The Decision Maker

Get Your Game On: Criteria for Evaluating Analytics Tools

Posted by Peter Keers, PMP on Jul 11, 2017 12:07:00 PM


Forward-thinking credit unions are tuning their internal data for improved decision making. Previously, data was locked up in multiple, “siloed” transactional systems. Now, innovative credit unions organize their critical information within integrated data warehouses.

 However, once the data is made available, how does a credit union make best use of it? An apt analogy is the XBOX and other gaming platforms. The game console by itself is a marvelous piece of technology. Yet, without the games, it is not very useful. By the same token, video games without a console are useless. Put the two together and wonderful things happen for video game aficionados.

How do wonderful things happen with an integrated data warehouse? What are the “video games” in data warehouse world?

There are an abundance of “games” in the form of business intelligence and analytics tools. These are software systems that turn data into information. Choosing a tool from among this abundance of options is a challenging task for most credit unions. Fortunately, there are resources to assist in choosing the best choice for a given organization.

A leader in the area of technology evaluation is Gartner ( Among Gartner’s most useful publications in this area is its Critical Capabilities for Business Intelligence and Analytics Platforms. Released annually, this report evaluates the leading business intelligence and analytics tools currently available.

Credit unions can purchase this report from Gartner or obtain an abbreviated free version from some of the vendors that are evaluated in the report However, on Gartner’s website is some free information that credit unions can readily use to evaluate the offerings of business intelligence and analytics tool vendors.

Gartner lists in the reports table of contents a list of the “Critical Capabilities” of these tools. While a credit union would get the best possible evaluation of vendor offerings by buying the Gartner report, the list of capabilities by itself can be a great aid in evaluating these tools.

Below are the Critical Capabilities Gartner uses to evaluate business intelligence and analytics tools. While the titles of the capabilities are largely self-explanatory, I’ve added some basic interpretations.

Admin, Security and Architecture – This is the basic housekeeping for the tool. It involves security, adding users, and usage logging.

Data Source Connectivity – Can the tool connect to both structured and unstructured data? What data types are allowed? What is the specific mechanism for connecting?

Cloud BI – What are the cloud versus on-premises capabilities of the tool?

Self-Contained ETL and Data Storage – What ETL (Extract/Transform/Load) functions are native to the tool? How does it handle data indexing and data load management including flexibility in scheduling?

Self-Service Data Preparation – What are the tool’s data cleansing capabilities? Does allow blending of multiple data sources?

Metadata Management – How does the tool support metadata creation and retrieval? How does it handle changes in dimensions, hierarchies and measures?

Embedded Advanced Analytics- What analytics are built into the tool? Can externally developed models be imported?

Smart Data Discovery – Does the tool have the ability to automatically detect correlations, exceptions, clusters, etc.?

Interactive Visual Exploration – Does the tool support drill down and drill through? What visualization options are available? Can the visualization objects be directly manipulated?

Analytic Dashboards – Can interactive dashboards be created? Is the data connection to dashboards intuitive?

Mobile Exploration and Authoring – Can the tool publish and interact via mobile devices?

Embed Analytic Content – Can developers easily create and modify analytic content/visualizations and easily embed them into a business process, and/or an application?

Publish, Share and Collaborate – Does the tool provide a wide array of ways to publish analytic content to various platforms?

Platform and Workflow Integration – Does the tool integrate smoothly with other platforms and tools?

Ease of Use and Visual Appeal – Overall, is the tool easy to use and does it have compelling visual appeal?

While these descriptions merely scratch the surface, they provide a credit union with a wide breadth of attributes against which to begin comprehensive analytical tool evaluation.

Credit Union Data Analytics, Beginning the Journey: Read the Whitepaper

Topics: Data Analytics