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John Myers

Hey all-

Welcome to my blog. The fine folks at the BeyeNETWORK™ have provided me with this forum to offer opinion and insight into the worlds of telcommunications (telecom) and business activity monitoring (BAM). But as with any blog, I am sure that we (yes we... since blogging is a "team sport"...) will explore other tangents that intersect the concepts of telecom and BAM.

In this world of "Crossfire" intellectual engagement (i.e. I yell louder therefore I win the argument), I will try to offer my opinion in a constructive manner. If I truly dislike a concept, I will do my best to offer an alternative as opposed to simply attempting to prove my point by disproving someone else's. I ask that people who post to this blog follow in my lead.

Let the games begin....

About the author >

John Myers, a senior analyst in the business intelligence (BI) practice at  Enterprise Management Associates (EMA). In this role, John delivers comprehensive coverage of the business intelligence and data warehouse industry with a focus on database management, data integration, data visualization, and process management solutions. Prior to joining EMA, John spent over ten years working with business analytics implementations associated with the telecommunications industry.

John may be contacted by email at JMyers@enterprisemanagement.com.

Editor's note: More telecom articles, resources, news and events are available in the BeyeNETWORK's Telecom Channel. Be sure to visit today!

October 2010 Archives

When dealing with the large amounts of data associated with the “big data” class of business intelligence efforts, there is a quandary:

  • Do you show “all” the data?
  • Do you show an aggregated subset of the data?

When you attempt to show all the data in a “big data” environment, you run the risk of data overload as well as “processing” overload.  When you aggregate, you run the risk of skipping over the detail that many analysts may require.

Step 1: Architecture

TableauLogoIn this quandary, business intelligence professionals need to look at the architecture of their “big data” environment and make the proper decisions on the performance of their data environments.  Tableau Software, for example, offers many options associated with their “big data” visualizations. From options for existing/traditional data warehouse environments to new analytical environments based on Hadoop or MapReduce technologies, data visualization products like Tableau give BI/DW architects the opportunity to make those decisions rather than being stuck on one side of the “big data” quandary.

Telecom Take

Telecom environments are a long way from being configured with a single data source for operational BI or analytics.  Mergers and acquisitions (M&A) as well as growing nature of telecom products and customers will ensure that a single data source is more of a “journey” than a destination.  Yet, there is the need to create operational BI and analytical data visualization layers similar to the example below:


Being able to mix and match as necessary will be a key architectural attribute for data visualization teams.  This will be a strong requirement in putting information in the hands of frontline customer service reps as well as strategic account management teams to manage customer expectations.

Does your telecom organization’s BI/DW architecture allow for these types of mix and match connections for data visualization?

Post your comments below or email (John.Myers@BlueBuffaloGroup.com) / twitter (@BlueBuffaloGrp) me directly.

Posted October 6, 2010 2:00 PM
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