Big Data: Ten Criteria for Evaluating Analytics Reporting Tools (Part 1)

Last week I talked about how to get involved in the latest conversations about Big Data analytics.  When working with the Big Data analytics, the end business users reporting tools are critical.  Your older tools may not be up to today’s Big Data analytics capabilities, such as delivering answers to the “bring your own device” reporting world.  By setting up an effective business user reporting experience, everyone can easily ask his or her own questions and get answers, improving productivity, time to market, and profitability, while reducing operating costs.

The following are five of the ten criteria for your Big Data analytics reporting tool. Weightings for each criteria category should be discussed, along with adding your company’s sub-topic considerations, to calculate the total best score.  By using these criteria and attributes as a starting point your company can quickly understand the different areas that make your business users effective for getting their Big Data analytic reporting answers.


  • Data Set Size Restrictions. This is the most important question within current Big Data environments. What are the tool’s size limitations (amount of data) of the source data or Big Data analytic answer result set(s) that can be retrieved and processed at one time?  What are the average sizes of the analytic result sets that are expected to be displayed at once by the reporting tool for your company?
  • Handles multiple Big Data sources at once.  There are always multiple sources of Big Data information.  Can your reporting tool handle multiple sources of information and can it bring those disparate sets of data together for evaluation, comparison, and charts into a single display or report?  Handling multiple diverse data sources and data types within a single view are critically important for end users to use the data in the way they know best.
  • Transparent native multiple platforms access and support.  Setup, administration and getting to Big Data analytic answers should be a straight forward business user experience: download, connect, and develop answers for their questions.  Working with the infrastructure and setup of the Big Data analytic reporting, the business users should have a straight forward and easily documented experience.  Connections to your various Big Data platforms, databases, and meta data sources should be simple to set up for the end user to configure within a secure context.
  • Security is standard. Does the Big Data analytics reporting tool support single sign on to these different platforms?  Are there levels of security for report distribution or drill down level security? Do the reports or answers stay secure even in your shared environment?  Are there personally identifiable information (PII) protections/controls, encryption capabilities for data over the wire, encryption for reports, encryptions for column data, and data masking for other critical private data?  If there are any security issues your company’s Big Data analytics reporting adoption rate could be non-existent or suffer, and can lead to a project delay or failure.
  • Accessibility to new and old platforms.  Does your Big Data reporting tool support your Big Data platforms and your legacy platforms?  Hadoop, Mongo, and other new NoSQL platforms have their connection considerations, but can your Big Data analytics tool leverage those platforms’ native data access interface, SQL or other special requirements?  Can it reference all the mainframe, UNIX, Linux and Windows data type your report needs within a single report?  Is the reporting tool cluster, aggregate or materialized query table aware?  Can the reporting tool leverage native aggregates or other specialized data stores?

Next week I’ll share the other five criteria for your Big Data analytics reporting tool.

Dave Beulke is a system strategist, application architect, and performance expert specializing in Big Data, data warehouses, and high performance internet business solutions.  He is an IBM Gold Consultant, Information Champion, President of DAMA-NCR, former President of International DB2 User Group, and frequent speaker at national and international conferences. His architectures, designs, and performance tuning techniques help organization better leverage their information assets, saving millions in processing costs.

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