Top Rated – We have investigated the top business intelligence tools based on their primary features and user popularity.
Examine the data analysis tools that can boost your company’s outcomes, and then compare top rated BI solutions in the table below.
Check out our Product Selection tool up top for advice on which business intelligence solution will work best for your company.
The term “business intelligence” (BI) refers to a suite of analytics tools used by businesses to extract meaningful information from large amounts of raw data and present it in digestible visual formats like charts, graphs, and dashboards.
Data visualization tools, data warehouses, interactive dashboards, and BI reporting tools are all examples of top-tier BI software.
Instead of analyzing data from external sources like competition intelligence does, a BI solution uses the data the company already has to get insight into the interplay between departments.
15 Top Rated Business Intelligence Tools for Companies of All Sizes
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 are generating, tracking and compiling business data on a scale never seen before.
And the ability to directly integrate cloud software 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 results.
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To make informed choices, companies must base their decisions on evidence.
The mountains of data that companies and their customers produce contain evidence of purchasing patterns and market trends.
By aggregating, standardizing, and analyzing this data, companies can better understand their customers, better predict revenue growth, and better protect themselves from business pitfalls.
Business intelligence has traditionally taken the form of quarterly or annual reports that report on a defined set of key performance indicators (KPIs), but today’s BI reporting software is supported by data analytics tools that work continuously and at lightning speed.
These insights can help a company choose a course of action in a matter of minutes.
BI software interprets a sea of quantified customer and business actions and returns questions based on patterns in the data.
BI comes in many forms and spans many different types of technology.
This comparison of business intelligence tools from software vendors breaks down the three major stages that data must pass through to deliver top rated business intelligence, and provides considerations for purchasing top rated BI tools for businesses of various sizes.
Top rated Business intelligence tools and platforms come in different forms for different business needs.
Companies looking to provide data services to business users will find that self-service top rated BI software will meet the needs of most of their users.
Data visualization tools are useful for teams that are dipping their toes into data analysis but may not have many additional development resources available. Data warehousing tools provide the underlying infrastructure that can house and clean data before serving it up through visualizations. And top rated BI tools offer end-to-end dashboard tools to store, clean, visualize and publish data.
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Perhaps one of the most exciting aspects of top rated BI, advanced analytics functions such as predictive and prescriptive analytics function as a subset of data mining.
The tools use existing datasets and algorithmic models to help companies make better business decisions.
As the name suggests, predictive analytics predict future events based on current and historical data.
By drawing connections between data sets, these software applications predict the likelihood of future events, which can lead to a huge competitive advantage for companies.
Predictive analytics involves detailed modeling, and even ventures into the realms of artificial intelligence (AI) and machine learning (ML), where software actually learns from past events to predict future consequences.
The three main forms of predictive analytics are predictive modeling, descriptive modeling, and decision analytics.
The most well-known segment of predictive analytics, this type of software does what its name says: it predicts, especially in reference to a single element.
Predictive models use algorithms to search for correlations between a particular unit of measurement and at least one or more functions relating to that unit. The goal is to find the same correlation across different data sets.