Benefiting from Big Data - A New Approach for the Telecom Industry

© 2014 Persontyle Ltd. All rights reserved.
Ali Syed
Founder and Chief Data Scientist
Persontyle
Customer Insight and Analyticsin Telecoms 2014
Benefiting from Big Data
A New Approach for the Telecom Industry

One Objective, Fifteen Minutes
“To understand how Telecom companies can employ big data technologies and machine learning techniques to exploit user, network and traffic data assets.”

LET’S SETTHE SCENE
Amazing view of Manhattan, New York, in 1944

"Creativity involves breaking out of established patterns in order to look at things in a different way" -Edward de Bono

DIGITAL TRANSFORMATION
GLOBALIZATION
9 Billion
Internet Devices in 2012
50 Billion
By 2020
DATA EXPLOSION
90%
Created within
Last Two Years
50X Growth
By 2020
RISE OF MOBILITY
6 Billion +
Mobile Connections
87%
of World’s Population
Mobile Data Growing 78% CAGR
CLOUD
90%
of new software delivery for Public Cloud
Public IT cloud services will grow to $107B in 2017

DATA AS A FABRIC OF DIGITAL AGE
All actions, interactions and behaviours both of humans and machines are stored and transmitted across networks to keep the engines of the digital age running.
The amount and complexity of data produced in science, business, and everyday human activity are increasing at staggering rates.
As we move from isolation into a massively connected world, making sense of data is the key ingredient in delivering meaningful value, competitive advantage, and prosperity.

THE MASS SCALE DATAFICATIONHAS LED TO AN EXPLOSION OF THE (big) DATA.
Social Media Data
Operational Data e.g.CDRs, CRM, Financial, LOB, etc.
Machine Data
Big Data
Transactions, Interactions, Observations
Clickstream Data

TELCOM BIG DATA CHALLENGES
Volume, granularity, diversity and latency of the data keeps growing
Need to shrink latency between business event and data availability for analysis and decision-making
Business mandate to obtain more value out of the data
The days of being impressed with standing up a petabyte system are over
Absence of data discovery and advanced analytics hindering discovery of business insights and value opportunities

OPPORTUNITY
“People used to say that information is power but that’s no longer the case. It’s analysis of the data, use of the data, digging into it –that is the power”
Sir Martin Sorrell, CEO, WPP Group

The State of Big Data and Analytics Market in 2014
MARKET

-94% of C-level executives say their organization is collecting and managing more business information today than two years ago, by an average of 86%more
-29%of executives cited that they are not ready to manage the data deluge
-93%of executives believe their organization is losing revenue – on average, 14%annually –as a result of not being able to fully leverage the information they collect
-97% say their organization must make a change to improve information optimization over the next two years
Industry-specific applications are an important part of the mix; 77%of organizations surveyed use them today to run their enterprise—and they are looking for more tailored options
Source: Oracle.com
Big Data Requires a New Kind of
Strategic Planning

According to Gartner, 64% of large enterprises plan to implement a big data project in 2014, but 85% of the Fortune500 will beunsuccessful in doing so.

“Big data is here to stay, as it should be. But let’s be realistic: It’s an important resource for anyone analysing data,not a silver bullet.”
GARY MARCUS and ERNEST DAVIS

Big Data isn’t new.
What is new is the availability and power of the tools for collecting, storing, managing and analyzingdata.

Disruptive Innovations in Big Data
Traditional
Database
HADOOP
NoSQL
Database
MPP
Analytics
Data Warehouse
Schema
Pre-defined, fixed
Required on write
Required on read
Store first, ask questions later
Processing
No or limited
data processing
Processing coupled with data Parallel processing / scale out
Data types
Structured
Any, including unstructured
Physical infrastructure
Enterprise grade
Mission critical
Commodity is an option
Much cheaper storage

Reference Architecture –Example
Infrastructure
Virtualization
Compute / Storage / Network
Operations
Workflow and Scheduling
Management and Monitoring
Security
Data Isolation
Access Management
Data Encryption
Data Processing
Batch Processing
Real Time/Stream Processing
Search and Indexing
Application
Analytics Apps
Transactional Apps
Analytics Middleware
Presentation
Data Visualization and Reporting
Clients
Data Integration
Real Time Ingestion
Batch Ingestion
Data Connectors
Metadata Services
Data Management
Distributed Processing
(MapReduce)
Non-relational DB
Structured In- Memory
Distributed Storage
(HDFS)
HadoopCore
HadoopProjects
Adjacent Categories

A Complete Enterprise Hadoop Data Platform
Source: Hortonworks

Application Landscape -Example
ETL
Real Time
Streams
(Social,
sensors)
Structured and Unstructured Data(HDFS, MAPR)
Real Time
Database
(Shark,
Gemfire, hBase, Cassandra)
Interactive Analytics
(Impala,
Greenplum,
AsterData,
Netezza…)
Batch
Processing
(Map-Reduce)
Real-Time
Processing
(s4, storm,
spark)
Data Visualization(Excel, Tableau)
(Informatica, Talend, Spring Integration)
Compute
Storage
Networking
Cloud Infrastructure
HIVE
Machine Learning
(Mahout, etc…)
Source: Vmware

“The role of a creative leader is not to have all the ideas; it’s to create a culture where everyone can have ideas and feel that they’re valued”
Sir Ken Robinson

“Learn from companies such as Google and Facebook, where data is king and virtually every product decision flows from what the available data says about customers and how it can be used.”
As ones and zeros eat the world, data is the new product and data science is the new process of innovation.
Optimizing routing and quality of service by analysing network traffic in real time
Analysing call data records in real time to identify fraudulent behaviour immediately
Allowing call centre reps to flexibly and profitably modify subscriber calling plans immediately
Tailoring marketing campaigns to individual customers using location-based and social networking technologies
Using insights into customer behaviour and usage to develop new products and services
Big data can even open up new sources of revenue, such as selling insights about customers to third parties.
Source: Strategy& analysis

Source: Strategy& analysis
Big Data and Analyticsoffers benefits across the entire telecom value chain

Telecom Organizations don’t need a Big Data Strategy;
THEY NEED A BUSINESS STRATEGY THAT INCORPORATES BIG DATA.
Source: McKinsey & Company

Stay Ahead of the Game
Elephant in the Cloud (Platforms, Services and APIs)
Hadoop clusters bloom in the cloud. Use Hadoop in the cloud to meet demand for ad hoc analytics, yet on-premises adoption "won't slow down."
Apache Ambariand VMware vSphere Big Data Extensions Integrate to Provision and Manage Enterprise Hadoop Clusters
Hadoop: The New Enterprise Data Operating System
Hadoop won't be just for analytics.
Traditional database theory dictates that you design the data set before entering any data. A data lake, also called an enterprise data lake or enterprise data hub, turns that model on its head.
Data Science, Predictive Analytics and Machine Learning
SQL on Hadoop: Faster, better (HIVE, IMPALA, SPARK, etc.)
SQL becomes Hadoop's killer app
More, better NoSQL to power IOT and Industrial Net
Deep Learning + Cognitive Computing + Apps and APIs
In-memory Analytics (hybrid transaction/analytical processing (HTAP) —allowing transactions and analytic processing to reside in the same in-memory database.

"LISTENING TO THE DATA - DOING EXPERIMENTS, ANALYZING THE RESULTS, DIGGING DEEPER, FOLLOWING UP ON SURPRISES
-IS THE PATH TO SUCCESS."
PROF. PEDRO DOMINGOS

What is Persontyle?
Persontyle is a people focused social enterprise obsessed with helping individuals, organizations and communities learn and apply Data Science to deliver real and meaningful value.
Born from the idea of creating a platform for the people, by the people to share passion, knowledge, theory and practices of analysing data scientifically.

OUR MISSION IS TO PROMOTE DATA LITERACY AND EMPOWER YOU TO ANALYZE DATA SCIENTIFICALLY.
EDUCATION
THE SCHOOL OF DATA SCIENCE
COMMUNITY SERVICES
DATA SCIENCE FOR SOCIAL CHANGE
PROFESSIONAL SERVICES

THE SCHOOL OF DATA SCIENCE SPECIALIZES IN HELPING YOU LEARN DATA SCIENCE AND MACHINE LEARNING IN SIMPLE HUMAN TERMS.
Join the Data Revolution
DATA SCIENCE
MACHINE LEARNING
DATA ENGINEERING
DATA VISUALIZATION
OFFERING THE MOST COMPREHENSIVE SET OF DATA SCIENCE AND MACHINE LEARNING COURSES.
GARNER THE SKILLS NECESSARY TO SUCCEED IN THE FIELD OF DATA SCIENCE.

We provide a full range of short courses and training programs to help you learn the skills you need to become a practicing data scientist.
Data Science and Machine Learning Courses
Big Data Academy
Corporate Data Science Training Solutions
The Data Science Incubator
Open Data Science Fellows Program

ALI SYED
@aaalee
EMAIL
ali.syed@persontyle.com
JOIN THE CONVERSATION: @persontyle
@schooltds
WWW.PERSONTYLE.COM

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