Popular BI tools
Posted: Wed Jan 29, 2025 10:14 am
Business intelligence (BI) provides organizations with powerful tools to collect, analyze, and visualize data to help make informed decisions. Popular BI tools are functional, easy to use, and customizable to specific business needs, making them indispensable in modern management.
Commercial BI systems
BI tools Tableau and Microsoft Power BI professors edu email addresses are among the leading solutions for business analysis, providing extensive capabilities for working with data. However, since 2023, the sale of their licenses in Russia has been suspended.
Qlik Sense is a BI solution with a unique associative search feature that simplifies working with data. Users can easily find and connect information from different sources without spending time on preliminary table setup. This significantly speeds up analysis and makes it easier to identify relationships between data. The platform also supports work on mobile devices.
1C:BI is a BI platform that has a key advantage in the form of integration with other 1C solutions. Users can work with data obtained from various 1C systems, such as 1C:Trade Management, 1C:ERP, 1C:Production Management, and use them for analysis and reporting.
Free BI systems are divided into two types - cloud and open source:
Cloud BI systems
Google Data Studio lets you create customizable, interactive reports and dashboards by integrating data from sources like Google Analytics, Google Sheets, and Google Ads. The tool comes with pre-built templates and visuals for reporting, as well as a feature for collaborating with colleagues.
DataLense is a BI analytics tool available in Russia for working with large volumes of data. DataLense automatically updates information, providing real-time tracking of changes. The platform offers a variety of functionality, including creating custom charts using JavaScript, setting up specific metrics, and generating reports tailored to unique tasks.
Open Source BI Systems
They often look simple and do not have a large set of functions. However, by adding a little code, you can implement the necessary features and adapt the program to business tasks:
Apache Superset is a Python-based business intelligence framework that provides connectivity to a variety of data sources, including SQL databases, Hadoop, Spark, Cassandra, and Druid. The platform comes with tools for creating interactive dashboards, graphs, tables, and reports. Users can also customize data visualizations using CSS and integrate their own graphs using JavaScript for advanced customization.
Metabase . An easy-to-use BI system for creating reports and visualizing data on dashboards. Despite the limited number of functions, the system offers a user-friendly interface that makes it easy to create reports and dashboards.
Pentaho . A platform equipped with built-in tools for ETL (extract, transform, load) and data analysis. It allows you to connect various sources of information for their processing and analysis.
OpenAnalytics . A platform for processing and analyzing large volumes of data, supporting query language, machine learning, and statistical analysis. Users can apply machine learning algorithms such as classification, regression, and clustering. OpenAnalytics can be integrated with other systems and its functionality can be expanded by connecting additional applications.
Another way to present data is to use Python libraries such as Matplotlib. Although these libraries do not allow you to create dashboards, they do provide the ability to plot graphs.
Commercial BI systems
BI tools Tableau and Microsoft Power BI professors edu email addresses are among the leading solutions for business analysis, providing extensive capabilities for working with data. However, since 2023, the sale of their licenses in Russia has been suspended.
Qlik Sense is a BI solution with a unique associative search feature that simplifies working with data. Users can easily find and connect information from different sources without spending time on preliminary table setup. This significantly speeds up analysis and makes it easier to identify relationships between data. The platform also supports work on mobile devices.
1C:BI is a BI platform that has a key advantage in the form of integration with other 1C solutions. Users can work with data obtained from various 1C systems, such as 1C:Trade Management, 1C:ERP, 1C:Production Management, and use them for analysis and reporting.
Free BI systems are divided into two types - cloud and open source:
Cloud BI systems
Google Data Studio lets you create customizable, interactive reports and dashboards by integrating data from sources like Google Analytics, Google Sheets, and Google Ads. The tool comes with pre-built templates and visuals for reporting, as well as a feature for collaborating with colleagues.
DataLense is a BI analytics tool available in Russia for working with large volumes of data. DataLense automatically updates information, providing real-time tracking of changes. The platform offers a variety of functionality, including creating custom charts using JavaScript, setting up specific metrics, and generating reports tailored to unique tasks.
Open Source BI Systems
They often look simple and do not have a large set of functions. However, by adding a little code, you can implement the necessary features and adapt the program to business tasks:
Apache Superset is a Python-based business intelligence framework that provides connectivity to a variety of data sources, including SQL databases, Hadoop, Spark, Cassandra, and Druid. The platform comes with tools for creating interactive dashboards, graphs, tables, and reports. Users can also customize data visualizations using CSS and integrate their own graphs using JavaScript for advanced customization.
Metabase . An easy-to-use BI system for creating reports and visualizing data on dashboards. Despite the limited number of functions, the system offers a user-friendly interface that makes it easy to create reports and dashboards.
Pentaho . A platform equipped with built-in tools for ETL (extract, transform, load) and data analysis. It allows you to connect various sources of information for their processing and analysis.
OpenAnalytics . A platform for processing and analyzing large volumes of data, supporting query language, machine learning, and statistical analysis. Users can apply machine learning algorithms such as classification, regression, and clustering. OpenAnalytics can be integrated with other systems and its functionality can be expanded by connecting additional applications.
Another way to present data is to use Python libraries such as Matplotlib. Although these libraries do not allow you to create dashboards, they do provide the ability to plot graphs.