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Business Intelligence (BI) Tools Overview

Business intelligence tools are software that can collect and process huge amounts of data from various sources like images, text files, videos, books, and public health records; integrate the data; prepare the data for analytics; and provide relevant insights to drive data-based business decisions.

BI tools overview and connecting to MongoDB

BI tools enable organizations to make better business decisions by automating most of the data analytics process and providing valuable insights. We can connect popular BI tools with MongoDB Atlas through the Atlas SQL Interface.

Built with a SQL-92 compatible dialect, mongosql, the Atlas SQL Interface, Connectors, and Drivers make it easy to natively query and visualize Atlas data with SQL-based tools while preserving the flexibility of the document model.

Through two custom-built connectors – a Microsoft-certified Power BI Connector and a Tableau Connector built in partnership with Tableau – in addition to new versions of our Atlas JDBC and ODBC Drivers for other SQL-based tools, you can eliminate the need for complex ETL and data duplication. Use custom SQL and native BI tool functionality right in your tool’s interface to transform, analyze, and report on live application data!

What is business intelligence (BI)?

Organizations today are striving to become intelligent, just like humans. Continuing the analogy, we can divide an intelligent organization into three groups:

  • Sensors are like the senses that collect data from various sources.
  • Processors are like the brain that processes the data and turns it into knowledge or insights.
  • Effectors are like our hands and legs that perform the action based on the signal given by processors (brain). Effectors consist of a flexible team of technical and non-technical people and resources.

Business intelligence is an umbrella term comprising these three processes along with the right technologies to create intelligent, data-driven organizations.

Business intelligence is an umbrella term comprised of sensors, processors and effectors.

Common examples of business intelligence:

  • Retail companies perform target marketing by managing preferences of millions of users through business intelligence.
  • Company HR uses BI tools to scan thousands of profiles and map job requirements.
  • Logistic companies use business intelligence to optimize routes and find out the fastest routes for shipments.

What are BI tools?

BI tools are special applications that can collect, process, and analyze data, and generate reports and dashboards to surface useful business insights. BI tools can also perform Online Analytical Processing (OLAP), predictive and augmented analytics, and much more.

Earlier BI tools were limited to querying and generating reports, which did not help much with making timely decisions. Modern BI tools like Tableau and PowerBI are more flexible and adaptive, and help generate actionable insights, prepare reports and dashboards, and build visualizations and performance scorecards to display KPIs and business metrics.

Through the Atlas SQL Interface, you can connect your live application data to popular BI tools to make better use of data and get timely insights.

popular BI tools

Why use business intelligence tools?

BI reporting tools can help businesses collect and integrate data from multiple sources, and present it in an easy-to-understand manner for further analysis, reporting, and actions. BI tools create “quality data” from the raw data and work on the past and present data to analyze market trends.

Although BI tools with advanced analytical capabilities are paid, many open-source BI tools like BIRT and KNIME provide good BI reporting and analytics.

Top advantages of business intelligence software tools for your organization are:

benefits of BI tools

  • Combining data from external and internal resources for a unified view
  • Increased organizational efficiency by reducing dependency on manual reporting and data preparation tasks, thereby ensuring faster analysis and quicker decisions
  • Improved customer experience by understanding user preferences and behavior patterns based on past and current data
  • Governed data to ensure both data security and data quality — most advanced BI tools provide in-built data governance like data auditing, security, and authorization
  • Increased competitive advantage by proactive actions based on forecasts given by BI tools
  • Increased revenue and profits by analyzing past, present, and future trends to understand customers, offer targeted marketing, and improve products and services

What are the different kinds of business intelligence software?

To choose the right BI tool for your business, it would help to make a BI tools comparison based on the tool type and features. The different kinds of business intelligence software are:

Reporting BI

Reporting BI can perform all the regular tasks like preparing reports and dashboards in a fixed-format design. You can think of them like an Excel spreadsheet. Reporting BI tools make complex reports easy, and can handle datasets with a few thousand documents. Example: FineReport.

Traditional BI

A step ahead of reporting tools, traditional BI software also supports OLAP, ad-hoc analytics, and data visualization. These are suitable for much larger datasets and non-technical users can easily learn and work with traditional BI tools. Example: SAP Crystal Reports and IBM Cognos.

Self-Service BI

Self-service BI is the most common type, as most traditional BI software is not able to fulfill the complete data analytics needs of organizations. For example, Chipotle had to replace its traditional BI for a self-service BI in order to create a single view of operations that would track effectiveness at a national level.

Self-service BI provides all the features of reporting and traditional BI along with data cleaning and exploration tools, and advanced AI-driven analytics. These tools can be used by both technical and non-technical users. Self-service BI is also called agile BI. Some common BI tools are Tableau Desktop, QlikView, and MongoDB Charts.

Embedded BI

Embedded BI allows integration of self-service BI into your business applications. These tools support better visualizations, interactive reporting, dashboards, and real-time analytics. Embedded BI can also become a part of workflow automation in advanced scenarios. SAP, PowerBI, and MongoDB Charts are some top embedded business intelligence software.

MongoDB’s Atlas SQL Interface, Connectors, and Drivers allow for seamless connection to all types of BI software. Read more about how to query Atlas data with sql, directly from your BI tool.

Key business intelligence software features

The best business intelligence reporting tools have a few or more of the following features:

Security, manageability, and maintenance

BI tools provide good platform security and disaster recovery. Users can monitor usage and manage access and authentication, such as how much information is shared and with whom. BI tools support various OS like Windows and iOS. For example, Pyramid Analytics provides enterprise-grade security and governance.

Data sourcing and integration

BI software can connect to real-time and static data from multiple sources, both internal and external — for example, spreadsheets, social media, CRM systems, data warehouses, and data lakes. The tools can then integrate data so that all the data can be analyzed together.

Cloud analytics

Many BI tools like Sisense are multi-cloud capable, meaning they can build, deploy, and manage analytics on the cloud, from multiple cloud environments, and also from on-premise data. Users can visualize and explore data on the cloud platform.

Metadata management

BI software can manage metadata centrally, including extracting, storing, processing, sharing, and publishing metadata. Metadata refers to measures, indicators, hierarchies, key performance indicators, sales data, and other data that can help in business analysis.

Data transformation

BI tools automatically perform the ETL (extract, transform, load) process and prepare data for analytics. Integrity checks are done to check data accuracy and consistency. Data is transformed to a common format and then loaded into a data warehouse or data lake. Some tools, like SAS, provide AI-driven data preparation suggestions, voice integration, and smart narratives.


OLAP is a means to sort, aggregate, filter, slice, dice, and group data to present it to users. Users can extract and view data from multiple sources. OLAP gives a multidimensional view of data and is good for analysis of past data.

Data visualization

Visualizations make it easy to find trends and insights in data. Visualization includes graphs, multi-layered charts, geospatial maps, custom maps, and many more. Most BI tools support advanced graphs and interactive displays, and automatically suggest the best graphical representation for a particular query.

Data mining and augmented analytics

BI tools can mine raw data to find information and wisdom in the form of patterns and trends. This includes advanced analytics and techniques like statistics and machine learning algorithms. Many tools like ThoughtSpot, Alibaba Cloud, and PowerBI offer augmented analytics and advanced ML capabilities.


A dashboard is like a customized home page based on the role of the BI tool user. It summarizes all the reports, important graphics, and visualizations in a single view.

Predictive analytics

While OLAP is primarily focused on past data, predictive analytics goes one step ahead to take past and current data to predict future outcomes. Predictive analytics uses machine learning and artificial intelligence techniques.


BI tools improve and automate ad hoc reporting by customizing the metrics. This means each user can look at the reports they want to, rather than generating hundreds of bulky reports. The reports can be easily shared and collaborated across the team.

Other features like mobile friendliness, and ease of learning and use are also becoming important when choosing the best business intelligence tool.

MongoDB Data Lake allows users to query and transform data across various sources and data formats. MongoDB Charts as a BI tool provides all the key features like reporting, predictive analytics, dashboards, data visualization, and OLAP, without any overhead.

Who uses business intelligence software?

As the capabilities of BI tools are increasing, so are the users. Earlier, the major users of BI software were the business analysts and the IT team. Now, business intelligence reporting and analytics tools are used by many teams within a company. Some typical users of BI software include the following:

Data analysts and data scientists

Data analysts and data scientists use BI tools to find insights, visualize patterns and trends, generate and share reports with stakeholders, and help with the decision-making process.


IT teams provide the necessary infrastructure and facilities that allow other departments to function smoothly. The IT team also ensures the security and governance of data, so that more insights can be derived from the data in the right way. Learn more about business intelligence best practices.

Business analysts

Business analysts define business goals and find new ways to make overall processes more efficient. They look at dashboards, reports, and visualizations to get insights, play around with data, and discuss possible solutions to problems with stakeholders and key business partners.


CEOs use business intelligence software and reporting tools to look for organizational trends, innovation in processes, overall company growth, and operational efficiencies, and to make better business decisions.

BI tools are becoming increasingly important because of more digitalization post COVID-19. From schools to offices, everyone seems to have an online presence now. This has led to new trends within business intelligence tools:

top BI trends

  1. Artificial Intelligence (AI) and Machine Learning (ML) inclusions: Many of the best business intelligence tools are already including AI and ML features in their software. BI is becoming more than just a reporting and visualization tool.
  2. Data governance: With more data shared, data governance — meaning data quality and data security — is becoming important.
  3. Cloud adoption: Cloud BI is more beneficial for cost efficiency and flexibility, especially because of the increase in remote working environments.
  4. Automation: Business intelligence software are focusing more on automating the tedious processes of data analysis, like cleaning and transformation, so that organizations can focus more on insights and decision-making.
  5. Data literacy: Data literacy is the ability to read, comprehend, analyze, and communicate effectively with data. Data literacy can bridge the gap between analysts and business users, and make BI reporting and visualizations easy to interpret.
  6. Self-service BI: Self-service BI is already trending because users with very little technical skills can also utilize data effectively. Business users can create BI reports using the self-service BI tools without depending on technical staff, thereby reducing the time required to get insights.

Choosing the right business intelligence software

The main purpose of a BI tool is to query the right data and get useful insights to drive business solutions. The right business intelligence software should be able to answer the following questions:

  • Who will use the BI tool? While data analysts are technically sound, business users are mostly non-technical and they should be able to analyze data without the need to manually write queries. Tools like Qlik, Tableau, and PowerBI provide self-service capabilities for business users. MongoDB Charts provides advanced visualization capabilities suitable for business and technical users.
  • What is the goal you want to achieve with the BI tool? Opt for a BI tool that solves your business problem over one that has a lot of features that won’t be useful for your business objectives. For example, you can choose a tool that already has prepackaged solutions for the specific objective your business wants to achieve.
  • Where is your data located? If your data is spread across cloud platforms and on-premise data centers, choose a BI reporting tool that can seamlessly integrate all the historic and real-time data. For example, MongoDB Atlas helps source data from multiple platforms and store it in any format for better transformation. MongoDB’s Data Lake allows SQL syntax via the $sql operator. This can also be done via JDBC driver or BI Tools.
  • Do you want your BI tool to transform data? More often than not, you will need a BI tool that collects data from various sources, cleans the data, and transforms it to make it useful for analysis. MongoDB aggregation framework provides advanced queries to filter and transform data as per your business needs.
  • What is the learning curve? Choose a BI tool that is intuitive and easy to learn so you can quickly get onboard with it. For example, Alteryx Connect has a collaboration feature that connects you with other BI professionals who can help with your data questions and specific problems. Similarly, MongoDB has extensive documentation and self-learning courses that help you easily get started using MongoDB Atlas with all major BI tools.
  • Is the price within your company’s budget? BI software vendors typically provide two pricing models: on-premise and cloud hosting. Along with your budget, you should also consider the model that you prefer and conduct a BI tools price comparison.

guiding questions to choose BI software

Gartner's magic quadrant for analytics and BI platforms shows Microsoft, Tableau, and Qlik as leaders. MongoDB Connector for Business Intelligence and the Data Lake SQL connection provide an easy interface to work with the aforementioned BI tools.

Which BI tools does MongoDB connect with?

MongoDB’s Atlas SQL Interface allows you to leverage existing SQL knowledge and familiar tools to query and analyze Atlas data live. The Atlas SQL Interface uses mongosql, a SQL-92 compatible dialect that’s designed for the document model. It also leverages Atlas Data Federation functionality under-the-hood so you can query across Atlas clusters and cloud storage, like S3.

The Atlas SQL Connectors and Drivers allow you to easily connect your SQL-based business intelligence and analytics tools to Atlas, enabling you to find insights faster on live application data. Built by MongoDB, they provide a first-class querying experience of Atlas data through your preferred tool.

Tableau Connector

The Tableau Connector for MongoDB Atlas enables querying live Atlas data with access to native Tableau features, such as custom SQL, calculated columns and raw SQL pass through, and split columns. Learn more.

Power BI Connector

Certified by Microsoft, the PowerBI Connector for MongoDB Atlas enables querying live Atlas data and access to native PowerBI features, including full Power Query, Power BI Desktop, and Service functionality. Learn more

JDBC Driver

Leverage the Atlas SQL JDBC driver to connect your SQL-based tools that accept an Open Database Connectivity API. Learn more.

ODBC Driver

Leverage the Atlas SQL ODBC driver to connect your SQL-based tools that accept an Open Database Connectivity API. Learn more.

MongoDB Atlas not only offers the Atlas SQL Interface, but also many other features, like MongoDB Charts, to explore and visualize data. Read MongoDB Charts documentation for more details.

Next steps

Now that you have firsthand information on BI tools, you can enable the BI Connector for Atlas and start using MongoDB with your choice of BI tools. If your data is in MongoDB Atlas or Data Lake, consider using MongoDB Charts, the SaaS BI tool that provides rich dashboards, real-time analytics, and data visualizations. You can also learn more about Data Lake SQL access via the $sql operator.

Ready to get started?

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What are the tools used in business intelligence?

There are many types of traditional, self-service, reporting, and embedded tools used in business intelligence. Some of the popular BI tools are:

  • Power BI
  • SAP
  • Tableau
  • TIBCO Spotfire
  • Qlik
  • MicroStrategy

What are the best business intelligence tools?

Almost all the modern BI tools provide features like visualization, dashboards, easy reporting, analytics, and cloud support. Some of the best business intelligence tools are listed above.

What are business intelligence tools and techniques?

Business intelligence tools refer to the tools that help businesses perform advanced data analytics and get useful insights to make strategic business decisions using various business intelligence techniques. Business intelligence techniques include:

  • Predictive modeling — meaning finding trends and forecasting future business outcomes.
  • Data mining and descriptive analytics — such as classification, clustering, association, pattern analysis.
  • Visualization — including transforming the results into bars, plots, charts, and other visualizations that are easy to understand and interpret.

What are business intelligence examples?

Some common business intelligence examples are:

  • A retail company collecting user data and transactions to understand its customers’ preferences and give customized offers and services.
  • A healthcare system collecting patients’ medical information and suggesting lifestyle changes and treatments based on their current and past data.
  • A bank manager identifying their most profitable customers by looking at all the data in one place through a BI tool.

Learn about more business intelligence examples.

What are the five basic tasks of business intelligence?

The five basic tasks of business intelligence are:

  • Data sourcing and integration: The data from various internal and external sources are integrated and then loaded into a data warehouse, data lake, or similar analytics repository.
  • Data preparation: Data is organized into OLAP cubes or data models for analytics.
  • Queries: BI professionals like business analysts and data analysts query the data to get the desired analytics results.
  • Data visualization: The results of queries are converted into visualizations, BI reports, and dashboards and shared to online portals for collaboration.
  • Decision-making: Business analysts, data scientists, and other stakeholders use the insights, reports, and visualizations to make strategic business decisions that can improve business processes and productivity, and increase business revenue.

What is the business intelligence process?

Business intelligence processes consist of the following steps:

  • Defining business goals
  • Gathering the required data
  • Data preparation and transformation
  • Data processing and analysis
  • Data visualization
  • Feedback and decision-making

What are BI tools and their uses?

BI tools help businesses analyse huge amounts of data automatically to improve their processes and increase revenue. BI tools can be used by technical and non-technical users alike because of their features like dashboards, automated reporting, data visualization, and drag-and-drop functionality. Some important uses of BI tools are:

  • Creating dashboards to view analytics results
  • Generating reports to make strategic decisions with stakeholders
  • Querying data for advanced analytics
  • Applying intelligent AI and ML capabilities to get accurate insights
  • Integrating business intelligence into applications for seamless workflow
  • Using cloud-based analytics for better reach and collaboration

What are traditional BI tools?

Traditional BI tools provide on-premise solutions for business intelligence and analytics. These tools are not fully automated and require IT staff to prepare, transform, and pre-process data. Traditional BI tools provide reporting and visualization features but do not have AI or NLP (natural language processing) capabilities. Traditional BI tools are becoming obsolete now with the emergence of self-service BI tools that overcome the limitations of traditional BI tools.