Find out more about Business Intelligence Software
What is Business Intelligence Software?
Business Intelligence Software (or BI software) is a class of computer applications that process and analyze corporate data to produce quality insights, and help understand the health of your business. BI software uses a variety of formulas and metrics to measure, compare, and relate business indicators, and makes it possible to distinguish the strengths and weaknesses of every company. The main functions of these systems are data discovery, data management, and reporting, but some of them also evaluate functionality and employees’ performance. If you are looking for the perfect BI system for your company, we recommend you to consider our leader Sisense, and other programs discussed in this category.
Most Popular Business Intelligence Software
Best Business Intelligence Software
How To Choose The Best Business Intelligence Software
The goal of business intelligence programs is to allow for the easy and deeper interpretation of large volumes of business data. Finding out opportunities to grow and adopting effective strategies based on these deep, analytical insights can provide businesses a huge competitive market edge over competitors, aside from long-term stability.
In addition, business intelligence software programs can provide businesses historical, current, and predictive online views of various operations of their business.
Thus, it is no wonder that a lot of businesses—whether they are a small start-up, a medium-size company, or an enterprise firm—use these tools to support a wide range of business decisions, whether they are operational or strategic in nature. It’s always a good idea to get more information on each product first. You may want to read more about the current leader in the business intelligence software category in our Sisense reviews or simply compare the most popular solutions in our database. To help you we have prepared detailed reviews of the top 10 business intelligence software.
Whatever your objective for using such a software solution, it is most efficient when it combines business data obtained from the market (known as external data) with the data considered internal to the operations, including financial (known as internal data). With its capacity to combine two extremely different data sets, the best Business Intelligence software can give you a more comprehensive overview of the business.
Get to know each product with free trial
It’s usually a good idea to try out some free trial plans provided by the most popular services to test the features of their software. You won’t be risking wasting your money and the test should offer you a solid look into the capabilities of each software. The best approach is to try our solutions that currently have the highest results in our SmartScore and Customer Satisfaction Rating in the business intelligence tools category and choose the best Business Intelligence software for your company: Sisense, Looker, Domo, Birst, Tableau or QlikView.
Departmental buyers and business users: These buyers opt for small data-discovery apps and BI tools over big BI systems. They look for ease-of-use and fast deployment, and do not worry much about robust functionality and integration. These are normally business users and not IT staff.
IT buyers: These are traditional buyers who look for in-depth functionality and integration with the other business apps they use. For these buyers, integration across different units and entities is more vital than ease of use.
Business Intelligence Tools For Enterprises
Business Intelligence Apps and systems are designed to analyze and transform big data into operable business intelligence, which is especially beneficial for large businesses with complex structure and organization. They need robust and well-integrated solutions that will reveal the whole picture of how their business is doing, in particular such that detect important trends and opportunities, and reveal risk on an early stage to help them avoid severe financial damage. Plus, large enterprises benefit from the quote-based pricing which is very typical for these products, as they obtain an individually tailored package that is priced and equipped according to their needs.
What are Examples of Business Intelligence Software?
- Sisense: one of the best business intelligence solutions that allows users to join, analyze, and picture out information they need to make smart business decisions and draft effective strategies and plans.
- GoodData: a solution that goes beyond business intelligence to offer high value insights to users. It provides advanced analytics to help companies create new revenue streams.
- Looker: a data-discovery solution that offers an intuitive approach to data exploration. It provides a web-based interface that users can utilize to make use of the knowledge of their data analytics team.
- Domo: an excellent self-service business intelligence (BI) app that provides a wide data set and connector support, and also offers a unique range of social collaboration features as well.
- Tableau: a business intelligence software that helps businesses see and understand data and allows businesses to quickly connect, visualize, as well as share data with an efficient seamless experience.
- QlikView: a business intelligence data discovery product that is used to create guided analytics applications as well as dashboards designed for business challenges.
- Birst: a cloud-hosted business intelligence solution that handles requirements of both production oriented BI and end-user data visualization and querying
- KISSmetrics: a robust platform that allows users to determine, monitor, and improve the metrics and other elements that are important for the success of their business.
For a wider choice, read our in-depth reviews and select from the top 15 business intelligence solutions.
Types of Business Intelligence Software
Business intelligence programs can be deployed in different ways. These include:
On-premise deployment: In-house product installation using equipment owned or leased by the company. The advantage is you are assured of data security.
Cloud implementation: Public cloud, private cloud, or a hybrid cloud. The benefits are you don’t have to download any software, or worry about upgrades and maintenance.
Data Management Tools
Include the following features:
- Data quality management – Helps companies maintain clean, error-free, and standardized data. Standardization is essential for BI implementations that include data from multiple sources.
- Extract, transform and load (ETL) – Gathers data from outside sources, changes it, and then loads it into the target system (a warehouse or database).
Data Discovery Applications
- Data mining – Sifts through vast amounts of data to identify new patterns.
- Online analytical processing (OLAP) – Enables users to speedily evaluate multidimensional data from various perspectives.
- Predictive analytics – Evaluates current and historical data to make forecasts about future opportunities and risks.
- Semantic and text analytics – Extracts and interprets huge volumes of text to spot patterns, sentiment, and relationships.
- Visualizations – Helps users create sophisticated graphical representations of data using simple user interfaces.
- Dashboards – Dashboards highlight key performance indicators (KPIs) that help managers focus on important metrics.
- Report writers – Allows users to design and create custom reports.
- Scorecarding – Scorecards give a numerical weight to performance and help to map progress towards objectives.
Key Features of Business Intelligence Software
The most typical features of a business intelligence program include:
- Experimenting to look at previous decisions (A/B testing or multivariate testing)
- Forecasting future business results (predictive modeling or predictive analytics)
- Extrapolating business data to see new patterns and relationships (data mining)
- Explaining the causes why a result or outcome has happened (statistical analysis or quantitative analysis)
Business Intelligence solutions are generally defined with extensive functionality and capabilities. If you are considering purchasing a business intelligence software program for your company, consider the following features before buying one:
Data management: A major consideration when selecting business intelligence programs is to check how capable a tool is in giving complex business data relevant meaning and context for your business to understand the entire situation. It means the tool you should choose should be able to make the raw and unstructured business data “analytic-ready” with its data manipulation, extraction, query, as well as business logic features.
Reporting: When choosing business intelligence, check out their reporting features as claimed by the solution’s vendor or provider. Can the tool really create and distribute business data in visually informative charts, tables, and in a specified or desired page layout. Can the tool also provide you with not just fundamental reporting but even advanced and more meaningful reporting and presentation features?
Check how the tool visualizes the business data. Features such as associative relationship displays, three dimensional images, and pivot-like, easy-to-configure interfaces should be some of the top considerations in your mind. Do these features show up on a mobile platform, particularly when you are showing these data outside your work?
Architecture: Does the business intelligence tool support scalable methods for diverse and complex data sets? For instance, if your business has a huge number of data sets that are at the same time complicated, you might consider buying a program that can effectively handle them and scales to large numbers of data sets.
Check if the tool is designed using a single code base or if it offers solutions compiled from various products that are developed independently. Check if the tool has a quick development cycle, provides your business tightly integrated solutions, and offers amazing user experience.
Can the tool be embedded with the information technology systems you are already using? Does it provide you with solid data security? Can the tool restrict business data view and functionality to a select number of users or user groups?
Does the tool provide you with consistent data backups? If it isn’t, then your business data might get leaked or lost when serious technical glitches happen.
Benefits of Business Intelligence Software
Any company that wants to buy a business intelligence software program needs to consider the functionalities that can help it to become more competitive in the market and really succeed in the industry.
Four major benefits and requirements should be in your mind when reviewing a program’s core features.
Ability to integrate information from different business systems: Strategic business insight generally needs data across various systems. For example, operational results of your company will need a financial perspective. Therefore, your business intelligence software solution should have the capacity to quickly and dynamically integrate information from different sources so you will get answers to a number of business questions.
Outstanding reporting and analysis: When looking at programs, always remember that the solution should offer you more knowledge about complex trends and views in your company. Do not stick with a business intelligence software application that can merely report the business data it mined. You should look for a tool that offers you an explorable capacity, letting you to understand different actions or strategies you can take to predict different scenarios and look for the best ways to achieve success.
Historical analysis and reporting: Ideally, the business intelligence program you should invest in is one that will be able to give you a deeper insight into the company’s overall performance over time and the causes for that positive (or negative) performance. Successful decision-making, in general, needs to have a thorough and critical understanding of the growth of your company over the years and the reasons behind it. In short, your program should have the capacity to map and analyze historical data that may be complex over time, even years. This means you should also get a tool that has the capacity to extract, manipulate, and understand possibly a lot of information. In a lot of companies, millions of database entries are a normal thing.
Future projection and forecasting: The tool’s capacity to analyze and report historical data enables you to project business findings into the future. It will enable you to look at present opportunities and forecast the next possible steps for your company. The ability to forecast and project scenarios in the future should always be among your top factors when it comes to success.
Huge industry – As a market industry, the business intelligence sector is a huge one. Based from a report by Gartner in 2013 (“Market Share Analysis: Business Intelligence and Analytics Software”), companies worldwide spent about $14.4 billion that year, an increase of eight percent from the total $13.3 billion spent by firms the previous year.
Big Data – The Internet is fast creating huge amounts of data. This phenomenon is called “Big Data” and business analytics software vendors are enhancing their analytics and data warehousing capabilities to meet the demand. Fortune 500 companies are expected to invest a lot in BI tools to harness the large amounts of data. They will also consider buying dedicated IT security apps to take care of their computer security requirements.
Mobile BI apps – The widespread use of mobile devices like smartphones and tablets is pushing vendors including Oracle and Microsoft to develop mobile business intelligence apps that can be used on the go. Mobile BI is expected to expand the number of BI users to mainstream sections.
Steep learning curve – Business intelligence apps can be difficult to learn for lay users. Select an app that has a simple interface design and is easy to learn and use effectively. Invest heavily in training your employees to use the app to ensure you get the expected returns from shelling out for the BI app.
Needless features – Do not get taken in by the gimmicky features offered by some vendors. You may end up not needing them at all. Plus, if the software is hard to use, your employees may not take to it resulting in low adoption rates. The solution is priority-based configuration to pick and choose the functions you need, while omitting the features you don’t need.
History of Business Intelligence Software
List of Business Intelligence Software Companies
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Our site uses our proprietary SmartScore™ method to examine all the solutions in the Business Intelligence Software category to help you select the best possible software. It includes the following aspects: cruscial components, collaboration tools, customization, integrations with other services, how easy a software is to use and learn, help & support, security, mobility, scores in other media. Currently, Sisense is the leader in this category and we gave it the highest score in our tests. Following detailed research and analysis it had the best results among its competitors and our reviewers strongly suggest that you include it as one of the options for your company.
A summary of the entire user satisfaction with the service in the Business Intelligence Software category based on our unique algorythm that gathers customer reviews, comments and opinions across a broad range of social media sites in order to help you make an informed investment choice.
Each vendor in the Business Intelligence Software category will offer a different set of pricing packages for its product and each package will include a unique set of features. Below we list the general pricing for the most affordable plan offered for each product. Keep in mind that advanced features may cost extra.
An overview of what type of devices and operating systems are supported by these B2B solutions in the Business Intelligence Software category, including mobile platforms and web-based solutions.
Check what languages and countries are supported by the top B2B solutions in the Business Intelligence Software category, including solutions intended for international markets and created for multi-cultural groups of employees.
Learn what pricing packages are supported by the vendors in the Business Intelligence Software category to check which one matches your business preferences and expenses best. Be aware that certain solutions can support free or freemium accounts for you to try out first.
An analysis of what types of companies a given B2B solution in the Business Intelligence Software category provides for, from small businesses and non-profits to large enterprises.
History of Business Intelligence Software
The attitudinal shift towards operable data is something that nowadays applies even to the smallest companies pursuing a corporate ladder data approach even fiercer than most large enterprises do. Unlike today, working with data was neither easy nor accessible in the past, but that didn’t stop the trend from being the only way out from gambling decisions and guesswork. If you’re a company still blowing hot and cold on your chance to digitalize analytics, the smartest course of action is to explore BI development from point zero, and understand how it developed from desirable to irreplaceable… The term ‘business intelligence’ was first introduced in early 1865, when Richard Miller Devens used it to name the process of gathering banking information in his ‘Cycloapaedia of Commercial and Business Anecdotes’. General enough to cover all analytical operations, but just as specific as it takes not to be confused with similar software, business intelligence remained the name of all apps used to gain insight on business. The basics of how business intelligence systems are supposed to look like were laid much later, listed by Hans Peter Luhn in the IBM Journal of 1958. Technology began to take over, and business intelligence was often associated with it. Still, it is only after 1970 that we can talk about big players and streamlined analytics on the digital BI market – IBM and Siebel revolutionized the BI concept, while modern successful companies such as Sisense hold responsibility for its growing popularity. In the period between 1970 and 2000, data analysis became multidimensional, with storage and reporting enabled, while in the years after that focus shifted to self-service efficiencies, improved visualization, and cloud-hosted systems where data can be accessed from any device. Currently, we are lucky enough to have programs which handle large volumes of big data, and cover predictive needs and personalized business health checks, and ones which even seem to gain momentum and revitalize traditional analytic initiatives.
The term ‘business intelligence’ was first introduced in early 1865, when Richard Miller Devens used it to name the process of gathering banking information in his ‘Cycloapaedia of Commercial and Business Anecdotes’. General enough to cover all analytical operations, but just as specific as it takes not to be confused with similar software, business intelligence remained the name of all apps used to gain insight on business. The basics of how business intelligence systems are supposed to look like were laid much later, listed by Hans Peter Luhn in the IBM Journal of 1958. Technology began to take over, and business intelligence was often associated with it.
Still, it is only after 1970 that we can talk about big players and streamlined analytics on the digital BI market – IBM and Siebel revolutionized the BI concept, while modern successful companies such as Sisense hold responsibility for its growing popularity. In the period between 1970 and 2000, data analysis became multidimensional, with storage and reporting enabled, while in the years after that focus shifted to self-service efficiencies, improved visualization, and cloud-hosted systems where data can be accessed from any device.
Currently, we are lucky enough to have programs which handle large volumes of big data, and cover predictive needs and personalized business health checks, and ones which even seem to gain momentum and revitalize traditional analytic initiatives.