Innovative mobile operators need to mine the vast troves of unstructured data now available to them to help develop compelling customer experiences and uncover new revenue opportunities. In this webinar, you’ll learn how HDB’s in-database analytics enable advanced use cases in network operations, customer care, and marketing for better customer experience. Join us, and get started on your advanced analytics journey today!

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Advanced Analytics for
Telecommunications
Bob Glithero, Principal Product Marketing Manager
Vineet Goel, Product Manager

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Agenda
• Pivotal – Hortonworks Partnership
• Challenges in Customer Experience
• HDB: Hadoop-Native Analytics Database
for Hortonworks Data Platform
• Sample Use Cases
• For More Information

3. Pivotal HDB + Hortonworks Hadoop
Partnering for Faster Value from Data
● Leaders in open-source Hadoop
● Managing, analyzing, and operationalizing data at
scale
● Joint support for ODPi promotes interoperability in
Hadoop
+
Pivotal and Hortonworks’ strategic partnership marries
Pivotal’s best-in-class SQL on Hadoop, analytical
database, with Hortonworks’ best-in class expertise and
support for Hadoop.

4. You’re the third
person I’ve
been handed
off to!
Can’t anyone
help me?
4

5. I’m not
seeing any
alarms...why
are our
customers
having poor
service?
5

6. Managing Experience is Complicated
Then
• Basic handsets, embedded applications
• Simpler services - voice, SMS, WAP
• Experience influenced mostly inside the network
Now
• From phones to hand-held computers
• Massive data volume, velocity, and variety from millions of apps and
services
• MNOs held responsible for all aspects of service, whether inside or
outside the network

7. CSPs Increasingly Competing on QoE
Trying to understand how network
performance impacts experience
When service is degraded, CSPs need
to quickly understand:
Is the problem inside or outside the
network?
Which subscribers are impacted?
What needs attention first?

8. Common Operator Challenges
Network Operations Customer Care Marketing
Increase monetization, offset
voice, SMS revenue loss
Reduce churn and
credits, cost to serve
Reduce complexity,
increase visibility,
increase QoE

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Operators are turning to their data to
solve these challenges
How do we analyze data in an
efficient, cost-effective way to
transform customer experience?

10. High performance, interactive SQL queries on Hadoop
HDB: The Hadoop Native SQL Database
● Highly efficient MPP
(massively parallel processing)
● Low-latency
● Petabyte scalability
● ACID transaction support
● SQL-92, 99, 2003 compatibility
● Advanced cost-based optimizer
DATA LAKE
SQL App
BUSINESS ANALYSTS
DATA SCIENTISTS

11. Advanced Analytics
Performance
Exceptional MPP performance, low
latency, petabyte scalability, ACID
reliability, fault tolerance
Most Complete
Language Compliance
Higher degree of SQL compatibility,
SQL-92, 99, 2003, OLAP, leverage
existing SQL skills
Best-in-class Query
Optimizer
Maximize performance and
do advanced queries with confidence
Elastic Architecture for
Scalability
Scale-up/down or scale-in/out, expand/
shrink clusters on the fly
Tightly integrated w/
MADlib Machine
Learning
Advanced MPP analytics, data science at
scale, directly on Hadoop data
HDB / HAWQ Advantages
MAD

12. ● Discover New Rela/onships
● Enable Data Science
● Analyze External Sources
● Query All Data Types!
Mul/-level
Fault Tolerance
Granular
Authoriza/on
Resource Pools
+ YARN
Mul$-tenancy + Security
ANSI SQL
Standard
OLAP
Extensions
JDBC ODBC
Connec/vity
MPP
Architecture
Online
Expansion
Hadoop / HDFS
Petabyte Scale
Cost-Based OpXYZizer
Dynamic
Pipelining
ACID +
Transac/onal
Ambari
Management
Machine
Learning
Data
Federa/on
Language
Extensions
Hardened, 10+ Years Tested, Produc/on Proven
Opera$ons + Extensibility
HDFS Na/ve
File Formats
● Manage Mul/ple Workloads
● Petabyte Scale Analy/cs
● Sub-second Performance
● Leverage Exis/ng
Skills & Tools
● Easily Integrate with
Other Tools
Compression
+ Par//oning
Core
compliance
● Well Integrated with
Hortonworks Data
PlaZorm
HDB + HDP Marketecture

13. 13
Faster Insight with In-Database Analytics
Pivotal HDB /
Apache HAWQ (incubating)
Low-latency, MPP analytic
database with full ANSI SQL
support running natively on
Hortonworks HDP
Apache MADlib (incubating)
Scale out, SQL-based
machine learning within
HDB/HAWQ, Greenplum, and
PostgreSQL databases
+

14. 14
Top MADlib Use Cases
• Fraud detection
• Risk analysis
• Customer experience
• Marketing
• Predictive maintenance

15. Telco uses HDB to analyze and improve call quality
2bn call records per day
• Overwhelmed traditional data warehouse
Hadoop and HDB
• 5x data stored at half the cost
• Familiar SQL interface to analyze 3 months
worth of dropped call data
DATA LAKE

16. 16
How could a network operations team apply analytics to
improve experience for its network services?

17. What Data Is Needed?
Service Assurance Customer Care Marketing
• Network Performance data (GTP
probe data)
• HTTP Click Stream Records
• Flow Records
• Network & Device Reference
Data
• Topology and location
• HTTP Click Stream Records
• Flow Records
• Network Performance data (GTP
probe data)
• CRM data (account, device
information)
• Service Request Records
• HTTP Click Stream Records
• Flow Records
• CRM data (account, device
information)

18. Constructing KQIs from performance indicators
84%
Speed
Latency
Effective
Throughput
Integrity
Drops
Time-Outs
Cut-Offs
Failures
Retainability
Failure %
Response time
Access time
Accessibility Voice QoE
Data capture Data science
• xDRs
• NetFlow
• Probes
Data processing
Accessibility
Quality
Retainability

19. In-Database Analytics with HDB and MADlib
Application/
Content Data
• Raw Usage
• Logs
• (HTTP, Flow, Other)
HDFS
HBase
Hive
HDB/HAWQ
In-DB AnalyticsNetwork Data
• Probes (GTP-C/U)
• xDRs
• Case management
• CRM
• Billing
• Device inventory
• Network topology
• Geolocation maps
B/OSS Data
PXF
PXF
MPP Query Execution
ANSI SQL
• SQL-based
• Over 50 data science
functions
• UDFs
• Offline modeling
• Batch queries
• Reporting/viz with
SQL-based tools
+
Native or PXF

20. 20
How could marketing teams use
analytics to better target
subscribers for promotions and
advertising?

21. Blended Mobile ARPU is Declining
Loss of voice and SMS
ARPU from competition,
free apps
Data revenues not
offsetting voice, SMS
losses
MNOs seeking new
monetization options
Source: IHS Technology Mobile ARPU Forecast, 2016

22. Need for Behavioral Insights
• CSPs need to maximize subscriber
yields to offset declining revenues
• Marketers have little information to
market to anonymous prepaid
subscribers
• Need to protect current revenue
from competition from over-the-top
(OTT) apps and services

23. Morning: New York
• Starts on Samsung Galaxy S6
• On CNN, sees news on earthquake
• Donates via Red Cross Society
• Later: Switches to iPad – same account
plan
• Checks market close on WSJ.com
A Day in the Life: User Perspective
Evening: Boston
• Checks Facebook page
• Streams Netflix

24. SubscriberId StartTimeStamp EndTimeStamp URL User Agent
RK2FQ9PWZVW52 2015 04 28 06 37 04 512 2015 04 28 06 37 04 543 http://www.cnn.com Mozilla/5.0 (Linux; U; Android 4.4.2; en-US; SAMSUNG-SM-N900A Build/KOT49H) CNN/2.1.1
RK2FQ9PWZVW52 2015 04 28 06 37 05 546 2015 04 28 06 37 04 623 http://www.cnn.com/world Mozilla/5.0 (Linux; U; Android 4.4.2; en-US; SAMSUNG-SM-N900A Build/KOT49H) CNN/2.1.1
RK2FQ9PWZVW52 2015 04 28 06 37 19 529 2015 04 28 06 37 19 599
http://www.cnn.com/2015/04/28/asia/flight-delhi-
nepal-earthquake/index.html Mozilla/5.0 (Linux; U; Android 4.4.2; en-US; SAMSUNG-SM-N900A Build/KOT49H) CNN/2.1.1
RK2FQ9PWZVW52 2015 04 28 06 37 23710 2015 04 28 06 37 23 770 http://www.cnn.com/2015/04/28/asia/kathmandu.jpg Mozilla/5.0 (Linux; U; Android 4.4.2; en-US; SAMSUNG-SM-N900A Build/KOT49H) CNN/2.1.1
RK2FQ9PWZVW52 2015 04 28 06 37 45919 2015 04 28 06 37 45988 http://adclick.g.doubleclick.net/pics/click/?= Mozilla/5.0 (Linux; U; Android 4.4.2; en-US; SAMSUNG-SM-N900A Build/KOT49H) CNN/2.1.1
RK2FQ9PWZVW52 2015 04 28 06 37 34957 2015 04 28 06 37 34996
http://www.google-analytics.com/__utm.gif?
utmwv=4.9mi Mozilla/5.0 (Linux; U; Android 4.4.2; en-US; SAMSUNG-SM-N900A Build/KOT49H) CNN/2.1.1
RK2FQ9PWZVW52 2015 04 28 06 42 09 883 2015 04 28 06 42 10 467
http://www.cnn.com/2015/04/25/world/nepal-
earthquake-how-to-help/index.html Mozilla/5.0 (Linux; U; Android 4.4.2; en-US; SAMSUNG-SM-N900A Build/KOT49H) CNN/2.1.1
….. (images being loaded here) …….
RK2FQ9PWZVW52 2015 04 28 06 43 03 234 2015 04 28 06 06 12 334 http://www.nrcs.org Mozilla/5.0 (Linux; U; Android 4.4.2; en-US; SAMSUNG-SM-N900A Build/KOT49H)
….. ….. ….. ….. …
RK2FQ9PWZVW52 2015 04 28 09 45 05 732
2015 04 28 09 45 05
812 http://wsj.com
Mozilla/5.0 (iPad; CPU OS 8_1 like Mac OS X) AppleWebKit/600.1.4 (KHTML, like Gecko) Version/
8.0 Mobile/12B410 Safari
….. ….. ….. … …
RK2FQ9PWZVW52 2015 04 28 17 03 14 204 2015 04 28 17 03 14 269 http://wsj.com
Mozilla/5.0 (iPad; CPU OS 8_1 like Mac OS X) AppleWebKit/600.1.4 (KHTML, like Gecko) Version/
8.0 Mobile/12B410 Safari
….. ….. ….. … …
RK2FQ9PWZVW52 2015 04 28 18 19 56 459 2015 04 28 18 19 56 509 https://69.63.178.45
….. ….. ….. … …
RK2FQ9PWZVW52 2015 04 28 21 23 25 754 2015 04 28 21 23 25 876 http://23.13.201.71 netflix-ios-app
A Day in the Life: Data Perspective
• Capture and collate raw subscriber data
• Sessionize and enrich clickstream data with location, device. and other data, calculate subscriber
usage metrics

25. SubscriberId DeviceNAME PUBLISHER
Category-
Subcategory
Application
Name SESSION START SESSION END PAGE_VIEWS HITS BYTES LOCATION
RK2FQ9PWZVW52 Samsung Galaxy S6 CNN News
News-International
News CNN App 2015 04 28 06 37 04 512 2015 04 28 06 42 10 467 4 45 539123 NY
RK2FQ9PWZVW52 Samsung Galaxy S6 Red Cross
Non Profit &
Charities-Institutions Browser 2015 04 28 06 43 03 234 2015 04 28 06 53 03 874 2 7 383372 NY
RK2FQ9PWZVW52 Apple iPad
Wall Street
Journal
News-Business &
Finance News Safari Browser 2015 04 28 09 45 05 732 2015 04 28 09 55 05 732 4 40 600272 NY
RK2FQ9PWZVW52 Apple iPad
Wall Street
Journal
News-Business &
Finance News Safari Browser 2015 04 28 17 03 14 204 2015 04 28 17 23 14 204 5 35 801714 NY
RK2FQ9PWZVW52
Apple iPad
Facebook
Social Media &
Networking-Social
Networking -
2015 04 28 18 19 56 459
2015 04 28 18 23 21 459
318 5041054 Boston
RK2FQ9PWZVW52
Apple iPad
Netflix
Media &
Entertainment-Online
Video Ne&lix App
2015 04 28 21 23 25 876
2015 04 28 23 23 24 325
6 2330 295121789 Boston
Compute subscriber-level metrics and aggregates
…enrich with information about content (websites or apps) and
categorization, devices, and locations
Aggregation and Enrichment

26. Insights: Marketing to Prepaid Users
• With data science, operators can infer gender
and approximate age from subscriber activity
• Classify according to segmentation schemes
(e.g., who does unknown subscriber resemble
from their activity)
We can offer advertisers anonymized
subscriber info mapped to standard
marketing/advertising categories (e.g.,
IAB) based on activity

27. Marketing Questions We Can Answer with Analytics
• How will subscribers respond
to changes in pricing?
• How do we market to
anonymous pre-paid
subscribers?
• Who’s likely to respond to an
offer?
• Which OTT apps threaten
our own branded apps?
• Which groups should we
target with advertising?

28. Pivotal and
Hortonworks are
partnering to help
companies use their
data for better
customer outcomes

29. Learn more
• Videos: bit.ly/MADlibvideos
• Project: madlib.incubator.apache.org
• Downloads: bit.ly/getMADlib
• Videos: bit.ly/HDBvideos
• Project: hawq.incubator.apache.org
• Commercial: pivotal.io/pivotal-hdb
• Downloads: bit.ly/getHDB

30. Let’s build something
MEANINGFUL