business intelligence tools power bi supplier

We’ve researched the best business intelligence software according to user popularity and major features. Compare the top BI tools in the chart below, and read on to learn more about how these data analytics tools can improve your enterprise outcomes. For a custom set of recommendations of the best BI software for your company, try our Product Selection Tool at the top of the page.

Business intelligence (BI) software is a set of business analytics solutions used by companies to retrieve, analyze, and transform data into useful business insights, usually within easy-to-read visualization like charts, graphs, and dashboards. Examples of the best BI tools include data visualization, data warehouses, interactive dashboards, and BI reporting tools. In contrast to competitive intelligence that analyzes data from outside sources, a BI solution pulls internal data that the business produces into an analytics platform for deep insights into how different parts of the business affect one another.

As big data — the tendency for companies to collect, store, and mine their business data — has gained in prominence, so has the popularity of BI software. Companies generate, track, and compile business data at a scale never before seen. And the ability to integrate cloud software directly with proprietary systems has further driven the need to combine multiple data sources and take advantage of data preparation tools. But all this data is nothing if we can’t make sense of it and use it to improve business outcomes.

Business intelligence has traditionally taken the form of quarterly or yearly reports that report on a defined set of key performance indicators (KPIs), but today’s BI reporting software is backed by data analytics tools that work continuously and at light speed. These insights can help a company choose a course of action in a matter of minutes.

BI software interprets a sea of quantifiable customer and business actions and returns queries based on patterns in the data. BI comes in many forms and spans many different types of technology. This business intelligence tools comparison of software vendors breaks down the three major stages data must go through to provide business intelligence, and provides considerations for purchasing BI tools for different sized businesses.

Business intelligence tools and platforms come in several forms for varying business needs. Companies looking to provide data services to business users will find self service BI software will meet the needs of most of their users. Data visualization tools are helpful for teams that are dipping their toes into data analytics but may not have lots of extra development resources available. Data warehousing tools provide the underlying infrastructure that can house and cleanse data before serving it up through visualizations. And BI tools provide end-to-end dashboard tools to store, cleanse, visualize, and publish data.

Some business intelligence platforms pull data for analysis directly from the source applications via a native API connection or webhook. Other business intelligence tools require the use of a cloud data storage system to aggregate diverse data sets in a common location. Small businesses, single departments, or individual users may find that a native connection works well, but large corporations, enterprise companies, and companies that generate large data sets will need a more comprehensive business intelligence setup.

Regardless of whether businesses choose to store their data in a data warehouse, a cloud database, an on-premise server, or run queries on the source system, data analysis and the resulting insights make the field appealing to business users. Data analytics tools vary in terms of complexity, but the general method of combining large amounts of normalized data to identify patterns remains consistent across business intelligence platforms.

Perhaps one of the most exciting aspects of BI, advanced analytics features like predictive and prescriptive analytics function as a subset of data mining. The tools use existing data sets and algorithmic models to help companies make better business decisions.

Unstructured data can’t be stored in neatly categorized sets of similarly-formatted data rows or columns, which makes it impossible for traditional data mining software to analyze. However, this data is often crucial to understanding business outcomes. With so much data in unstructured form, text analytics should be a key consideration when researching the best business intelligence tools.

Natural language processing (NLP) software, also known as text analytics software, combs large sets of unstructured data to find hidden patterns. NLP is particularly interesting for businesses that work with social media. Using the right software mix of data ingestion and AI, a business can set up rules to track keywords or phrases — a business’s name, for example — to find patterns in how customers use that language. Natural language processing tools also measure customer sentiment, provide actionable insight into lifetime customer value, and learn customer trends that can inform future product lines.

For example, a supply chain’s data metrics can include location, SKU, date of purchase, salesperson, and expiration date. OLAP tools can provide the analysts with a clear picture of any combination of these metrics. That provides analysts with the power to surface insights that would otherwise be hidden within two or three-dimensional spreadsheets.

Not every business user needs full access to everything available in the dashboard. Most employees only need access to a dashboard of their most important metrics. It gives at-a-glance access to a range of predefined visualizations. While each company can define its own dashboards based on custom business needs, some possible dashboard tools provide:

Some BI solutions also offer interactive dashboard tools where business users can manipulate the data visualizations, dig for a more detailed view, and zoom out for more context.

BI applications promise to clarify data analytics tools for the most non-technical of employees, which has driven the demand for embedded BI. These features let companies build data visualizations within their cloud BI software, and dynamically serve those visualizations to internal and external customers within company apps.

Visualizations, reports, and dashboards that are embedded in a company webpage or cloud app save companies thousands of hours and hundreds of thousands of dollars they would otherwise use to build BI reporting tools and analytics dashboards from scratch to track business performance. These tools now give business users access to custom, plug-and-play visualizations, greatly speeding the time to market.

QlikView business intelligence from Qlik is a powerful tool trusted by huge corporations such as Cisco, Raymond James, and KitchenAid, and it’s easy to see why. User-friendly interfaces and flexible customization make the tool an ideal self-service BI for your team to use, and users report excellent customer support and training.

Best suited for enterprise-level businesses, Birst offers a user-friendly experience for both developers and end-users, including a complete API that allows you to integrate other tools and automate simple tasks. Birst also provides both governance and agility in its platform, allowing for centralized, controlled data while also letting you source data from multiple points across your business.

Standout feature: Birst is one of the only BI tools that offers governance and agility in one platform, giving companies the power to keep a single source of truth for data while remaining nimble.

Looker is another bi tool that’s grown in popularity in recent years. The tool offers easy and attractive reporting, but unlike many other BI tools, Looker updates dashboards regularly, providing you with the most up-to-date information in real time.

As a pioneer among business intelligence tools, MicroStrategy was one of the first BI tools to be picked up by large corporations after McDonald’s signed a $10 million contract with the company in 1992. The tool continues to deliver today, offering fast and comprehensive reporting tools and best-in-class security features.

While it is best known as one of the top business intelligence tools on the market, BOARD also offers performance management, analytics, and data discovery solutions all in one platform. Combine its all-in-one approach to business intelligence with clear data visualization tools, and it’s easy to see why BOARD is among our top picks for business intelligence solutions.

Consistently recognized as one of the best BI solutions around, Microsoft Power BI offers flexible plans for businesses of all sizes and integrates with your Microsoft office tools such as Excel. In addition to sourcing data from a variety of cloud and on-premise sources, Power BI can also collect data from IoT devices.

Artificial intelligence (AI) and machine learning (ML) are computing trends that have touched nearly every corner of the technology industry because of their abilities to spot patterns and learn from existing data. BI in particular is ripe for the growth of ML products because the tools thrive in high data-density environments. AI and ML algorithms can be used on existing data to learn, predict, and better forecast for businesses.

Cloud computing — and the databases that it produces — give companies thousands of daily data points to train machine learning algorithms. Companies that use BI will find that data integration between AI tools and their cloud data warehouses is often the logical next step.

In-memory database processing utilizes RAM instead of disk or hard drive processing in order to read information. Accessing information in this manner increases the application performance exponentially. The increasing power of RAM in our cloud or on-premise computing environments coupled with the demand for more agile systems means this software has a large stake in the future of BI. Dramatic drops in memory prices are making it a more popular option than running data analysis through multidimensional databases and cubes.

More and more, BI users aren’t IT staff; they’re employees with a standard amount of technological savvy that want to harness the power of cloud BI to get a competitive advantage.

Comparing all the features these tools offer side by side can be a daunting task, but we can help you shave hours off your software search. Contact us today or fill out the form at the top of the page to start the process. We’ll send you a set of recommendations that fit your feature requirements and data needs.

BI tools make it simpler to corral the right data and visualize it in ways that enable us to understand what it means. But how simple that process gets, and how you can visualize the data depends on the tool: Picking the right one for your needs becomes important.

Board International combines three tools in one: BI, predictive analytics and performance management. While it aims to offer something for everyone, it predominately focuses on finance-oriented BI. It has modules for finance (planning, consolidation), HR (skills mapping, workforce planning), marketing (social media analysis, loyalty and retention monitoring), supply chain (delivery optimization, supplier management), sales (cross-selling and up-selling analysis) and IT (KPIs, service levels). The company is Swiss, but the software is available in English, Spanish, Chinese, Japanese, French, German and Italian. The latest version of its platform has replaced its multidimensional online analytical processing (MOLAP) approach with an in-memory calculation engine.

Domo is a cloud-based platform focused on business-user-deployed dashboards and ease-of-use. It offers business intelligence tools tailored to various industries (such as financial services, health care, manufacturing and education) and roles (including CEOs, sales, BI professionals and IT workers). CIOs might start by checking out how it handles data from AWS, Jira, GitHub, or New Relic before looking at how over 500 other integrations can help the rest of the enterprise.

Dundas BI from Dundas Data Visualization is used predominantly for creating dashboards and scorecards, the company’s historic strengths, but it can also perform standard and ad-hoc reporting. Analysis and visualization are performed through a web interface that can adapt to users’ skills: Power users and standard users see different features. The latest version has a new in-memory engine, a new natural language query capability, and adds point-and-click trend analysis, support for Linux, and an application development environment for customized analytic applications. Dundas BI has been tailored for 19 industries, including clean tech, mining and construction, in addition to the usual suspects such as banking and healthcare. It sells to large enterprises but specializes in embedded BI.

With the Power BI Desktop app for Windows, users can analyze and visualize data from local or cloud sources, publishing their reports to the Power BI platform. It offers data preparation, visual-based discovery, interactive dashboards, and augmented analytics. The free Power BI Desktop version suits isolated users; the Pro version makes collaborative analysis easier, for a monthly fee, leveraging Microsoft Office365, SharePoint and Teams to control access to raw data and published reports. For enterprises that want to go all-in, the Premium tier makes self-service data prep possible with prebuilt connectors to corporate data held in Microsoft Dynamics 365, Azure SQL Data Warehouse, or third-party sources such as Salesforce.

MicroStrategy targets the enterprise BI market in a broad range of industries with cloud, on-premises and hybrid deployment options. It features a drag-and-drop interface to help users create customized data visualizations and build personalized, real-time dashboards. MicroStrategy touts federated analytics that allow customers to leverage existing investments in data sources such as Tableau, Qlik and Power BI, and blend the data to build reports and insights. It also features enterprise semantics graph, which indexes data assets to enrich data silos with location intelligence and real-time telemetry. MicroStrategy offers a free, 30-day full platform trial.

Oracle has spent the past several years bulking out its Oracle Analytics Cloud offering, launched in 2014 as an outgrowth of its flagship Business Intelligence Enterprise Edition suite. In 2020, it added a Cloud HCM offering to provide self-service workforce analytics to HR executives, analysts and line-of-business leaders. Oracle has focused on making its cloud offering intuitive and user-friendly, with powerful reporting and machine learning features. Key features include data preparation, data connectors, visualizations, predictive analytics, a native mobile app, and support for embedded analytics.

Sisense’s BI software stack covers everything from the database through ETL and analytics to visualization — and it claims its In-Chip database engine is faster even than in-memory databases. It is best known for embedded BI uses. The latest version adds new machine learning capabilities. Sisense is available on premises or in the cloud. There are solutions for finance, marketing, sales, HR and IT, as well as customer service and operations and logistics departments. Sisense also makes it possible to offer the analytics tools to users outside the enterprise by embedding them in web applications. Sisense acquired Periscope Data in September 2019 and is in the process of integrating advanced analytics capabilities gained through the acquisition.

Formerly known as Einstein Analytics, Salesforce rebranded the offering as Tableau CRM in October 2020. Tableau CRM integrates Einstein Analytics’ advanced analytics capabilities — including predictive and prescriptive analytics — into Tableau’s full range of offerings. The goal is to extend self-service access to data to users across the business. Users can build predictive models for their data. There are industry-specific templates, and tailored tools for sales, service, marketing, and IT departments. The first fruit of the newly integrated offering is Einstein Discovery in Tableau, an AI and machine learning platform for predictive and prescriptive analytics. More integrations are planned. Salesforce is working on connecting Tableau natively to the Einstein Analytics data store, which will take advantage of the performance optimizations and native Salesforce security integration. That’s planned for release later in 2021.

Tibco Spotfire is a self-service, AI-powered data visualization platform for dashboards, interactive visualization, data preparation, and workflow. The platform offers machine learning-based data preparation capability to support building complex data models. It is deployed across many verticals, including financial services, energy, manufacturing, consumer packaged goods, government, travel and logistics, healthcare, and life sciences. The latest version adds support for Python.

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.

In this piece we present a concise overview of our recently updated, independent BI & Analytics study of the software vendor Microsoft and its product portfolio (such as Microsoft SQL Server, Power BI and Azure Databricks). Microsoft BI & Analytics comes out on top in our research. Microsoft is vigorous in artificial intelligence and the least strong in decision management. Within the context of BI & Analytics, we have put together the main advantages and disadvantages of Microsoft Business Intelligence, and arranged them by topic (business intelligence, big data, artificial intelligence and data science). We also point out the distinguishing features of the most popular products such as Microsoft SQL Server, Power BI and Azure Databricks et cetera.

In our independent study we also judged the various tools of Microsoft BI & Analytics software. We examined no less than 690 aspects. The image below illustrates the pros and cons of Microsoft Business Intelligence. Please note that Passionned Group is 100% independent of the suppliers in our guide. We do not sell licenses, we do not make deals or having any legal ties to the vendor. Among other things, we help and advise companies in the proper selection of BI tooling.

Under this heading, we report the (main) characteristics of Microsoft Business Intelligence, including some of its features and any related products. This product group consists of Power BI, Microsoft Azure, Microsoft SQL Server, Microsoft Power Query, Microsoft AI, Microsoft Machine Learning, Microsoft R Server, Microsoft Advanced Threat Analytics, Microsoft Data Platform and Microsoft Flow Analytics. This product / group of products can be best defined by the following characteristics:analytics

Are you considering hiring an external consultant specialized in Microsoft Business Intelligence who can do a mountain of work for you and implement an Microsoft Business Intelligence application? Or do you want to develop an application for one of the related products like Power BI, Microsoft Azure, Microsoft SQL Server, SSAS, Power BI Report Server, Power BI Desktop, Power BI Premium, Azure Synapse Analytics, Microsoft AI and SQL Server Reporting Services? Our specialists are happy to assist you. Indeed, hiring Microsoft Business Intelligence developers is sometimes unnecessary and costly. Leave a message here and we will be happy to work for you.

Under this heading, we describe Power BI, including some of its features and any related products. This product group consists of Power BI Desktop, Power BI Report Server, Power BI Premium, Microsoft Power BI Pro, Power BI Report Builder and Microsoft Power BI Enterprise. This product / group of products can be best defined by the following functionalities:BI infrastructure > Application Programming Interface > REST APIs

In this section, we provide a description of Power BI Desktop, including some of its features and any related products. This product / group of products can be best characterized by the following features:BI infrastructure > Application Programming Interface

In this paragraph, we report the (main) characteristics of Power BI Report Server, including some of its features and any related products. This product can be defined by the following features:BI infrastructure > Application Programming Interface > REST APIs

We don’t reveal everything here but, in this paragraph, we provide a description of Power BI Premium, including some of its features and any related products. Power BI Premium can be best characterized by the following features:BI infrastructure > Application Programming Interface

In this paragraph, we provide a description of Microsoft Power BI Pro, including some of its features and any related products. The product Microsoft Power BI Pro can be best characterized by the following characteristics:analytics

In this paragraph, we provide a description of Power BI Report Builder, including some of its features and any related products. The Power BI Report Builder can be best characterized by the following functionalities:BI infrastructure > authentication

In this paragraph, we provide a description of Microsoft Power BI Enterprise, including some of its features and any related products. This product can be best characterized by the following properties:BI infrastructure > Application Programming Interface

We do not display here all the features but, in this paragraph, we provide a description of Microsoft Power Query, including some of its features and any related products. This product / group of products can be best defined by the following functionalities:BI infrastructure > SDK

Do you want to know the intricacies of all the functionalities (100+) of Microsoft Power Query? In that case open the BI & Analytics Guide™ 2022 here.

It is difficult to determine exactly what a license of Microsoft SQL Server, Power BI and Azure Databricks costs because it depends on the country, the number of users (or the number of CPUs in the case of server software), the connectors to data sources, and at what point in the year you request a quote. If you do this a few weeks before the end of Microsoft’s fiscal quarter, you may be in for a decent discount. In addition, it makes sense running the software in the cloud. You then only pay for what you use. The purchase cost of Microsoft SQL Server, Power BI and Azure Databricks may not be the largest cost item, but maintenance and support do return each year.

In the following paragraphs, we name all the advantages and disadvantages of Microsoft BI & Analytics, Microsoft SQL Server, Power BI and Azure Databricks, et cetera. These are not necessarily definitive because: Microsoft can currently work to creating missing functionality at this time (such as support for AIX and Unix). In addition, documentation may lag behind current events.

Microsoft has an excellent rating in our independent BI & Analytics survey on the subject ‘Analytics’ (for this section Microsoft comes out as the absolute market leader in our research) with a score of 100%, relative to other vendors. The following criteria were used: analytics platform, customer analytics, marketing analytics, retail analytics, data center analytics, operations analytics and quality analytics. In doing so, we analyzed the following five products: Azure Synapse Analytics, Azure Stream Analytics, Power BI, Azure Data Lake and Azure Databricks. In total, we examined 127 criteria in this category. Would you like to learn more about the topic ‘Analytics’? Then download here our BI & Analytics Guide 2022. Or take a deep dive in the following content:

Microsoft has an excellent performance in our independent BI & Analytics survey on the subject ‘Business Intelligence’ (for this section Microsoft comes out as the absolute market leader in our research) with a score of 100%, compared to other vendors. We looked at the following criteria, among others: reporting, business intelligence platform, enterprise business intelligence and business process monitoring. In doing so, we looked at the following five products: Power BI, Power BI Desktop, Power BI Premium, Power BI Report Server and Power BI Report Builder. In total, we examined 75 criteria in this category. Would you like to learn more about the topic ‘Business Intelligence’? Then download here our BI & Analytics Study. Or take a deep dive in the following content:

Microsoft has an excellent performance in our 100% vendor-independent BI & Analytics survey of the theme ‘Big Data’ (for this section Microsoft comes out as the absolute market leader in our research) with a score of 100%, relative to other vendors. We looked at the following criteria, among others: IoT, streaming, big data analytics, unstructured data, complex data, data lakes and Blob storage. In doing so, we looked at the following five products: Azure Synapse Analytics, Azure Data Lake, Azure Cognitive Services, Microsoft SQL Server and Power BI Premium. In total, we examined 58 criteria in this category. Would you like to delve further into the topic ‘Big Data’? Then download here our BI & Analytics Guide 2022.

The vendor Microsoft has an excellent rating in our 100% vendor-independent BI & Analytics survey on the section ‘Data Connectivity’ (for this section Microsoft comes out as the absolute market leader in our research) with a score of 100%, relative to other vendors. We looked at the following criteria, among others: Sharepoint, connectivity, native, Teradata, Google Analytics, Amazon Redshift and PostgreSQL. In doing so, we assessed the following products: Microsoft Power Query. In total, we examined 95 criteria in this category. Would you like to learn more about the topic ‘Data Connectivity’? Then download here our BI & Analytics Guide 2022.

The vendor Microsoft has an excellent rating in our current BI & Analytics survey on the section ‘Data Governance’ (for this section Microsoft comes out as the absolute market leader in our research) with a score of 100%, relative to other vendors. The following criteria were used: data management, data quality, data catalog, data encryption, data lineage and data acquisition layer. In doing so, we looked at the following products: Microsoft Power BI Enterprise. In total, we examined 82 criteria in this category. Would you like to learn more about the topic ‘Data Governance’? Then download here our BI & Analytics Guide 2022. Or take a deep dive in the following content:

We organize various courses in the field of BI & Analytics but can also provide specific Microsoft training, for example as incompany. Then think about the following software: Microsoft SQL Server, Power BI and Azure Databricks. Of course, such training is framed with the ideas of the intelligent, data-driven organization.

In this piece we present a concise overview of our recently updated, independent BI & Analytics study of the software vendor Microsoft and its product portfolio (such as Microsoft SQL Server, Power BI and Azure Databricks). Microsoft BI & Analytics comes out on top in our research. Microsoft is vigorous in artificial intelligence and the least strong in decision management. Within the context of BI & Analytics, we have put together the main advantages and disadvantages of Microsoft Business Intelligence, and arranged them by topic (business intelligence, big data, artificial intelligence and data science). We also point out the distinguishing features of the most popular products such as Microsoft SQL Server, Power BI and Azure Databricks et cetera.

In our independent study we also judged the various tools of Microsoft BI & Analytics software. We examined no less than 690 aspects. The image below illustrates the pros and cons of Microsoft Business Intelligence. Please note that Passionned Group is 100% independent of the suppliers in our guide. We do not sell licenses, we do not make deals or having any legal ties to the vendor. Among other things, we help and advise companies in the proper selection of BI tooling.

Under this heading, we report the (main) characteristics of Microsoft Business Intelligence, including some of its features and any related products. This product group consists of Power BI, Microsoft Azure, Microsoft SQL Server, Microsoft Power Query, Microsoft AI, Microsoft Machine Learning, Microsoft R Server, Microsoft Advanced Threat Analytics, Microsoft Data Platform and Microsoft Flow Analytics. This product / group of products can be best defined by the following characteristics:analytics

Are you considering hiring an external consultant specialized in Microsoft Business Intelligence who can do a mountain of work for you and implement an Microsoft Business Intelligence application? Or do you want to develop an application for one of the related products like Power BI, Microsoft Azure, Microsoft SQL Server, SSAS, Power BI Report Server, Power BI Desktop, Power BI Premium, Azure Synapse Analytics, Microsoft AI and SQL Server Reporting Services? Our specialists are happy to assist you. Indeed, hiring Microsoft Business Intelligence developers is sometimes unnecessary and costly. Leave a message here and we will be happy to work for you.

Under this heading, we describe Power BI, including some of its features and any related products. This product group consists of Power BI Desktop, Power BI Report Server, Power BI Premium, Microsoft Power BI Pro, Power BI Report Builder and Microsoft Power BI Enterprise. This product / group of products can be best defined by the following functionalities:BI infrastructure > Application Programming Interface > REST APIs

In this section, we provide a description of Power BI Desktop, including some of its features and any related products. This product / group of products can be best characterized by the following features:BI infrastructure > Application Programming Interface

In this paragraph, we report the (main) characteristics of Power BI Report Server, including some of its features and any related products. This product can be defined by the following features:BI infrastructure > Application Programming Interface > REST APIs

We don’t reveal everything here but, in this paragraph, we provide a description of Power BI Premium, including some of its features and any related products. Power BI Premium can be best characterized by the following features:BI infrastructure > Application Programming Interface

In this paragraph, we provide a description of Microsoft Power BI Pro, including some of its features and any related products. The product Microsoft Power BI Pro can be best characterized by the following characteristics:analytics

In this paragraph, we provide a description of Power BI Report Builder, including some of its features and any related products. The Power BI Report Builder can be best characterized by the following functionalities:BI infrastructure > authentication

In this paragraph, we provide a description of Microsoft Power BI Enterprise, including some of its features and any related products. This product can be best characterized by the following properties:BI infrastructure > Application Programming Interface

We do not display here all the features but, in this paragraph, we provide a description of Microsoft Power Query, including some of its features and any related products. This product / group of products can be best defined by the following functionalities:BI infrastructure > SDK

Do you want to know the intricacies of all the functionalities (100+) of Microsoft Power Query? In that case open the BI & Analytics Guide™ 2022 here.

It is difficult to determine exactly what a license of Microsoft SQL Server, Power BI and Azure Databricks costs because it depends on the country, the number of users (or the number of CPUs in the case of server software), the connectors to data sources, and at what point in the year you request a quote. If you do this a few weeks before the end of Microsoft’s fiscal quarter, you may be in for a decent discount. In addition, it makes sense running the software in the cloud. You then only pay for what you use. The purchase cost of Microsoft SQL Server, Power BI and Azure Databricks may not be the largest cost item, but maintenance and support do return each year.

In the following paragraphs, we name all the advantages and disadvantages of Microsoft BI & Analytics, Microsoft SQL Server, Power BI and Azure Databricks, et cetera. These are not necessarily definitive because: Microsoft can currently work to creating missing functionality at this time (such as support for AIX and Unix). In addition, documentation may lag behind current events.

Microsoft has an excellent rating in our independent BI & Analytics survey on the subject ‘Analytics’ (for this section Microsoft comes out as the absolute market leader in our research) with a score of 100%, relative to other vendors. The following criteria were used: analytics platform, customer analytics, marketing analytics, retail analytics, data center analytics, operations analytics and quality analytics. In doing so, we analyzed the following five products: Azure Synapse Analytics, Azure Stream Analytics, Power BI, Azure Data Lake and Azure Databricks. In total, we examined 127 criteria in this category. Would you like to learn more about the topic ‘Analytics’? Then download here our BI & Analytics Guide 2022. Or take a deep dive in the following content:

Microsoft has an excellent performance in our independent BI & Analytics survey on the subject ‘Business Intelligence’ (for this section Microsoft comes out as the absolute market leader in our research) with a score of 100%, compared to other vendors. We looked at the following criteria, among others: reporting, business intelligence platform, enterprise business intelligence and business process monitoring. In doing so, we looked at the following five products: Power BI, Power BI Desktop, Power BI Premium, Power BI Report Server and Power BI Report Builder. In total, we examined 75 criteria in this category. Would you like to learn more about the topic ‘Business Intelligence’? Then download here our BI & Analytics Study. Or take a deep dive in the following content:

Microsoft has an excellent performance in our 100% vendor-independent BI & Analytics survey of the theme ‘Big Data’ (for this section Microsoft comes out as the absolute market leader in our research) with a score of 100%, relative to other vendors. We looked at the following criteria, among others: IoT, streaming, big data analytics, unstructured data, complex data, data lakes and Blob storage. In doing so, we looked at the following five products: Azure Synapse Analytics, Azure Data Lake, Azure Cognitive Services, Microsoft SQL Server and Power BI Premium. In total, we examined 58 criteria in this category. Would you like to delve further into the topic ‘Big Data’? Then download here our BI & Analytics Guide 2022.

The vendor Microsoft has an excellent rating in our 100% vendor-independent BI & Analytics survey on the section ‘Data Connectivity’ (for this section Microsoft comes out as the absolute market leader in our research) with a score of 100%, relative to other vendors. We looked at the following criteria, among others: Sharepoint, connectivity, native, Teradata, Google Analytics, Amazon Redshift and PostgreSQL. In doing so, we assessed the following products: Microsoft Power Query. In total, we examined 95 criteria in this category. Would you like to learn more about the topic ‘Data Connectivity’? Then download here our BI & Analytics Guide 2022.

The vendor Microsoft has an excellent rating in our current BI & Analytics survey on the section ‘Data Governance’ (for this section Microsoft comes out as the absolute market leader in our research) with a score of 100%, relative to other vendors. The following criteria were used: data management, data quality, data catalog, data encryption, data lineage and data acquisition layer. In doing so, we looked at the following products: Microsoft Power BI Enterprise. In total, we examined 82 criteria in this category. Would you like to learn more about the topic ‘Data Governance’? Then download here our BI & Analytics Guide 2022. Or take a deep dive in the following content:

We organize various courses in the field of BI & Analytics but can also provide specific Microsoft training, for example as incompany. Then think about the following software: Microsoft SQL Server, Power BI and Azure Databricks. Of course, such training is framed with the ideas of the intelligent, data-driven organization.

Transforming your business into an insight-driven operation starts with a modern business intelligence tool, and choosing the right tool is critical for success. Not all BI tools are created equal. To make the right choice, organizations must consider how business intelligence will drive value, which users will be doing the driving, and the full spectrum of costs associated with deploying the solution.

Before getting into feature/function discussions, make sure you’re considering business intelligence tools that offer a solid foundation to support data-driven digital transformation. At the core of this foundation is intuitive data access, robust governance, and broad deployment options. An effective BI tools comparison process will help you gauge the ability of any solution to effectively democratize data and drive data literacy throughout your business.

Business intelligence and analytics can help decision-makers better manage their organization’s supply chain by visualizing data to be actionable and directly accessible. This can be elevated by self-service capabilities from platforms and tools such asPower BIthat enable business and nontechnical users to create their own reports, run their own queries, or analyze the meaning and context behind data.

Power BIis one of the platforms that can help convert seemingly unrelated sources of data into coherent and interactive visualizations that can be used to manage the supply chain. While tools that provide reports such as enterprise resource planning (ERP) and materials requirement planning (MRP) software can provide snapshots of activities in the supply chain, using them alone is no longer enough.

When implemented properly, Power BI offers a versatile solution to visualize the supply chain’s operations and performance while also having the flexibility to integrate it with existing tools and external apps or online services, which encompasses:

When generating reports or creating visualizations, underlying information is accessed and processed from a data source. Depending on the type of data source — such as online services like Google Analytics or QuickBooks, cloud databases like those in Azure, or an Excel file on a local computer —Power BI Desktopcan be used to connect to the data source, import the data, and query and load it.

Power BI makes it easy to consolidate various kinds of data from different parts of the organization and display them in a single visualization or dashboard. Even if the user doesn’t have direct connection to a data source, they can still access and use them to generate reports or visualizations. Users don’t have to go through the time-consuming, back-and-forth process of requesting access to data. If real-time information is needed, aPower BI gatewaymight be needed to be able to refresh data. If data is on cloud-based tools and services such as SharePoint or Azure SQL Database, reports or visualizations refresh automatically if there are updates.

Not all metrics and KPIs need to be tracked or visualized in a dashboard. Designing and building awarehouse KPI dashboard, for instance, depends on the business need and the audience. It also depends on whether it needs to be an analytical, operational, strategic, or tactical dashboard. Users might even need different reports to home in on different aspects ofwarehouse operations— from measuring inbound productivity, tracking outbound performance, or measuring putaway efficiency. Power BI dashboards can be customized to meet different business requirements. Itsfilterfunctionality anddrag-and-dropfeature, for example, can be used to configure what data to display, visualize, or analyze, giving users the specificity they need without having to painstakingly generate new dashboards or reports.

Power BI has prescriptive and predictivecapabilitiesthat help improve business decision-making. These capabilities can involve knowing thebuying trendsand behaviors of customers,tracking project schedules, monitoring the competition, benchmarking the performance of a retail store or a warehouse, estimating thelead timeof deliveries, and identifying when to launch outreach or promotional activities, to name a few. Users can useData Analysis Expressions (DAX) in Power BI, for instance, to analyze, compare, and forecast information such as product demand, costs, revenues, transactions, or inventories across different timeframes or categories.

Having vast amounts of data to analyze is good, but it’s more important to know how they can be meaningfully linked to the supply chain’s critical success factors. Power BI has themetrics featurethat enables users to define andvisualize KPIsas well as configure the ways they caninteracton the dashboard. This especially applies to organizations that want to track their supply chain across multiple, dispersed vendors or partners that use different data sources, platforms, or ecosystems.

Power BI enables data to be visualized even when the format of data sources is different, such as non-SQL databases, CSV files, or Excel workbooks that various platforms typically provide (e.g., SAP, Oracle ERP). This is particularly helpful if different business functions within the supply chain use different tools for data management. Power BI supports importing data frommultiple sourcesbefore it’s loaded into a dashboard, giving users more interactivity with their data.

Tracking movement in logisticsAnalyzing logistics data (e.g., forecasting products needed for specific warehouses, knowing the status of shipped products) can be done by using Power BI’sinactive model relationshipsin the date and fact tables. This enables data to be filtered by customer, product, or region, so the movement of specific inventory through time can be seen. It can even help estimate the costs of shipping it.

Monitoring sales or ordersAPower BI sales dashboardcan extract data from a customer relationship management (CRM) system and present it in a more palatable format. Data from invoice and order lines, for instance, can be used to analyze if sales are growing or decreasing.

Checking vendor complianceFor example, anon-time, in-full(OTIF) report can be generated by using thedata transformationfeature in Power BI to datasets related to time (i.e., requested and actual delivery dates) and quantity (i.e., ordered and delivered quantity) and using some formulas to calculate OTIF.

Planning and scheduling productionAGantt chartdeveloped in Power BI adds interactivity to managing projects and optimizing the utilization of resources required for production. APower BI Gantt chartcan also be complemented by add-ins such asdynamic labelsthat allows complex information to be presented or highlighted without the intricacy of creating DAX measures.

Managing inventoriesThere are several techniques to track and report inventory. Power BI can take sales data across different financial periods and measure them against current stocks in warehouses, using relevant DAX calculations to see if the warehouses are stocked well enough to adjust to current and future demand.Report slicers, too, can be used to filter inventory by category, lines of business, and geography, which is useful for analyzing commonly used filters in the report.

Measuring quality assurancePower BI can be used to analyzesupplier qualityby measuring defects against the downtime that they caused. This can be broken down to different timeframes and categories such as defect type, vendor, facility, or material, but this will depend on the data.

Indeed, Power BI can empower employees, managers, and decision-makers with self-service data intelligence that they can embed in their operations and customer touchpoints, enabling day-to-day and long-term decisions that better manage their organization’s supply chain.

Power BI is more than just a data visualization tool. Users can build on itsAI-enabled analytics, while data modeling tools are available before data is loaded into dashboards or reports. It can be deployed to the cloud or on-premises, and it can be an intuitive platform for organizations that already use Microsoft Office and Azure solutions where it can be easily integrated.

Lingaro is aMicrosoft Gold Partner, with certified developers, engineers, and solution architects who work with supply chain leaders and decision-makers in using Power BI to embark on their journey toward digital transformation. Oursuccess storiesinclude helping a Fortune 500 company generate annual savings of US $2.6 million by developing intuitive and interactive Power BI dashboards as well as enabling a global brand to open business opportunities — estimated at US $3.5 million — in just one and a half years by improving their use of data.

Lingaro’ssupply chain analytics practicedelivers business intelligence solutions that strengthen digital supply chains — from inventory management, demand forecasting, warehouse operations, transportation, and manufacturing to sustainability. To get a glimpse of Lingaro’s industry-recognizedexpertise in Power BI, take a look at some of the demos we created — fromcustomer survey analysisandexecutive reporting dashboardtoPower BI objects.

Today, data is more important than ever before. This is the main reason more manufacturers are turning to Business Intelligence (BI) tools to help them make sense of the information they’re collecting. BI tools can help you track key performance indicators (KPIs), understand trends, and make better decisions for your business. And this will only become more important as regulations change, competition intensifies, and customer needs evolve.

As things continue to change, it’ll be essential for manufacturers to remain agile enough to adapt quickly – and that means looking at what Business Intelligence tools they’re using now, and how their needs might shift over the next few years. As an example, there’s been a significant shift from big Data Analytics over recent years as IoT (Internet of Things) solutions become more ubiquitous. As a result, analytics solutions that were designed for analyzing small datasets have fallen out of favor with larger manufacturing companies.

Tools aren’t the only important factor, either. The manufacturing industry is under constant pressure to improve productivity, while also reducing costs. In order to stay competitive, manufacturers must adopt new technologies where they can. With so many options on the market, it can be difficult to know which BI tool is right for your business. Luckily, this question has been answered by a study from International Data Corporation (IDC). IDC’s 2018 Worldwide Semiannual Manufacturing Smart Machines Spending Guide revealed that artificial intelligence-powered analytics will become increasingly important over the next five years.

According to a report from marketsandmarketsblog.com, The global AI-powered analytics market is projected to grow from $10.5 billion in 2021 to $28.1 billion by 2026 – at a CAGR of up to 21.7% over the forecasted period.

What does this mean for manufacturing? Manufacturers need data about their performance – not just about their products or services but also about their employees and processes. Using intelligent systems like augmented reality or virtual reality combined with artificial intelligence-powered analytics will allow manufacturers to better predict outcomes and make data-driven decisions that drive profitability while improving employee engagement levels.

One organization already doing this is Caterpillar Inc., who implemented digital transformation into its retail stores through an AR application called CatAdvisor. CatAdvisor uses computer vision and 3D point clouds to help retailers sell more products, identify inventory gaps, analyze customer preferences and monitor store traffic patterns. And now Caterpillar is piloting sensors in stores using machine learning and IoT technology to get even more granular insights into customers’ preferences. With these AI-powered solutions available today, there really isn’t any excuse for a manufacturer not to embrace advanced analytics!

Even the concept of operations management in the manufacturing industry is going through significant changes. In the past, the focus was on production efficiency and cost reduction. Today, the focus is on customer needs and market demand. To meet these new challenges, manufacturers are turning to business intelligence (BI) tools and Microsoft Dynamics 365 F&O. Together, these modern solutions enable better insight into product quality, reliability, compliance, and any other KPIs that impact the end customer experience.

Manufacturing companies can also use BI tools to gain insights into their own operations with real-time data analysis that can be used for decision making such as material sourcing or capacity planning. These solutions allow manufacturers to increase throughput and reduce downtime. For example, a manufacturer may have a bottleneck at one part of the process because they can’t produce enough parts quickly enough due to limited materials availability. With BI they could track down the problem by looking at lead times, inventory levels and component dependencies. With this information they could find alternative suppliers or renegotiate with existing suppliers in order to free up those materials so they can increase production volume.

Business intelligence tools are nothing new. In fact, they’ve been around for decades. But what is new is the way that manufacturers are using them to gain a competitive edge. With the rise of Industry 4.0, manufacturers are turning to business intelligence tools to help them make sense of the vast amounts of data being generated by their factories. And with the help of included Power BI connectors, integrating these tools into different systems has become incredibly easy.

Power BI Connectors are an innovative way to enhance your manufacturing business intelligence data with minimal coding. Rather than manually inputting data into your business intelligence software, connectors automatically export data from other sources directly into Power BI without the need for extensive development. This saves time and money by minimizing any manual processes involved and gets you up and running faster than ever before. You can choose from a variety of pre-built connectors for industry-leading applications like Microsoft Dynamics, SAP, Salesforce, Google Analytics, Twitter, and many more. You can even build your own if needed.

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 busine