What is Business Intelligence Software? Analysis of Features, Benefits, Types & Pricing

What is business intelligence software?

Business intelligence software or BI software is a suite of tools designed to source, sort, consolidate, analyze and present complex data into digestible reports for insights. In this article, we’ll go beyond the question of what is business intelligence software and explain in detail the different aspects of this profit-driver solution.

Companies use business intelligence for strategic goals including the following:

  • Identify SWOT (strengths, weaknesses, opportunities and threats)
  • Measure KPIs
  • Deploy resources cost-effectively
  • See relationships between datasets for more informed-decisions
  • Plot business health across overall goals
  • Generate insights for quick decisions

Another advantage of business intelligence software is that it leverages big data and cloud-computing to simplify complex data analysis and helps companies adopt business intelligence practices across departments. Today’s BI solutions are easy to deploy, use and integrate with existing systems. They can be standalone applications or as part of an enterprise suite like ERP, CRM and ecommerce systems.

Beyond the definition of business intelligence software, we’ll walk you through the key aspects of these tools in our guide. Specifically, you’ll learn the following:

  1. Examples of Business Intelligence software
  2. Benefits of Business Intelligence
  3. Types of Business Intelligence
  4. Features of Business Intelligence
  5. Factors to consider
  6. Pricing of Business Intelligence
  7. Potential issues
  8. Latest trends

The market shift from IT-led to business-led analytics is spurring the growth of BI software. Typical users of BI solutions today are business owners, senior executives, managers and frontline staff like sales, support and purchasing. This cross-departmental shift makes BI software both a strategic and tactical tool.

What are examples of business intelligence software?

BI solutions come in various forms. Some act as standalone applications while others are part of an enterprise suite. Some are targeted at large enterprises, still others are primarily for small businesses. To give you an idea how they are packaged, here are some examples of business intelligence software that are popular on the market:

  1. Sisense – A leading BI software known for robust features and advanced technologies like its InChip engine and single-stack architecture. If you need a reliable Sisense alternative, check out our other comparison articles.
  2. GoodData – Features a growth-centric advanced analytics ideal for finding new revenue streams or understanding customer behavioral trends
  3. Looker – A data discovery app with intuitive data exploration tools that let users build and share reports on the fly. It’s a solid GoodData alternative.
  4. Tableau – A highly visual BI platform with extensive access across devices from PC to iPad, this software leverages its Tableau Service for smooth data flow across platforms
  5. Domo – Features a wide range of self-service BI tools with extensive data connectors and social collaboration features which make it a worthwhile Looker alternative.
  6. Klipfolio – This simple yet very powerful business data platform that allows businesses to turn their company data accessible and visible to their people, with all information updated constantly for real-time accuracy.
  7. Engtics – a behavior tracking, engagement, and analytics suite that helps you view and assess your users and how they relate to the performance of your products, websites, applications, and more.
  8. Artivatic – an end to end plug-in-play business intelligence with neuroscience focused automated decision making advanced AI/ML platform.
  9. GroupThinq – a cloud-based project management and business intelligence software designed primarily for consulting firms and professionals, helping them manage their processes and grow their business.
  10. Qubida – an end-to-end business intelligence and big data integration platform that enables businesses and enterprises to prepare, analyze, and visualize data without having to rely on multiple data platforms and systems.

Sisense is a leading BI software known for its InChip engine and single-stack architecture

Why use business intelligence software?

Now that you know the answer to what is business intelligence software it’s also important to understand why you should use one.

IDC predicted that big data and business analytics will grow to $187 billion global market in 2019, an impressive 50% jump from 2015. Clearly, more companies today understand the myriad benefits of BI solutions across the organization and overall business competitiveness. Here are the main benefits of a business intelligence software:

  1. Gain insight for growth. This is the main definition of BI. You can optimize business intelligence for sales opportunities, lead generation, market analysis, customer segmentation, etc. Combining relational database and multidimensional data models with real-time data and cross-departmental collaboration, you can manipulate huge volumes of data and surface insights in almost unlimited ways.Among others, you can identify growth areas, assess supply and demand, measure product viability and determine your market position. Moreover, data is sourced in real-time and analyzed through collaboration, further enhancing your market knowledge. For instance, customer-facing staff like support and sales can share feedback updates with top-level management, giving the latter an accurate picture of current market behavior.
  2. Address urgent issues. Crises can be immediately addressed if you have the right information. BI solutions feature ad hoc reporting that let you input data and generate insights in minutes, if not seconds. You can take a more informed action before a crisis further escalates.Through a wizard interface, these solutions let you locate and extract critical data off volumes of datasets and generate reports on the fly. This alone saves you time from mindlessly browsing through databases. Does a social media rant affecting your whole market or is it limited to a segment? Which branch has inventory surplus you can reallocate to a needy branch in the next hour? How much a sudden current event set to impact on your project? These questions need answers now and a BI solution makes that happen.
  3. Ground data is immediate. Instead of waiting for weeks or months to collate and process raw market data from frontline departments like sales, marketing and support, you can now access real-time ground movement. BI solutions are equipped with powerful multidimensional analytics that can be simultaneously used by teams. Data is dynamic and moves with market events as they happen.Moreover, because many BI solutions today are intuitive for non-tech users, data analysis is widely adopted across the organization. Ground data sourced by your frontline employees can be immediately cleansed, sorted and added to the central repository, empowering the company with the latest information. Likewise, most BI solutions feature collaboration tools that allow sharing of insights and best practices.
  4. Get the big picture. Dashboards and scorecards are typical features in BI solutions. They give senior executives a bird’s eye view of the company’s overall performance. Metrics can be customized to align with your key performance indicators and reports generated in real time.With dashboards you can plot the business health across a threshold range. Automatic alerts can be triggered if you reach a minimum or maximum tolerance within the range. Meanwhile, scorecards can be set to deliver periodic snapshots of your company’s progress vis-a-vis its goals. Metrics and milestones are customized to align with your objectives and overall strategy.
  5. “See” the future. The more advanced BI solutions feature predictive analytics and forecasting that enable you to anticipate future outcomes. These tools leverage historical, recurring and current patterns to churn out calculated forecasts. The ability to anticipate events lends to your company agility and flexibility, critical factors in highly disruptive industries like tech, retail and entertainment.

So, the next time someone asks you,“Why use a business intelligence software?” lay down these clear benefits, instead of simply discussing the features of business intelligence software.

Looker is a data discovery app that let users build and share reports on the fly

What are the types of business intelligence software?

You have learnt what is business intelligence software, but how does it work? The answer, it depends on its type. One of the best ways to define the types is by the purpose of business intelligence software. Generally, BI solutions fall under three main functions, which are, again, either packaged as a standalone application or part of a suite.

Data management

A BI can primarily function to clean your existing data. Raw data is messy and disparate. It needs to be prepared for processing such as for analytics or reporting. A data management BI software uses a standardized approach for indexing and archiving. This tool ensures you get clean, accurate raw data to process and that you are conducting an apple-to-apple comparison.

Likewise, this BI software type follows ETL processes (extract, transform and load) to gather data from various sources and load them into a target platform, such as, spreadsheets, data containers and data warehouses. Most top BI software solutions include data management as a major feature.

Example: Sisense, GoodData

Data Discovery

When users say BI software today, they’re likely referring to its data discovery function. This is where real intelligence is unearthed, when data silos are mined and consolidated for patterns and insights.

Most BI solutions are data mining tools capable of integrating with different business systems and datasets. These include spreadsheets, mailing lists, reports, website content, etc. BI software funnels their data into a centralized platform, where processing takes place and the output literally, the “business intelligence” asset.

Most data discovery BI solutions feature an online analytical processing, which is often considered as its own classification. But OLAP is really just the “processing” part of the broader data discovery spectrum. It needs other data discovery tools, such as, relational database, predictive analytics, semantic analytics and report writing to churn out intelligent assets. Together, these tools parse data, carve huge datasets into digestible bits and present them in meaningful reports.

Example: Looker, Tableau, Domo

Reporting platform

Some BI solutions focus on how data is presented intuitively that they become popular among non-technical users like senior executives and managers. These solutions offer visualizations that simplify complex data, dashboards that highlight KPIs, report writers for customize outputs and scorecards that display overall business health with a measurable numerical value.

Example: Sisense

GoodData features a growth-centric advanced analytics ideal for finding new revenue streams

What does business intelligence software do?

We’ve described what is business intelligence software earlier in the article, let’s now review its main features. Business intelligence solutions come with myriad features, but in general they let you accomplish all or some of these processes:

  • Compare, match different outcomes via A/B or multivariate testing
  • Forecast outcomes through predictive modeling
  • Surface insights off patterns or relationships
  • Present cause-effect scenarios

When comparing, try matching the main features of a business intelligence software, which should include all or at least some the following:

  1. Online analytical processing (OLAP) or business analytics. OLAP runs the gamut of data preparation, processing and delivering outcomes for reporting. At the core of BI solutions are OLAP tools that enable you to analyze multidimensional data in real-time or simultaneously with other analytics processing.
    For example, a user aggregates the company’s sales data by location, while another one uses the same data source and mashes it with  real-time online purchases. The same dataset is used interactively by two users with different purposes.
    A great BI software should allow you to perform the three OLAP operations: consolidate or roll up disparate sources; drill down to details; and slice and dice. Generally, the more ways you can isolate data from a dataset (called OLAP cube) and view it, the more flexible you can interpret data. When reviewing BI solutions, you’ll come across terms like data mashups, data unification and complex business queries, which are OLAP functionalities.
  2. Reporting and querying. Reporting and querying is another key feature of BI software–how complex data is sorted and generated. Integration is key here to tap into external sources. Likewise, mobile access for query and reports lets you leverage the flexibility afforded by  cloud computing and real-time data.
    Generally, business intelligence reporting falls into two types: customized and ad hoc. Customized reports let you sort data subsets, arrange the order of data points, and use specific metrics that matter to you. On the other hand, ad hoc reports are quick data outputs generated by the solution during an urgent situation to help you, among others, make on-the-spot decisions.
    In both instances, reports can be presented as quick lookups or in drill-down details and can be shared across the organization.
    Meanwhile, advanced BI solutions today feature intuitive querying that enables users to surface complex data even without SQL writing or coding skills. OLAP automatically prepares the datasets for every new query. This ability, in fact, allows companies to adopt BI tools organizational wide, beyond the traditional realm of the IT department.
  3. Digital or visual dashboards. Data visualization is the end-stage of reporting and, in fact, one of the most identifiable elements of BI solutions. Executives and non-technical users often regard BI through this lens, enabling them to generate charts, graphs and dashboard widgets. Advanced visualizations include geospatial reports, heat maps and funnels.
    In many ways, visual dashboards are the sum of the BI solution’s capabilities. Behind the chart or graph are the OLAP, reporting-querying, integration, customization and other features at work.
    Although BI solutions have varied visual dashboards by color, location, clusters and any other metrics, they usually feature sharing and commenting capabilities.
  4. Integration. Integration is also a key factor in answering–what does a business intelligence software do? BI solutions rely on different data sources to churn out meaningful and deep insights, so integration is key. In fact, many vendors tie up BI tools with other business applications, such as, CRM, salesforce automation and shopping cart software.
    Integration can be native (with vendor’s own apps), pre-built (arrangement with third-party apps) or via API (with your own apps). Many top BI software solutions integrate with key business applications like CRM, sales, accounting, content management, and project management.
    But not all have API integration that allows you to develop apps for the software. If you’re a developer, there are BI solutions with open API, along with Ruby, Java and JavaScript support.

What should you consider when buying business intelligence software?

Tabeau is a highly visual BI platform with extensive access across devices from PC to iPad

Most BI software solutions are web-enabled and leverage SaaS capabilities, so let’s skip the standard cloud benefits, such as:

  • Real-time data
  • Collaboration tools
  • Role-based access
  • Mobile access
  • Scalability  

Likewise, we have a section on the cost of a business intelligence software, so we won’t touch pricing here. Instead, we focus on four essential aspects that differentiate a good business intelligence software from a great one.

  1. Accuracy of reporting tools. Reporting is standard in BI solutions but they’re not created equal. While data accuracy largely depends on the integrity of raw data, how data is processed matters, too. Although most BI solutions allow for simultaneous and multidimensional analytics, the devil is in the details.
    Check the software’s OLAP capabilities, specifically how many ways it can source, sort, aggregate and present data. The more extensive the OLAP tools the more specific, comprehensive and, ultimately, accurate the data. You’ll need to closely scrutinize the software and find out its slice-and-dice capabilities.
    Make data accuracy your topmost comparison metric. All your forecasts and reports–and your company’s health–will depend on this factor.
  2. Clarity of outputs. Another key factor that should influence your purchase decision is how the solution churns out clear, concise, easily digestible reports. Visualization is the game-changer here considering that busy top-level executives or non-tech users are the software’s main users.
    A solution that can simplify complex details with the least clicks or technical requirements is likely the better BI software. Quick look-ups with drill-down options, dashboard widgets, templates, rules and customizable metrics are some of the key features that impact clarity of insights.
  3. Ease of use. We pick out ease-of-use from standard cloud benefits because of the high learning curve associated with BI software solutions. They have plenty of moving parts that can be demanding for the casual user.
    It’s not to say the more simple the solution the better. Rather, consider intuitiveness as the main factor. Some of the features that can improve user experience include: drag-and-drop mechanism; collaboration features; reliable tech support and self-learning database; toggle view; filter data; and self-service visualization.
  4. Data Environment. The top business intelligence solutions offer a wide range of integration the further to extend their data environment. Not only do they support various data sources, but they also allow multi-platform access to users.
    Even as the BI solution integrates with other business systems like CRM, ERP, salesforce automation, content management, help desk, office apps and ad networks, it should also be accessible through various OS, devices and deployment models, such as: Android, iOS, Windows, Linux, Mac, on-premise and cloud-hosted.
    Furthermore, if you have a resident I.T. team, consider getting a BI solution with an open API. Your tech team will have greater flexibility to develop apps that further enhance the BI software. On this note, check also if the software supports Ruby, Java and JavaScript.

How much does business intelligence software cost?

Domo features a wide range of self-service BI tools including social collaboration features

BI solutions are priced just like any other SaaS or on-premise software. Cloud BI solutions are packaged in monthly or annual price points based on features scope, integration and customization. Where fixed plans are unavailable, pricing is by quote for a more customized bundle. Licenses may apply for on-premise deployment or private cloud-hosted.

Here are the pricing of some of the more popular business intelligence solutions:

  • SisenseGoodDataLooker. Most comprehensive BI solutions are available by quote only
  • Tableau. Has small business and enterprise plans, starting at $35 per user/month. Its Professional edition costs $70 per user/month featuring advanced analytics.
  • Domo. Offers a free app plus a fixed plan at $175 per month. Domo also has a by-quote enterprise edition.

What are the potential issues with business intelligence software?

Despite its clear benefits BI solutions are not without issues. Here are the common problems associated with BI software:

  1. Inaccurate data leads to wrong forecasting . Too much dependence on BI software can lead to clunky data gathering. Sales may feed the system with guesswork just to comply with management’s requirement. As a result, BI software churns out misleading or inaccurate reports. 
  2. Unused or under-utilized complex and expensive BI tools. Some BI solutions have comprehensive set features in an attempt to cover the whole range of business analytics. But not all companies need to cover the whole nine yards, leading to some of these sophisticated tools unused or underutilized. Partly, the BI solution becomes a liability as its cost isn’t optimized.
  3. Steep learning curve. Because it involves complex analytics and uses data sources managed by different teams, BI software has a higher-than-average learning curve among SaaS solutions. It has a lot of moving hardware and software parts like multiple-stack architecture and predictive analytics. Likewise, it leverages frontier technologies like multidimensional analytics, big data and OLAP. These technologies are fast evolving that both vendors and users have to play catch-up.
  4. Difficulty in rollout among large enterprise. In a survey of 2,500 users by, one in ten enterprise Bl system rollouts take a year or more to implement. However, small businesses only take one to three months, according to the survey.

Some of the reasons cited for the slow pace among large enterprises are incompatibility with legacy systems, varied user requirements and corporate politics. The study suggested that  incremental rollouts marked by success stages can make BI software adoption faster and smoother.

  1. Deconstruction of dashboards. Dashboards are becoming a collection of building blocks more than a whole structure by itself. BI solutions notwithstanding, they are turning to widgets, indicators, filters, etc. to present quick look-ups rather than a complete picture at once. Time is essential and users across the organization are gaining precise control over analyzing data that matters just to them and when they matter.
  2. Deep learning. More investments are pouring into deep learning after the initial traction on artificial intelligence. As deep learning technologies march on, we will see more of their application on BI software, primarily on image recognition and machine translation.
  3. IoT. It’s a staple of consumer technology fantasy, but internet-of-things is legitimately happening. We can see advances in algorithms, sensors and integration that drum up predictive analytics. The same technology will further enhance OLAP capabilities in BI solutions.
Chris Miller

By Chris Miller

Chris Miller is a senior customer service analyst at FinancesOnline. For more than 5 years now, he has witnessed and written about the tremendous impact of digital technologies that have deeply disrupted the customer service industry. The onset of chatbots and other AI/ML tech, omnichannel platforms, highly personalized service, the emerging blockchain methodologies specially created a deep impact, all of which are reflected in his writing. His reviews of customer service applications serve as invaluable resources for businesses of any size and scale.

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