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Compare Business Intelligence (BI) Software Tools

This page is managed by
Michael Koploy, Managing Editor
Last updated: April 17, 2014

Top 10 Most Recommended Business Intelligence Systems

 
BOARD Management Intelligence Toolkit We recommend BOARD to organizations looking for a centralized tool to house its data, conduct multidimensional analyses (including OLAP) and drill-down to find which areas of the company are performing above and below standard.
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SiSense SiSense is a BI tool that was developed for all types of user--even those with little or no prior experience with BI software. SiSense's tools manage and support business data with powerful visuals and tools.
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23

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in the last 30 days
TIBCO Spotfire TIBCO Spotfire enables organizations to synthesize data into a format that is immediately actionable. With intuitive self-discovery tools, anyone (not just IT) can dive in and immediately make use of your data.
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15

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Tableau Tableau is a solution engineered to meet the needs of anyone looking to analyze key business data. Adaptable to almost all industries and easy to learn, Tableau will help you make the most of your business’s data.
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14

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Microsoft SharePoint Microsoft SharePoint is a popular option for businesses looking to better manage and analyze its data. A good fit for organizations that currently use Microsoft Dynamics products and store information using Microsoft SQL Server.
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13

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Necto Panorama Necto is a comprehensive BI application that offers the industry's first socially-enabled BI suite, empowering organizations to gain actionable insights from user behavior.
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12

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Birst Birst combines the flexibility of a SaaS system with the precision of an enterprise-capable Business Intelligence system. The result is a solution for business analytics that's extremely user-friendly and analytically accurate.
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12

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GoodData GoodData is a powerful, cloud-based business intelligence suite. Their analytics package delivers complete visibility over sales, marketing, and customer service. They also offer robust analytics packages right out of the box.
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10

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Clear Analytics Clear Analytics by Ana Data Consulting Inc is an Excel-based system that combines the familiar structure of Excel spreadsheets with powerful Business Intelligence analytics, providing detailed, easy-to-interpret reports.
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6

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TARGIT Decision Suite We recommend the TARGIT Decision Suite to buyers looking for a tool to quickly create customizable dashboards. With the new iTop feature, TARGIT BI can be used on iPhones and iPads to analyze pertinent company information.
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3

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Feedback from buyers we've advised
 
"Extremely helpful staff helped me focus my efforts on the best systems to look at given my needs." Kristin Hall Sliwicki
Prairie Lakes Counseling Associates
"SoftwareAdvice was instrumental in narrowing down the huge number of products available to be relevant and customized to our specific requirements." Louise R. Serkey
Canyon View at Ventana
"Software Advice really helped me organize and narrow my search to only a few software companies that all seemed to fit pretty well with our needs. Without them, I'm not sure how I would have found the software we selected. I highly recommend you contact them to see what they can help you find." Cameron Monteath
Medical Modeling Inc.

Buyer's Guide

Business intelligence (BI) software has gained considerable traction since its introduction as “decision support systems” in the 1960s. Today, there are over 100 BI software companies selling some type of business intelligence tool. We put together this buyer’s guide to help buyers understand the market. In this guide, we’ll review:

What is Business Intelligence Software?

BI software helps organizations organize and analyze data to make better decisions. This could include internal data from company departments as well as data from external sources, such as marketing data services, social media channels or even macroeconomic information.

The BI market is growing rapidly because of the proliferation of data to analyze. Over the past few decades, companies that have deployed Enterprise Resource Planning (ERP), Customer Relationship Management (CRM) and other applications are now sitting on a mountain of data that can be analyzed. In addition, the growth of the Web has increased the demand for tools that can analyze large data sets.

One of the biggest trends in the BI market is the shift in software architecture and design to more user-friendly applications. These applications are now being used by business users--not just IT staff--to analyze particular sets of departmental data, including marketing, procurement, retail and Web data.

Matching the Right BI Tool to Your Needs

BI software can be divided into three broad application categories: data management tools, data discovery applications and reporting tools (including dashboards and visualization software). In the next section, we’ll explain how these applications can help your organization’s decision-making process become more data driven.

What BI tools you need depends on how your data is currently managed and how you would like to analyze it. For example, if your data is currently scattered across disparate transactional databases, you might need to build a data warehouse to centralize it and invest in data management tools that offer Extract, Transform, and Load (ETL) functionality to move and re-structure the data.

Once data is given a common structure and format, you can invest in data discovery applications that offer Online Analytical Processing (OLAP), data mining and the capability to create custom ad hoc reports. And because information is stored within the data warehouse, users can quickly pull reports without impacting the performance of the organization’s software applications, such as CRM, ERP and supply chain management solutions.

We’ve illustrated this concept in the image below

Business Intelligence (BI) Software Architecture


But this isn’t the only way to implement BI within your organization. If you’re only analyzing data from a single source, ETL and data warehouses are unnecessary. Alternatively, you might require multiple data warehouses, and thus require different tools to connect data between both these servers and other BI applications that need access to this data.

 

Data Management Tools

Better decision-making starts with better data. Data management tools help clean-up “dirty data”, organize information by providing format and structure, and prepare databases for analyses.

Functionality Description
Data Quality Helps organizations maintain clean, standardized and error-free data. Standardization is especially important for BI implementations that integrate data from diverse sources. Data quality management ensures that later analyses are correct and can lead to improvements within the business.
Extract, Transform, and Load (ETL) Collects data from outside sources, transforms it and then loads the compiled data into the target system (a database or data warehouse). Because primary data is often organized using different schemas or formats, analysts can use ETL tools to normalize data for useful analysis.

Data Discovery Applications

The ability to sift through data and come to meaningful conclusions is one of the most powerful benefits of adopting business intelligence tools. Data discovery applications help users make sense of their data, whether it be through quick, multivariate analysis during OLAP or via advanced algorithms and statistical computations during data mining.

Functionality Description
Data Mining Sorts through large amounts of data to identify new or unknown patterns. It is often the first step that other processes rely on, such as predictive analytics. Databases are often too large or convoluted to find patterns with the naked eye or through simple queries. Data mining helps point users in the right direction for further analysis by providing an automated method of discovering previously-neglected trends.
Online Analytical Processing (OLAP) Enables users to quickly analyze multidimensional data from different perspectives. It is typically made up of three analytical operations: data consolidation, data sorting and classification (drill-down), and analysis of data from a particular perspective (slice-and-dice). For example, a user could analyze sales numbers for various products by store and by month. OLAP allows users to produce this analysis.
Predictive Analytics Analyzes current and historical data to make predictions about future risks and opportunities. An example of this is credit scoring, which relies on an individual’s current financial standing to make predictions about their future credit behavior.
Semantic and Text Analytics Extracts and interprets large volumes of text to identify patterns, relationships and sentiment. For example, the popularity of social media has made text analytics valuable to companies with a large social footprint. Understanding semantic trends is a powerful tool for organizations evaluating purchase intent or customer satisfaction among users of these channels.

Reporting Tools

In the words of John W. Tuckey, “The greatest value of a picture is when it forces us to notice what we never expected to see.” Reporting applications are an important way to present data and easily convey the results of analysis.

BI users are increasingly business users--not IT staff--who need quick, easy-to-understand displays of information. In response, software vendors have been working to mask the complexity of these applications and increasingly focus on the user experience.

Functionality Description
Visualizations Helps users create advanced graphical representations of data via simple user interfaces. The ability to visualize information in a graphical format (as opposed to words or numbers) can help users understand data in a more insightful way. In addition, new interactive tools can provide teams the ability to both analyze and manipulate reports in real time.
Dashboards Dashboards typically highlight key performance indicators (KPIs), which help managers focus on the metrics that are most important to them. Dashboards are often browser-based, making them easily accessible by anyone with permissions.
Report Writers Allows users to design and generate custom reports. Many CRM and ERP systems include built-in report writing tools, but users can also purchase stand-alone applications, such as Crystal Reports, to create ad hoc reports based on complex queries. This is especially helpful for organizations that continually modify analyses and need to generate new reports, quickly.
Scorecarding Scorecards attach a numerical weight to performance and map progress toward goals. Think of it as dashboards taken one step further. In organizations with a strategic performance management methodology (e.g., balanced scorecard, Six Sigma, etc.), scorecards are an effective way to keep tabs on key metrics. For example, a scorecard might establish a grade of “A+" to 40% year-over-year growth if the goal was set at 14%.

What Type of Buyer Are You?

Before evaluating software, you must determine what type of buyer you are.

Business users and departmental buyers. This group of buyers favors small data discovery vendors and BI tools over the big traditional BI systems. Ease-of-use and fast deployment are more important than in-depth functionality and integration. They are usually business users rather than IT staff.

IT buyers. Traditional buyers are more focused on functionality and integration within their information infrastructure stacks or other enterprise resource planning (ERP) applications. Integration across different entities and departments is usually more important than ease of use.

Market Trends

As you begin your software comparison and evaluation, there are a couple trends to consider:

In-Memory Processing. OLAP systems of the past would pre-calculate every possible combination of data. These calculations would be stored in the “cube” and users could retrieve them when they needed a certain analysis. Creating these cubes was very time consuming - sometimes taking as long as a year - and required expertise. Today, computer processors and memory are faster, cheaper and overall more powerful. This same process can happen in-memory, rather than using a disk-based approach with cubes. Analytic software built on an in-memory architecture can retrieve data and perform calculations in real-time or on-the-fly.

Big Data. The Internet is rapidly creating vast amounts of data. According to the International Data Corporation (IDC), data use in 2011 will grow by as much as 44 times amounting to 35.2 zettabytes (a billion terabytes) across the world. This phenomenon is being dubbed “Big Data” among IT and business leaders. Business analytics software companies are beefing up their data warehousing and analytics capabilities to keep up with demand.

Business users to outnumber IT staff. This is a major trend playing out in the market. More business users - rather than traditional IT staff - are evaluating and purchasing software. So usability is becoming more important than functionality during software evaluations. As a result, small data discovery vendors that develop really good interactive visualization tools are gaining market share. Meanwhile, traditional BI vendors are parroting new market entrants by promoting ease of use.

Software as a Service (SaaS). A growing number of organizations are considering SaaS or “cloud” BI software instead of traditional, on-premise software that you install on location. Cost is a major driver of this trend. The poor performing economy is motivating companies to look at lower-cost BI software from SaaS and open source vendors. Of course, perceived ease of use, faster implementations and reduced IT needs are also driving this trend. On-premise BI vendors are responding by committing development resources to cloud technology.

Mobile BI applications
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Proliferation of the iPhone, iPad and other mobile devices is pushing vendors (e.g. Microsoft and Oracle) to develop on-the-go business intelligence applications. Analysts think mobile BI could expand the population of BI users to a larger mainstream audience.