BUILT FOR THE SPEED OF BUSINESS. Copyright 2013 Pivotal. All rights reserved.
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1 BUILT FOR THE SPEED OF BUSINESS 1
2 2 Pivotal Real Time Intelligence Paul Davey GM & CTO Telecommunications industry
3 Real-Time Intelligence Introduction Sample video Solution architecture Conclusion 3
4 Introduction When time matters Movement + travel People + behaviour Problem resolution 4
5 5
6 Solution Architecture 4G LTE Mobile Exchange Core network 2G / 3G Tower ID Real - Time Intelligence - Ingest Analyse Call Centre Control System Display Report 6
7 Real Time Intelligence Source feeds A Gb IuCS IuPS S1-MME Gn/Gi Binary Connectors Cleanse Filter Anonomise Decorate Location User profile Algorithmic selection Action Present Report User Loc Time Home Device User Loc Time Home Device User Loc Time Home Device 0010 a34 00:23 UK w a34 00:23 UK w a34 00:23 UK w a34 00:23 DE w a34 00:23 DE w a34 00:23 DE w a44 00:23 JP ss a44 00:23 JP ss a44 00:23 JP ss b44 00:23 US b44 00:23 US b44 00:23 US
8 Real-Time Intelligence Telco example Push notice to [new customer ] at [ location ] since [ t-n mins ] Push notice to [ customer ] on [ top list ] in [ location ] when [ call drop ] >[ n / t ] Push notice to call centre when customer on top list and datarate < nbps Count customer with device type who had dropped call and retry in time in location Push notice to netops when network device will impact > #10 customer on top list 8
9 Conclusion Real-time is important for some uses of data Combination of multi-streams requires common time base to be relevant. Fast data requires Scale-Out platform Pivotal combination Pivotal Big Data + Pivotal Real-Time = Maximum value + Pivotal Cloud Foundry = Maximum value + Maximum flexibility. 9
10 A NEW PLATFORM FOR A NEW ERA
11 11 Telco Industry Pivotal solutions examples
12 New service development Challenge: Telecom company sought to become country s trusted partner for Big Data enabling enterprises to drive economic growth. Desired infrastructure for companies to easily explore, collaborate, analyze, upload, and transform internal data and augment with industry data to create new applications Desire for low-touch, self service, scalable platform for clients to deploy applications Pivotal Solution includes: Pivotal Cloud Foundry, PHD, HawQ, Chorus, Alpine, RTI Solution: Provided foundation for massive data storage, where customers can connect and collaborate to build applications Data Science practice helps customers understand value of data Automated Dev Ops: Customers can come in & create apps against the data, start paying for data when apps are deployed 12
13 Agile low cost service development Challenge: Create platform for development to establish new revenue relationships with customers Leverage massive amounts of collected mobile data to differentiate from existing IaaS vendors Pivotal Cloud Foundry, Pivotal Labs Solution: Create a seamless, integrated PaaS to existing cloud infrastructure, with a familiar web console and look and feel to manage all data services Leverage native security, authentication, billing, and other infrastructure Enable new generation of mobile development that embeds mobility into user experience 13
14 Churn reduction new basis for data driven decision making Challenge: Poor call quality caused massive loss of customers. No Insight into root cause of issues. Increased scrutiny from regulators, but infrastructure did not support the requests for information needed Difficulties with Scale: Call Data Record generates 2 Billion new records per day, no info on dropped calls due to capacity Pivotal Solution includes: PHD, HawQ Solution: New Data Warehouse infrastructure contains both dropped and completed calls for analysis, 3 month capacity Hadoop infrastructure with familiar SQL interface stores 5x volume at half cost of Teradata Reports which took 2 Months to obtain now take 1 day 14
15 Telco Establishes Real-Time Intelligence (RTI) Framework Challenge: Current reporting on call faults, network quality, customer experience is plagued by significant lag time Opportunity to improve marketing efforts through real-time analytics, foot fall analytics with improved data Pivotal Solution includes: RTI 4 T, Spring, Rabbit, Gemfire, SQLFire, PHD, Hawq Solution: Improve Revenue: real-time geographic customer lists enable geographically-targeted offers Improved Network Optimization, conduct event-based adjustments to power, bandwidth within minutes instead of waiting for tomorrow Better understand where Capital investments should be placed based on network data 15
16 Predicting Outages in Cellular Network Customer A major telecommunication company Business Problem Predicting service outages using network data captured by the servers Challenges The time series signal from the network traffic data shows a seasonal behavior with multiple seasonality which had to be accounted for in the modeling Solution Analyze the network traffic data using time series analysis and a forecasting algorithm based on an autoregressive model is implemented in UAP to predict the network traffic behavior Fourier series techniques were used to account for multiple seasonality 16
17 Text Analytics for Churn Prediction Customer A major telecom company Business Problem Reducing churn through more accurate models Solution Built sentiment analysis models to predict churn and topic models to understand topics of conversation in call center memos Achieved 16% improve in ROC curve for Churn Prediction Challenges Existing models only used structured features Call center memos had poor structure and had lots of typos 17
18 A NEW PLATFORM FOR A NEW ERA
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