Inspire 2014 – Verizon Wireless: Creating the Optimal Wireless Service Experience with Handset Analytics

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The competition for wireless subscribers is fierce, and a user’s experience with their mobile device plays a significant role in whether they stay with their existing carrier or churn to the competition. In this session you will hear how Verizon Wireless uses Alteryx to monitor handset performance to identify potential problems and take corrective action to maintain the highest quality of service. You will also hear how Alteryx is being used in other parts of their network to predict capacity requirements and network utilization.

Aaron Agostini, Systems Engineer, Verizon Wireless

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Inspire 2014 – Verizon Wireless: Creating the Optimal Wireless Service Experience with Handset Analytics

  1. 1. #inspire14 Creating the Optimal Wireless Service Experience w/ Handset Analytics Aaron Agostini Systems Engineering Verizon Wireless
  2. 2. #inspire14#inspire14 Network Engineer for Verizon Wireless Please allow me to introduce myself… • RF System Performance Group (former position) • Currently in Data Engineering • In my RF role, I was responsible for finding areas of opportunity for improving our network’s performance • This is what spurred on my investigation into Alteryx • As I’ve moved into my new role, I’ve continued using the tool for reporting on the internet based backhaul of our network
  3. 3. #inspire14#inspire14 3 different technologies with different characteristics Challenge: Maximizing time on LTE while minimizing time on previous technologies • CDMA’s soft hand-off scheme allowed for a larger area of overlap between cell sites • LTE’s approach leads to interference when sectors and cells overlap • Can create situations where there are substantially different RF environments between technologies • Handsets can vary in performance in these environments
  4. 4. #inspire14#inspire14 Data collected varied by technology Challenge: Linking sets of data • Each technology had its own independent database • Each data set had it’s own measurement pegs and KPI’s • Data visualization was exclusive to each technology • Prior to Alteryx, creating cross-technology KPI’s was a challenge • Records for individual devices were difficult to cross correlate with time stamps due to the sheer volume of records • LTE has a significantly higher number of records, but did not at the time provide location information
  5. 5. #inspire14#inspire14 Voice over LTE has differences from standard LTE traffic Further Challenge: VoLTE • Significant differences in signaling (SIP vs 5E/SS7) • Traffic is still handled the same at the enodeB level • Parameters such as hand-off will make no distinction between LTE and VoLTE traffic
  6. 6. #inspire14#inspire14 Previously, I used multiple software packages with mixed results Struggles Prior to Alteryx • Data parsing and charting was handled primarily in Excel • This led to somewhat clunky macros that could take hours to days to get working properly • The software struggled with larger datasets (files could be several gigabytes and larger) • When I was finished in Excel, I would need to import the result into MapInfo • From here, I would again need to work out the result, which could involve some clunky macros, SQL queries, etc.
  7. 7. #inspire14#inspire14 Alteryx easily joined the sets of data, leading to a new KPI Solution: Handset-based Performance Analysis • Cross technology movement can now be analyzed as a new KPI • High runner individual users can be found • Best and worst performing devices can be determined • Heat maps can be generate for technology drop down hotspots • Records pertaining to technology changes for individual devices can be generated
  8. 8. #inspire14#inspire14 Alteryx allowed to do my job more quickly, and to do more Results from using Alteryx • Map creation that in the past had taken 2 hours or more could be completed in as long as it took to run a module • Adjustments were far easier to make, again reducing work time from hours to minutes • Automating tasks was much easier, as Alteryx is much more intuitive than other packages were; 2 hours in Alteryx could equal days of work in Excel and MapInfo • Alteryx made complicated joins very easy; this allowed me to do analysis I wasn’t able to do previously
  9. 9. #inspire14 THANK YOU!

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