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A BI tool is an application created to allow users to view data without the use of programming. These apps can display and share data as charts, dashboards, and tables.
BI tools & technologies plug into existing data sources at your company, such BI Platforms as your CRM, data warehouse, or event analytics service.
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If yes, we are happy to introduce common BI tools that are helpful in understanding business trends and generating insights from your data.
Spreadsheet applications: A spreadsheet program like Microsoft Excel or Google Sheets is a classic illustration of a BI tool. With these programs, you may visualize data in tables, pivot tables, or charts and share the outcomes as separate files (or links to those files in the cloud).
BI platforms: A BI tool is frequently considered an app that is used for data visualization and creating reports. In addition, BI tools like Metabase can handle responsibilities like data modeling, data cataloging, version control, and permissions management.
In this ebook we cover a series of questions that you should ask when choosing the right BI tool.
Get BI Buyer's GuideThe user-facing end of a data stack can be configured using various analytics tools, including BI tools. BI platforms can easily manage almost the same responsibilities as your other stack parts. Here’s how these pieces interact:
BI tools aren't data sources; they don't take the role of production databases or data warehouses for data storage that belongs to your company. By executing queries and showing the results, BI tools retrieve data from databases.
Programming languages like Python and R are used by open source applications like Jupyter Notebook and RShiny to manipulate data. Additionally, they are used to create reports and dashboards for analytics, but because they rely on code rather than a visual interface, they aren't considered BI tools.
When it is about regularly importing or transforming large amounts of data, BI tools cannot take the role of ETLs (or ELTs). Some BI tools, like ETLs, can manage data modeling and data stitching (connecting data from many databases) by performing queries immediately.
Data on product usage is collected by event or web analytics platforms like Google Analytics, Segment, or Amplitude. These services aren't regarded as BI tools, even though they have their interface for visualizing and sharing that data. They can be regarded as mini data stacks and can be utilized independently.
READ MORE: How AI Powered Chatbots Simplify BI And Analytics Adoption For Decision Makers