Data Day - Escuchando la red
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This document discusses how telecommunications companies can use big data to improve their business. It notes that currently telecom networks generate a lot of data but it is stored in silos and only a small percentage is analyzed. The document advocates building a user-centric data architecture to better understand subscribers and their usage patterns. This involves ingesting different data sources into a flexible system like Pivotal HD and then analyzing the data. The goals are to provide customized tracking and predictive insights to enterprise, individual and internal customers in order to improve customer experience, marketing and network performance.
Data Day - Escuchando la red
- 2. Escuchando la red: Cómo el Big Data está ayudando a las empresas de Telecomunicaciones Xavier Prud’Homme Luis de la Torre Álvarez
- 3. 3© 2015 Pivotal Software, Inc. All rights reserved. Software is Eating the World
- 4. 4© 2015 Pivotal Software, Inc. All rights reserved. People Are Living Through Applications Businesses Can Dominate Markets with Applications • - Do Banking • - Buy a House - Share Kids Pics • - Read Editorials - - Order Dinner - - Meet Your Wife - - Diagnose Illnesses - - Talk to Mom
- 5. 5© 2015 Pivotal Software, Inc. All rights reserved. How Pivotal Accelerates Value Creation 70% of data generated by customers 80% of data being stored 3% being prepared for analysis 0.5% being analyzed <0.5% being operationalized First Movers Smart Enterprises ~20X $2.9B ~30X $41B ~7X $290B ~20X $120B Average Enterprises SOLVE THE BIG DATA UTILITY GAP
- 6. 6© 2015 Pivotal Software, Inc. All rights reserved. pivotal.io © 2015 Pivotal Software, Inc. All rights reservedDevelopment & Enablement with Pivotal Labs Your industry is already being disrupted Why Become Agile?
- 7. 7© 2015 Pivotal Software, Inc. All rights reserved. TRANSFORMATION Modern Product Development Help customers learn by doing it for and with them Big Data Modern, open, highly parallelized platform Cloud Native Platform Modern, open, highly automated cloud platform Pivotal’s answer to the new disrupting business models
- 8. 8© 2015 Pivotal Software, Inc. All rights reserved. BIG DATA IMPACT IN THE TELECOMMUNICATION INDUSTRY
- 9. 9© 2015 Pivotal Software, Inc. All rights reserved. Current status of the Telecom Industry VS HIGHER capabilities LOWER cost Respond FASTER to consumer trends in usage Many initiatives focus on delivery content faster, cheaper and better to any device. HETNET roll-out with focused approach to content delivery.
- 10. 10© 2015 Pivotal Software, Inc. All rights reserved. Enforcement and Reporting Points SGSN GGSN DPI Client Content Delivery Network (CDN)Enforcement and Reporting Points Subscriber Profile Repository (SPR) PCRF Captive Portal OSS Provisioning System SGW TDF PGW Client VO OCS IMS P-CSCF 3rd party AM/SDP ePDG Gy SOAP Rx Gx Gxx Sh Sd WLAN Node B eNode B MGCF I/S-CSCFAS SBC HSS MRFC Gx RNC Sy Gy MRF MGW Client Many steps, lots of complexity NO BUILT-IN VISIBILITY Service Delivery Access and Core Networks Charging Control
- 11. 11© 2015 Pivotal Software, Inc. All rights reserved. Where is the subscriber in all of this? Location Terminal or Device info Voice and Data Plan Usage Charging and Billing DATA SILOS – REPOSITORIES (Support Systems) Enjoying sightseeing Just got this new phone Wow! This new app is amazing! WHAT?! How did I spend all this money?!
- 12. 12© 2015 Pivotal Software, Inc. All rights reserved. Co-existence of network-centric and user-centric Data Architectures. USER CENTRIC NETWORK CENTRIC Track performance Monitor reliability and service-wide quality Preserve a cost- effective operation Focus on end-user experience Track changes in usage behavior Designed for dialogue
- 13. 13© 2015 Pivotal Software, Inc. All rights reserved. Building a user-centric Data Architecture (Planning ahead of needs) Virtualization Layer Flexible Data Ingestion Data replication Layer Optimization of Query Plans for Structured or Unstructured Data Complete toolset for Data Analysis (MADLib, SQL-on-Hadoop) Visualization Layer
- 14. 14© 2015 Pivotal Software, Inc. All rights reserved. Feeding a user-centric Data Architecture (Think BIG, Start SMALL) Flexible Data Ingestion Signaling Monitoring External WebServices Deep Packet Inspection Charging Control Operational Records Billing Records
- 15. 15© 2015 Pivotal Software, Inc. All rights reserved. Storing and using our data feed (Creating a cost-effective toolset) Flexible Data Ingestion Pivotal HD Data Node 1 HDFS Pivotal HD Data Node # Pivotal HD Data Node 3 Pivotal HD Data Node 4 Pivotal HD – NameNode Pivotal HD – Standby NameNode Pivotal HD Data Node N Query plan optimization Dynamic pipelining Multi-Parallel processing Data Management with Partitioned tables Polymorphic storage Block replication Pivotal HDB (SQL-on-Hadoop)
- 16. 16© 2015 Pivotal Software, Inc. All rights reserved. Results (Your goal) Visualization Layer Enterprise Customer Customized tracking on usage on corporate devices. Predictive actions for recurrent congestion or service failure. Pro-active communications for service offerings. To create a Cost-effective relationship management To build a Beyond-standard communication framework.
- 17. 17© 2015 Pivotal Software, Inc. All rights reserved. Results (Your goal) Visualization Layer Individual Customer Individual usage tracking on all devices Predictive insights into top data-mongering applications and security-risk alerts. Pro-active suggestions for service offerings based on voice/data plan quota exhaustion, etc. To surpass your customer´s expectation for account management. To build a brand-new dialogue framework.
- 18. 18© 2015 Pivotal Software, Inc. All rights reserved. Results (Your goal) Visualization Layer Internal Customer Tracking of sales campaigns on specific regions Predictive insights into top data-mongering applications. Pro-active alerts for device behavior and access network performance. To react quickly. To generate relevant insights for Marketing, Sales and Product Development teams.
- 19. 19© 2015 Pivotal Software, Inc. All rights reserved. Q&A