A buyer's guide to choosing the right BI analytics tool
A collection of articles that takes you from defining technology needs to purchasing options
There are a plethora of business intelligence (BI) tools on the market that address the increasing analytics needs of businesses of all sizes and industries. However, determining which BI analytics tool or tools to buy isn't always easy.
In this article, we examine BI analytics tools from 12 leading vendors: Birst, IBM, Information Builders, Logi Analytics, Microsoft, MicroStrategy, Oracle, SAP, SAS, Qlik Technologies Inc., Let's examine which product or products can best meet your organization's needs.
Evaluating BI analytics tools
By identifying with the following use cases, you can determine which of the BI analytics tools examined here will best meet your needs.
Operational snapshots. In this use case, pre-defined production reports are built to support business processes and operational reporting. Information Builders, SAP, Oracle, IBM, MicroStrategy and TIBCO offer BI products that match these requirements.
Oracle and SAP are the leaders in ERP applications and have leveraged their BI products to offer prebuilt operational reporting. Oracle Business Intelligence Foundation Suite, SAP BusinessObjects and IBM Cognos are typically used by large enterprises because of resource and product cost considerations. For small and medium-sized businesses (SMBs) or more cost-conscious enterprises, Information Builder's WebFOCUS, MicroStrategy and TIBCO JasperSoft are viable alternatives. These BI tools support large-scale operational reporting across numerous enterprise applications and are resource- and cost-effective for enterprises of all sizes.
While IBM, Oracle and SAP acquired other BI tool vendors to become part of their product portfolios, other enterprise application vendors have built their operational reporting by leveraging BI tools that are targeted for embedding. QlikView and Logi Info are BI tools that have been embedded in operational reporting or used to build BI packaged applications.
Limited exploration. Here, data and metrics are known and used on a recurring basis. IT will integrate data as needed, create analytical data models and perform data management. Business users want to filter the data, drill down into details, and use both graphics and tabular reports with related subjects typically grouped together in dashboards.
Guided data discovery tools such as QlikView, Tableau, TIBCO Spotfire, Birst and Logi Info are the best fit for this use case. These tools enable IT to source, integrate and manage security and privacy as needed to enable users to concentrate on analysis rather than data management. But they provide reports, graphics and dashboards oriented toward business users rather than IT. Although data discovery tools are often brought into enterprises to perform exploratory self-service BI, as we've discussed, a use case where IT manages the data and business people create their own BI applications using this data enables a positive business return on investment (ROI).
For larger enterprises, with existing investments in legacy BI platforms, IBM Cognos, SAP BusinessObjects, Oracle Business Intelligence Foundation Suite, MicroStrategy, Information Builder's WebFOCUS and SAS Visual Analytics could be leveraged instead of acquiring new BI analytics tools. (A discussion on multiple BI use cases for large enterprises is covered later in this article.)
Packaged applications. SAP, Oracle, IBM, Information Builders and SAS offer BI analytics tools that best match these requirements. These BI packages may be corporate performance management or domain-specific applications that require significant BI analysis.
Oracle and SAP have leveraged their BI products, which also operate standalone, to offer operational reporting and analytics to their ERP customers. Enterprises that have invested in these applications often select those vendors' BI packages because they're tightly integrated, ensure quick time to market and have a positive ROI.
If an enterprise is using other application vendors or wishes to obtain BI packages from independent vendors, then IBM, Information Builders, SAS and Oracle provide excellent operational or domain-specific BI packaged applications.
Spreadsheet integration. Although many BI analytics tools integrate with spreadsheets, Microsoft has finally leveraged its Excel franchise and expanded its BI capabilities into Excel itself. Microsoft Power Pivot's in-memory columnar capabilities replace its proprietary Excel data store. Power Query, Power View and Power Map provide BI reporting, dashboards and visualization capabilities without requiring the user to ever leave native Excel while PowerBI works with Office 365.
BI product suites from IBM, SAP, Oracle, Information Builders and MicroStrategy can use spreadsheets as sources and enable spreadsheets to pull data from the BI tool. Data discovery tools such as Tableau, QlikTech and TIBCO Spotfire generally interact with spreadsheets in a one-way fashion of importing or querying spreadsheet data.
Querying and analysis. There are two analytical situations encountered. In the first scenario, business people don't know what data is needed prior to analysis. This is a true self-service BI use case with the business user performing ad-hoc analysis. This requires the user to know what data is available, how to access it, its quality and its completeness. This means the tools used must perform analysis and also data preparation or data blending. Qlik Sense, Tableau, TIBCO Spotfire and Logi Vision work well for this use case, provided that limited data preparation is necessary. Otherwise, third-party data preparation tools will be needed to extend capabilities. A tech-savvy business user would also be able to use guided discovery tools such as QlikView, Logi Info and Birst in this scenario.
In the second scenario, performance measures aren't defined, but data is known prior to analysis. The best practice is for IT to create a predefined data model to enable business users to concentrate on business analysis. The BI styles that best support this use case are online analytical processing (OLAP) or prebuilt in-memory columnar data models. Microsoft BI (Power Pivot), SAS, IBM, Oracle, MicroStrategy and Tableau are good choices, as they support accessing OLAP cubes and enable pivot-style analysis. These tools incorporate all the must-haves and many of the nice-to-have features noted in our third article, including context-based filters and visualizations, collaboration and publishing analysis for other business people and Office integration.
Supplemental data source analysis. Here, IT should pre-build data models with whatever data and performance measures are known and used on a recurring basis. Business users may need to supplement both data and measures as they perform each new business analysis. The amount of data preparation that will be required by business users will determine whether the BI tool selected should be a guided data analysis or a self-service data discovery tool.
If the business user needs to select only IT-managed data sources with little or no data preparation, then guided data analysis tools such as QlikView, Logi Info, Microsoft Power BI and Birst are the best fit. If more extensive data blending is necessary, then self-service data discovery tools such as Tableau, Qlik Sense, Logi Vision and Microsoft PowerPivot best fit this scenario.
The BI analytics tools mentioned all have the must-have features needed for their use cases while also providing nice-to-have features such as collaboration, advanced visualizations and in-memory analytics.
Visual-oriented analytics. For this use case, the best-fit tools are TIBCO Spotfire, SAS Visual Analytics, Tableau and Qlik (Qlik Sense and QlikView), along with MicroStrategy and Microsoft (PowerPivot and Power BI). Tableau, in particular, is dedicated to implementing data visualization best practices and assisting its customers to select the visualization that matches the type of analysis and data they're performing. For the most demanding advanced visualization uses -- when data scientists are using these capabilities coupled with statistical modeling -- TIBCO Spotfire and SAS Visual Analytics would be the top candidates. All of these products support either guided analysis and/or data discovery use cases, so selecting these tools will enable an enterprise to support multiple use cases.
For large enterprises with more than one BI use case. BI tool suites from SAP, IBM, Oracle, MicroStrategy and Information Builders support enterprise-grade development and management functionality and include a set of discrete BI tools that focus on specific use cases and BI tools styles. These suites provide dashboards, production reporting, ad-hoc query, scheduling, alerting and sometimes OLAP analysis. The suites offer varying degrees of support for cloud BI, mobile BI, data discovery, data visualization and self-service BI. They're catching up to the market leaders in these areas by expanding existing BI tools or integrating BI tools acquired from other vendors in their suites.
There are compelling advantages to IT-centric deployments such as the ability for an enterprise to implement data management, enforce privacy and security, meet scalability needs, and foster improved productivity by enabling business people to concentrate on analysis rather than gathering and cleaning data. These BI tool suites have a long history in the BI market and a large customer base.
Because of their extensive functionality, BI suites from IBM, SAP and Oracle, for example, tend to be complex and require extensive product-specific knowledge. In fact, it's common for IT to have people dedicated to discrete tools in a BI suite; for example, they may have different people specializing in production reporting, dashboards and OLAP. The high IT resource costs coupled with tool costs means that these products tools are best suited for large enterprises, with SMBs seeking other alternatives as examined below.
For SMBs with more than one BI use case. The traditional BI product suites such as IBM, SAP and Oracle typically aren't the best fit for SMBs. These smaller organizations generally don't have dedicated IT resources to develop, manage and support these tools, nor do they have a large number of business users to justify the investment.
For SMBs with a variety of use cases, the pragmatic options are to either select different BI tools for each BI use case or select one or two tools that will be sufficient. Although the impression is that a single BI product suite is easier and more cost-effective than using multiple BI tools, often that isn't the case. That's especially true when the BI suite is really a group of different BI tools bundled together but not truly seamlessly integrated.
For example, to address the aforementioned tool selection options, you could either:
- Select a data discovery BI tool such as Tableau, QlikView or TIBCO Spotfire and deploy it in two ways. First, deploy it as a self-service BI tool for business users whose analytical needs match that use case. Second, create prebuilt dashboards with reports and visualizations, and deploy these BI applications for business users who have use cases where guided discovery or reporting tools fit.
- Select a BI tool for a specific BI use case and supplement it with Microsoft BI and Excel for other user cases that need guided discovery or reporting tools, as mentioned above.
Additional evaluation criteria
Once you've determined your BI use cases and selected a BI product or set of products that are a good fit for those use cases, there are a few additional items to consider before you make the final product selection:
Product ease of use. This is very subjective, as every vendor claims that its product is the easiest to use. The key to this helping you differentiate products is if the BI consumers in your use cases are also the evaluators. For example, it isn't relevant to your selection if your BI developer finds a product easy to use but the business people who will be using a self-service BI tool don't.
Method of distribution (on premises versus software as a service). This criteria matters only if the selected products match your BI use cases. Some BI evaluations have gone astray by using this as the primary (or sole) criteria, and then finding out that the cloud BI product doesn't work for their BI use cases. This criteria is all about cost, not really about the BI users. Purchasing or subscribing to the wrong product doesn't save money. If the pool of BI products that match your BI use cases offers different methods of distribution, then this criteria is an excellent differentiator that may indeed result in lower total cost of ownership and provide the BI capabilities that your enterprise needs.
Too often, the BI tool an enterprise chooses is the one that gets the highest marks based on a long checklist of functions and features -- many which will never be used -- or is chosen with little regard to the users. Stop the madness. The best BI tool is one that's used by business people and is useful in supporting their jobs when they need reporting and analysis.
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