreds of data sources, thanks to native connectors for Amazon Redshift, Cloudera, Google Analytics, Microsoft Excel, My SQL, and other big business platforms. Users may link to data that has already been published on their Tableau site, as well as data stored in a cloud database, a private server, or Excel or text files. Developers can also create their own connections to sources that aren’t currently supported, or users can request that Tableau support such connections in future updates.
With native connectors to enterprise applications and cloud services such as Apache Hadoop, Azure, Microsoft Office, MongoDB, Snowflake, SAP, and Twitter, QlikView can connect to both on-premise and cloud-based data sources. After installing connectors, users must install them separately for QlikView. Developers may use the OBDC or REST API to create advanced connections. Users can also drag-and-drop data from files or bind to both legacy and new databases.
Therefore, Tableau and Power BI is the better options in terms of data connectivity, as both offering a wide range of data integrations and support for data sources both newer and older.

Dashboards and Data Visualization
Data visualization tools take numbers and transform them into visually pleasing and easily turn them into graphs, charts, and maps, are one of the most useful ways to derive insights from data in business intelligence. The dashboard is capable of reducing data visualization to just one element. It offers a quick rundown of key KPIs that viewers can absorb in minutes, making them an effective way to share information and save time for decision-makers.

One of the most user-friendly data visualization software in the business intelligence industry is Microsoft Power BI. The software’s drag-and-drop interface, combined with access to a library of data visualizations and 85 other data visualization apps, creates an intuitive experience that leads to beautiful and insightful reports. The data visualization feature of Power BI is hinges on tiles, which are visually represented metrics that serve as an entry point into the underlying reports and datasets, allowing for a better understanding of the numbers. Users can easily create dashboards by pinning tiles from any report and adjust the look and feel of their dashboards using the platform’s toolbar. To keep track of important metrics, users can set alerts for specific dashboard tiles and allocate featured or preferred dashboards. Users can collaborate, exchange data through teams, and access insights from any computer through the web thanks to convenient sharing capabilities. Since Power BI uses many of the same features as Excel, users who are already familiar with the Office tool would be able to get the most out of it.

Tableau is a user-friendly data visualization application that is well-known in the industry. Its user-friendly interface enables non-technical users to build and customize dashboards that provide insight into a wide range of business data quickly and easily. These dashboards have responsive interfaces that adjust to a variety of devices and screen sizes, enabling Tableau users all over the world to enjoy a consistent look. Users can quickly create graphics by manually dragging and falling fields, or by using Ask Data to automatically ask the solution questions in natural language. Filters, a Show Me tool, highlighting, and other features enable users to dig deeper into their dashboards. Tableau has a library of pre-built dashboard models called Dashboard Starters that build dashboards automatically based on integrations with common business data sources. Users can also create their own custom visualizations or use those generated by other Tableau users in the online community.

QlikView’s data visualizations provide real-time, interactive analysis as reports are created, in addition to standard report design features such as visualization models, customizable views, and configurable tables and graphics. All related visualizations and data sets are shown for fast reference while the device is in operation. To build dashboards, QlikView users can create and insert objects based on data into a canvas. Charts, selections, buttons, and metrics are the four elements that users can use to build their dashboards. Users can generate visualizations using a variety of table and chart forms in QlikView. Dashboards are structures that are embedded in sheets. Drill-down and filtering options are built into dashboards, allowing users to interact with them. In comparison to other tools, QlikView’s dashboards are relatively limited in terms of interactivity and customization; however, many of the more advanced dashboarding features in line with modern BI standards, such as drag-and-drop data, are available via Qlik’s SaaS-based updated platform, QlikSense.

Hence, in terms of dashboard and data visualization, Tableau and Power BI are better as both solutions feature drag-and-drop dashboard creation. However, Tableau includes features like animations and pre-built dashboard models that are only accessible through customization or extensibility in Power BI. Tableau users can analyze any number of data points in data visualizations, while Power BI users are restricted to 3,500 data points while digging down into datasets, making Tableau’s dashboards more useful in terms of interactivity. In addition, Tableau offers an all-encompassing and user-friendly experience with its intuitive interface, customization options, and real-time analytics, making it the clear front-runner for data visualization and dashboarding. Therefore Tableau has got a slightly better advantage over Power BI.

Reporting
Reporting is an important feature of any BI tool as it organizes data to show what is happening in a business at any given point in time. Although reporting used to be the sole domain of IT power analysts, modern BI solutions have made self-service reporting a reality for business users, allowing them to produce their own reports in minutes rather than days, easing the burden on their company’s IT department.
Users of the different level of Power BI subscription can create and exchange reports. Users can build, customize, and explore interactive reports using a drag-and-drop canvas that is sensitive and compatible with all screen sizes and aspect ratios. Reports can be published to the cloud or on-premises, or they can be embedded into existing applications or websites. Users can also export paginated reports to Excel, Word, XML, CSV, PowerPoint, MHTML, and PDF files, among other formats. Power BI reports are designed to print smoothly and pixel-perfectly on a page. Power BI Report Server is a cloud-ready enterprise reporting solution that allows for on-premises governance and report delivery behind a firewall while remaining cloud-ready. The Share button within the application allows users to easily share their reports within those in their organization, and managing permissions and access to their reports.
Tableau’s reporting tool offers both automatic, scheduled and ad hoc reporting options. Users may generate reports in table and spreadsheet formats, with graphs, maps, and histograms as visualizations. In addition, they may also opt in to receive these reports as daily email updates in a variety of file formats, including photos and PDF files. Reports can be converted into personalized dashboards that can be accessed through a web browser.
NPrinting is an innovative report generation and delivery method in QlikView. Reports can be easily created in a variety of common formats, including Microsoft Office, PDF, and HTML web pages. NPrinting provides both managed distribution and self-service reporting to ensure that the right reports are sent to the right people at the right time, whether by ad-hoc requests, scheduled reports, email delivery, or other methods.
Therefore Power BI is the best option of the three as it simplifies report development and customization while emphasizing print and publication ready sharing

Data Querying
Though data is stored in databases, users can only get the most out of their data through data querying. A data query is a specific request for data written in a programming language, most commonly Structured Query Language (SQL), that extracts information and formats it for consumption and analysis. Many of the more advanced and nuanced features of data preparation and analysis are unlocked by data querying, which can reveal hidden patterns and relationships between data points. As an data analyst, one should have access to a BI solution that supports data querying in order to fully utilize your data.
The Power Query Editor in Power BI helps it to link to various sources through queries. There are five tabs for organization on the ribbon: Home, Transform, Add Column, View, and Help. Users may use queries to shape and turn data, and a pane in the Power Query Editor displays the number of active queries.
Tableau allows custom SQL data querying and uses the VizQL query language. The Visual Query Language (VizQL) is a program that converts drag-and-drop behavior into data queries. Users can generate a wide range of requests using custom SQL queries. They can only bind to a subset of a dataset, not the entire dataset. Users can append, merge, and aggregate data using custom querying. Users may configure cross-database joins or table unions, as well as restructure or reduce the size of data for analysis. Users can also make queries in natural language using Tableau’s AI-powered Ask Data function.
To bind to and retrieve data from different data sources, QlikView uses a load script, which is controlled in the script editor. Users may use script statements and expressions to modify or convert data, or they can define fields and tables to load within the script. The associative engine in QlikView distinguishes popular fields across tables, and users can view the transformed data structure in a viewer. QlikView stores the data in the active document or in RAM after it has been loaded. Users must reload the script to get new data.
With its built-in support for data queries in both its own query language and SQL, as well as its enhanced NLP data querying capabilities, Tableau is the best option of the three.

Data Security
Protecting your data is just as critical as analyzing it, if not more so. Protocols and certifications should be kept up to date by the best BI solutions. They can also provide tools to help administrators manage entry, permissions, authentication, encryption, auditing, and other aspects of security so that businesses can rest assured that their confidential information is still safe.
Power BI complies with data protection requirements because it is governed by Microsoft’s security standards and policies. Power BI’s commitment to data protection is reflected in its architecture, which consists of a web front-end cluster and a back-end cluster for each deployment. As the solution authenticates clients and transmits data between the two clusters, data remains stable. Administrators may choose their preferred user authentication method. Inside the solution, Power BI provides row-level and column-level protection that can be used to limit data access for specific users. Users can choose whether to grant recipients Read or Reshare permissions while sharing a dashboard, and they can later display and manage individual user permissions for each dashboard. Multi-tenant environment protection, network security, and the ability to incorporate additional security measures are all included in Power BI platform security.
Local, SAML, Kerberos, shared SSL, OpenID, trusted authentication, and personal access tokens are among the authentication methods supported by Tableau. It promotes server, extensive, encryption, and network security best practices. Users can choose whether or not to ask users for database credentials when they select a published view to secure live data sources. Tableau administrators can handle data protection by combining three options: database login accounts, authentication modes, and user filters. Administrators can monitor data access and authorization using site roles and permissions. Tableau also has row-level encryption, which allows users to see only some rows of data inside a workbook.
Authentication for QlikView can be done via Windows, the platform’s user ID and password, or the license key. Security tables, which users must create into the script by data queries in the same way that the solution usually loads data, are used to control data access. Users without authorization cannot access QlikView documents; these security tables can set access privileges for individual users or groups of users based on roles. Within the protection page of a QlikView document’s assets, users may restrict modification permissions. QlikView and QlikView Server also have a feature that allows the user to hide some of the data in a document depending on the section access login.
Although Tableau and MS Power BI share many of the same security components, Power BI uses Azure and its built-in cluster architecture to provide stronger security models.

Augmented Analytics
Artificial intelligence, machine learning, and natural language processing are all used in augmented analytics to speed up time to insights and help humans interpret data more effectively. It can make insights more available to users of all technological ability levels, automate time-consuming activities, forecast future events using statistics, and personalize information to provide more meaningful information. Overall, augmented analytics is the same data analytics you’re familiar with, but it’s quicker and smarter. If you want a future-proof BI solution, you would definitely prefer it to be one that includes augmented analytics.
Quick Insights is a Power BI feature that uses algorithms to automatically classify basic insights, associations, and possible outliers using a collection of visualizations. Using decision trees, AI-powered data visualizations automatically reveal key drivers that affect given metrics and segment data into classes. Users can use the Get Insights function to learn more about specific data by simply clicking a button inside any dashboard; Power BI can then run machine learning models to clarify what’s going on. Users may opt to continue running research, allowing the AI to update the insights as it learns more, even though these ML models only run for a short time to return insights quickly. Predictive analytics can also be used by data scientists using advanced machine learning (AutoML). Users can use AutoML to train, validate, and invoke machine learning models, making the development and testing of machine learning algorithms much easier. AutoML extracts the most important features, chooses an appropriate algorithm, and then tunes and validates the machine learning model. After a model has been conditioned, Power BI produces a performance report that includes the validation results. The ML model can then be used on any new or modified data in the dataflow. When it comes to personalization, Power BI supports custom visualization panes and Siri Shortcuts.
In the case of Tableau, Smart Analytics uses machine learning to simplify data preparation, allowing users to pivot and break data, as well as index and group similar terms using fuzzy matching. Tableau also employs machine learning to suggest database tables and joins based on data source use metrics. Explain Data describe particular points in their data using a focused set of explanations, which are driven by algorithms and statistical models. Tableau also has predictive analytics capabilities, including drag-and-drop forecasting and statistical model integration through R and Python.
Unfortunately, artificial intelligence, machine learning algorithms, map recommendations, or natural language processing are not supported by QlikView at this point in time.
Overall, Power BI is the best option when it comes to augmented analytics, with AI-powered explanations in the tool and built-in trainable machine learning algorithms.

Embedded Analytics
By allowing a BI tool to be incorporated into another software, embedded analytics provides users of an existing platform with the advantages of data-informed decision making. BI applications with embedded capabilities are a great way for developers to apply analytics to their product or service without having to design their own tool.
Via REST APIs and JavaScript APIs, Power BI users can embed Power BI dashboards, interactive reports, and tiles inside an application; they can opt to display their data directly in Power BI or in the embedded application. It also facilitates multi-tenancy, which allows for multiple user capacities to be accommodated with a single sign-on authentication. Users of Power BI may create dedicated resources for their clients or workspaces by creating a dedicated ability. Power BI Embedded, a scalable version of Power BI that allows for additional visuals and functionality such as white labeling, customization, and Q&A support, is available for users looking for a more versatile solution.
Tableau includes multitenant architecture, white labeling, customization, and security features including single sign-on, row-level security, and user permissions in its embedded analytics. Tableau’s JavaScript API and Rest API offer various options for integrating BI capabilities into custom-developed web applications. It also includes a Mobile App Bootstrap sample code that can be used as a starting point for developing custom mobile apps with Tableau features.
QlikView does not support embedded analytics, but QlikSense and Qlik Analytics do, with RESTful APIs that allow developers to create and expand embedded analytics tools for almost any application or browser-based UI.
Though Tableau and Power BI are comparable in terms of embedded analytics, Power BI comes out on top because it is easier to integrate into other applications and supports secure write-back through a custom visual, while Tableau requires custom creation.

IoT Analytics
The Internet of Things, or IoT, refers to a network of interconnected devices that can transfer data without requiring human-to-human or human-to-device interaction. Smartphones, smart thermostats, cameras, engines, machinery, and other IoT devices are only a few examples. The IoT connects all of these devices, allowing BI tools with IoT analytics capabilities to explore and analyze the massive amounts of data produced by this massive network of devices, resulting in even more comprehensive and detailed insights.
Power BI integrates with Azure Stream Analytics, a real-time analytics and complex event processing engine that analyses and processes large amounts of fast streaming data from multiple sources at the same time. It also works with Azure Event Hub and Azure IoT Hub to absorb data from connected devices, sensors, social media feeds, clickstreams, applications, and log files, among other sources. Power BI can recognize patterns, which can then be used to trigger behaviour and workflows like generating warnings, feeding data into a reporting tool, or storing transformed data for later use. For these IoT applications, users may generate real-time dashboards and warnings based on temporal or spatial trends and anomalies.
Tableau can collect data from sensors or devices, analyze it, and visualize it to generate insights based on the information gathered. Tableau is able to build dashboards using IoT data and spot patterns and anomalies.
With direct access to IoT data in near-real-time, QlikView supports IoT Analytics. It can analyze large volumes of IoT data and present it in an understandable format, as well as support real-time tracking and forecasting with automatic alerts and other features.
Therefore, with real-time streaming data analytics is a breeze with Azure Stream Analytics, and Power BI is the best option of the three thanks to its warn, dashboarding, and anomaly detection capabilities.

Geospatial Analytics
Geospatial analytics aids in the transformation of spatial, location-based data into maps, visualizations, and useful insights. It adds another layer of information by placing data points in a geographical sense.
Users can pin map visualizations to dashboards using Power BI’s integration with ArcGIS maps. TopoJSON maps can also be used to generate map visuals. Users can convert shapefiles or GeoJSON files to TopoJSON files, which they can then convert into visualizations for their dashboards, if their geospatial data is in another format.
Users of Tableau can import geospatial data from a variety of file formats, analyze it, and visualize it directly in the platform. Tableau supports a wide range of interactive map visualizations, including proportional symbol maps, choropleth maps, point distribution maps, heatmaps, and flow maps, among others. Tableau users can use a map search to locate locations and then explore and inspect data associated with those locations. When users start typing in the search box, map search recommends potential locations based on place names and text from their data sources that are in their map view. Users may look for continents, countries, states or provinces, counties, cities, and postal codes. Tableau also includes forward and reverse geocoding, as well as a number of spatial functions that allow users to perform advanced spatial analysis and combine spatial files with data from other sources such as text files or spreadsheets. Users can bind to and enter ESRI Shapefiles, KML, GeoJSON files, MapInfo tables, and other types of geospatial data using Tableau’s spatial connector.
Qlik GeoAnalytics provides mapping and location-based analytics for QlikView, allowing users to make better location-related decisions. Multi-layer mapping in QlikView allows you to capture, display, and manipulate location-based data such as street addresses, zip codes, satellite images, and GPS coordinates, as well as perform spatial analysis. Users can also perform geo data lookups to automatically populate and refresh dashboards and maps with information about particular locations.
Tableau is the best of the three option with its geospatial data integrations in a variety of formats, interactive map visualizations, and efficient map search feature.

Natural Language Processing
Natural language processing (NLP) and natural language generation (NLG) are tools that allow for simple data processing, querying, and generation of reports and visualizations using conversational language commands rather than SQL or other code. NLP and NLG are augmented analytics features that make data insights more available to users throughout an organisation.
Power BI has a Q&A feature that lets you ask questions in natural language and get answers in the form of charts and graphs. Users may ask Power BI conversational questions about ratios, formulas, and metrics, and Power BI will produce automated answers and reports. Intelligent narratives created by Narrative Science Quill, an advanced natural language generation tool that can uncover hidden patterns, can be included in these studies. As users interact with their data, these narratives become more complex and update more frequently. Users will change the story and share it with others. Power BI supports both text-based and voice-based natural language questions, as well as autocomplete, which provides specific and contextual recommendations. Power BI integrates with Cortana, allowing users to ask Cortana, Windows’ built-in AI assistant, questions and receive instant answers. Natural language questions are also supported by the Power BI mobile app.
Ask Data, which uses algorithms to allow users to type questions in natural language and receive answer recommendations in the form of visualizations, supports NLP queries in Tableau. Users can then tweak their questions and the data visualization to their liking. The results can be saved and shared with others at a later time. Natural language queries can also be used to incorporate more data sources, perform map searches, and generate dashboards.
QlikView is unable to support supports natural language processing, but QlikSense can.
Power BI is the natural language processing leader, with more comprehensive features overall than the other two tools.

Native Mobile App
Nowadays, we take our job with us everywhere we go, so we need to be able to access our data wherever we go instead of having business done in the office. Native mobile apps play a critical role in delivering insights to your Android or iOS users, ensuring that the platform adapts to different screen sizes and that the dashboards remain interactive.
Power BI provides native mobile apps for Windows, Android, and iOS that enable users to securely access and share real-time reports and dashboards, as well as see all of their important data in one location. They are able to just tap to explore, filter, and focus on what matters. Mobile users can also build and share reports, send natural language queries, and receive personal data updates through push notifications for tile changes. Mobile users don’t need to be linked to the internet to see their data because up to 250 MB of offline data caching is available. The mobile app refreshes data periodically by default; users can access and interact with dashboards they’ve previously accessed and interacted with when offline, but paginated reports and certain tiles that involve an active server link will be unavailable. The Notifications tab in the mobile app gives users a sequential customized stream of messages about reminders they’ve set, new dashboards shared with them, workspace updates, and more. Touch-enabled annotation and sharing, geospatial analysis, and QR code scanning are also supported by Power BI Mobile for on-the-go collaboration.
For Android and iOS users, Tableau has native smartphone apps. It allows users to communicate with dashboards and KPIs by using filters, scrolling and zooming behaviors, and drill-down functions. Mobile users can label, scroll, scan, and view dashboards with Tableau. Tableau’s offline data features provide interactive previews that enable users to access data when offline; when users connect to the server, the mobile app downloads all of their favorite workbooks and views, which they can access later even if they don’t have access to the internet. Users on mobile devices can subscribe to workbooks and receive push notifications when data exceeds a certain threshold. Tableau mobile users often have a customized home screen that shows their most important metrics in a curated, consistent way.
The mobile app for QlikView is only available for iOS users. It has a responsive interface that resizes maps, scales the level of data detail, and optimizes visualizations for mobile devices.
In this category, Power BI outperforms Tableau and QlikView in terms of mobile collaboration, geospatial analysis, and QR code support, as well as report generation and natural language processing queries.

Free Trial
To be able to test the product, making sure to that every tool your shortlist works and that it is able to integrate well with your current solutions before purchasing them is an option that most organizations appreciates. A risk-free trial gives you the opportunity to do so.
A 60-day free Pro trial is available for Power BI. Power BI Desktop, a perpetually free version for individual users, is also available.
Tableau provides a 14-day free trial of Tableau Server or Tableau Online, which includes Tableau Desktop. Tableau Public, a perpetually free version, is also available.
QlikSense, the improved SaaS version of QlikView, is available for a 30-day free trial. QlikView Personal Edition, a perpetually free version of its software for personal use, is also available.
Out of the three tools, Microsoft provides the longest and most comprehensive free trial, so is is the best option among the three.

Price
Your budget is also an important factor to be considered when choosing a software.
Power BI comes with two advance versions (Power BI Pro & Power BI Premium) and these packages cost $10 per user per month.
Tableau’s advance version cost $100 per user per month.
QlikView’s advance version cost $30 per user per month.
Power BI is the most cost effective option of the three tools.

Overall
When these 13 main requirements are compared among the three tools, Power BI comes out on top of Tableau and QlikView. Based on the analysis, it claimed the advantage 10 times – and in many of the most important features – making it the more appealing choice.