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 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!
Organizations today are striving to become intelligent, just like humans. Continuing the analogy, we can divide an intelligent organization into three groups:
Business intelligence is an umbrella term comprising these three processes along with the right technologies to create intelligent, data-driven organizations.
Common examples of business intelligence:
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.
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.
Top advantages of business intelligence software tools for your organization are:
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 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.
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 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 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.
The best business intelligence reporting tools have a few or more of the following features:
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.
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.
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.
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.
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.
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.
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.
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.
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 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 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:
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:
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.
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.
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.
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
Leverage the Atlas SQL JDBC driver to connect your SQL-based tools that accept an Open Database Connectivity API. Learn more.
Leverage the Atlas SQL ODBC driver to connect your SQL-based tools that accept an Open Database Connectivity API. Learn more.
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.
There are many types of traditional, self-service, reporting, and embedded tools used in business intelligence. Some of the popular BI tools are:
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:
Some common business intelligence examples are:
Learn about more business intelligence examples.
The five basic tasks of business intelligence are:
Business intelligence processes consist of the following steps:
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:
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.