SlideShare una empresa de Scribd logo
1 de 6
Descargar para leer sin conexión
Intel has taken a
leadership role to bring
Hadoop* to enterprises,
enabling scalable,
cost-effective analytical
solutions in the market. Our
ecosystem partners like Flytxt
are a great example of how we
are accelerating the solution
for faster adoption across
enterprises.
CASE STUDY
Intel® Xeon® Processor E5 Product Family
Intel® Server Systems
Intel® Ethernet 10 Gigabit Adapters
Big Data Analytics
Telecommunications
Transforming Data Insights
into Business Value with Big Data Analytics
Intel partners with Flytxt and Netweb Technologies to deliver one of the largest Big Data Analytics
deployments for a leading telecom service provider in India
The telecommunications industry is a melting pot of data. The steady
growth in the number of users coupled with the advent of multiple
smartphones and their complex features and abilities has led to the
existence of voluminous and widely variable data, all conceived at high
velocity and scattered across departments and business units.
One of India’s leading telecom service providers sought to establish market
leadership and deliver customer satisfaction by providing personalized and
contextually relevant offers to their customers in real-time.
Flytxt Analytics platform leveraging high performance Intel® based servers
from Netweb Technologies running Hadoop* clusters brought an entirely
new dimension in the way the telecom service provider could utilize the full
power of data available with them to enhance customer experience and
increase revenue.
Challenges
• More real time than near-real-time: Obtaining insights in real time, at the
velocity in which data is generated, and then using these insights to take
decisions in real time, was a major challenge for the telecom service
provider. The latency between the subscriber initiated event to insight and
then to action needed to be minimized greatly. Legacy systems struggled
to meet this requirement and hence the telecom service provider could
not respond to the customers’ needs within the window of relevance.
• More relevant than categorized: The telecom service provider generated
huge volumes of subscriber data at various sources. Up to 4 terabytes of
data were generated in a day, and these data had to be analysed for taking
instant decisions. Processing such voluminous and varied data to generate
insight for decision making presented a daunting challenge, in terms of
technology and the time involved. This in turn meant that offers were not
always relevant to subscribers and specific marketing needs like churn
prevention and margin optimization were not met.
• Closing the loop - gratification in real time: The telecom service provider
had disjointed systems for data processing, campaign execution and
rewards gratification. This meant a long delay between target generation
to campaign execution to call-to-action to gratification.
RadhaKrishna Hiremane
Regional Product Marketing Manager,
Intel Corporation
Why Big Data Matters
Data is exploding at an astounding
rate. Billions of connected devices -
ranging from PCs and smartphones
to sensor devices such as RFID
readers and traffic cams - generate
this flood of complex structured and
unstructured data.
Unstructured data is heterogeneous
and variable in nature, and comes in
many formats including text,
document, image, video, and more.
A critical component in the
telecommunications industry,
unstructured data is growing faster
than structured data. As a new,
relatively untapped source of insight,
unstructured data analytics can
reveal important interrelationships
that were previously difficult or
impossible to determine.
Big Data Analytics is a
technology-enabled strategy for
gaining richer, deeper, and more
accurate insights into customers and
the business, and ultimately gaining
competitive advantage. By
processing a steady stream of
real-time data, organizations can
make time-sensitive decisions faster
than ever before, monitor emerging
trends, course-correct rapidly, and
jump on new business opportunities.
Flytxt is a leading provider of Big Data
Analytics powered solutions with a
focus on enabling mobile operators to
derive measurable economic value
from subscriber data. The company
offers customer experience, revenue
management and insight monetization
solutions as well as consultancy
services. Flytxt solutions are deployed
with leading operators across APAC
and EMEA, serving more than 500
million subscribers; generating around
$350 million incremental revenue for
operators till now.
Flytxt has won many industry awards
and recognitions like Frost & Sullivan
ICT Awards 2014 for Product
Innovation Leadership in Marketing
Analytics, Gartner Cool Vendor,
NASSCOM* League of 10, CEM
Excellence* Award for Middle East,
Aegis* Graham Bell Award for
Innovation in Mobile Advertising, BID*
International Quality Award, Red
Herring* Asia 100 and IEEE Cloud
Computing Challenge. Flytxt has its
headquarters in Netherlands, corporate
office in Dubai and global delivery
centres in Trivandrum and Mumbai.
Flytxt also has presence in London,
Kuala Lumpur, Lagos, Nairobi, Dhaka
and New Delhi.
Spotlight on Flytxt
Solutions
• Flytxt: NEON, a Big Data Analytics Platform and Revenue Enhancer
Application - based on an Intel® Architecture-based real-time, fully integrated
Hadoop* platform, powers the client’s real-time contextual trigger-driven
marketing campaigns.
• Netweb Technologies: Flytxt’s Big Data Analytics Solution was deployed on
highly resource-intensive Netweb's Tyrone servers powered by Intel® Xeon®
processors.
• Intel: Hadoop* clusters based on Intel® Xeon® E5 processors and Intel®
Ethernet 10 Gigabit Converged Network Adapters.
Impact
• Enhanced Customer Experience: Response time to customer events reduced
from 24 hours to 30 minutes.
• High Conversion Rate: 5.9% incremental conversions of subscribers
month-on-month.
• Maximized Migration to Higher Value Base: 55% of the customers moved to
higher-value recharge segments.
• Rapid Growth in ARPU: Target customer base clocked a net ARPU growth of
18.9%.
This is a first of
its kind deployment of this
scale in the telecom world,
where a Big Data Analytics
solution enabled a telecom
service provider to bring
together the power of ‘real-
time context’ and ‘in-depth
subscriber intelligence’ to
send personalized offers to
their millions of subscribers in
real time.
Prateek Kapadia
Chief Technology Officer,
Flytxt
current legacy system, which was
struggling with the huge load of data,
by implementing a cutting-edge
real-time marketing system
leveraging on the advantages of Big
Data Analytics to enhance the
customer experience and drive
incremental revenue.
Integrated Big Data Analytics
for Big Success
Flytxt, a leading provider of Big Data
Analytics powered solutions,
empowered their client to transform
the way they provide customer
satisfaction, positively impacting their
business in a huge way.
Flytxt’s multi-dimensional integrated
Analytics framework addressed the
challenges and complexities of new
age information asset processing and
accelerated sustained economic value
generation from data for the client.
Flytxt Integrated Analytics framework
enabled the telecom service provider
do analytics faster, deeper, and in a
more efficient and objective-driven
way from a single easy to use
interface, reducing the ‘data to
decision’ time significantly.
Riding the Big Data Wave.
Addressing Big Challenges.
The client, one of India’s leading
telecom service providers, in their
constant endeavour to stay ahead of
the competition in the highly volatile
and competitive Indian market was
looking to ramp up their customer
service platform, enhance the average
revenue per user (ARPU) and reduce
customer churn considerably. And
with tight regulatory intervention and
number portability options further
intensifying the price competition in
the market, the client stood in the
cusp of great challenges and
opportunities.
The Big Data challenges facing the
client, who has a subscriber base
close to 200 million, were gargantuan
and can be gauged from the
intimidating number of data being
handled regularly including 3.5TB of
data and 4 billion events per day, 200
million subscribers, 20,000+ data
jobs, 530 million triggers, 7,000+
broadcast rules, 21,000+ tracking
rules, and 14,000 tags/KPIs per
subscriber.
The client was looking to refresh their
Netweb is a leading provider of High
Performance Computing, Big Data
and Storage solutions, and has
been a trusted name for providing
best-in-class solutions for almost
two decades. Netweb Technologies
has seven offices globally in India,
Singapore, and South East Asia.
Netweb Technologies provides
best-in-class products that deliver
solutions combining speed,
reliability, and scalability with
energy efficiency to deliver
maximum ROI at lower TCO.
Netweb Technologies is widely
recognized for its implementation
of the PARAM Yuva II System,
India’s fastest hybrid
supercomputer till date and is also
well-known for its out of the box,
totally customizable solutions.
Netweb Technologies provides
custom configured solutions for
HPC environments and related
applications for verticals that span
across Pharma, Manufacturing, Oil
and Gas, Animation R&D, Earth
Sciences, Defense, Science and
Technology in India and other
developing economies around the
world.
Spotlight on Netweb
Technologies
Hadoop* server clusters powered by
Intel® Xeon® processors can enable
near-real-time discoveries.
Driving the Big Data
Revolution. Making a Big
Difference.
Leveraging on their deep expertise in
Big Data Analytics, Flytxt delivered an
intelligent and powerful Analytics
solution to capture the behavioural
pattern of existing subscribers and
provide relevant offers and deals
tailored to the customer’s need.
With its Integrated, Multi-Dimensional
Analytics Framework, Flytxt enabled
the following capabilities for the
telecom service provider:
• Predictive Analytics: Predict the
propensity to churn, winback,
purchase, etc.
• Prescriptive Analytics: Suggest best
channel, offer, price affinity based
on given business objective/context
• Heuristic Analytics: Behavioural
customer segmentation based on
marketer/expert/SME hypothesis
and experience
This was made possible through the
deployment of Flytxt’s Revenue
Enhancer Application, a
game-changing solution powered by
NEON, which is a Big Data Analytics
powered revenue and customer
experience management platform for
telecom service providers.
NEON’s rich set of applications
enabled the telecom service
provider’s marketing team to run a
wide variety of real-time trigger-based
campaigns in areas like loyalty and
retention, churn management, usage
and recharge stimulation, VAS
marketing and product up-selling/
cross-selling.
The following triggers were utilized by
the telecom service provider to
maximize their customers’ experience:
• Recharge Trigger: Recharge for ‘ n’
denomination, ‘n’th recharge of the
day etc.
• Balance Trigger: Balance going
below the threshold
• OG Call (Voice): First/‘n’th minute
call of the day
• Local On-Net OG Call (Voice)
• National Calling Outgoing (Voice)
• International Calling Outgoing
(Voice)
• Roaming OG Call (Voice): Trigger on
roaming
• SMS Count: ‘n’th SMS
• GPRS Usage, etc.
Segment Product Rol Location
Marketing
programs Infrastructure
Descriptive
Exploratory
Heuristic
Predictive
Prescriptive
Fig. 2: Flytxt Integrated, Multi-Dimensional Analytics Framework
With real-time marketing, Analytics
driven decisions and actions were
integrated into the business
workflows in no time. This reduced
the telecom service provider's
response time to customer actions
from days to seconds. Closed-loop
workflow also allowed the marketers
to perform experimentations quickly
to iteratively improve marketing
effectiveness. For example, it allowed
the operator to run A/B testing to
choose the best campaign, creative,
time and channel for a given segment.
Powering Big Data Analytics
with Powerful Hardware
Netweb Technologies, a leading
provider of Server, Storage and HPC
solutions, played a critical role in
enabling the solution and was a key
driving force behind the daunting
setup of a solution of this scale.
The powerful NEON platform, which
powers Flytxt’s intelligent solution,
runs on Intel® Xeon® processor E5 v2
product family based Tyrone* Servers.
Netweb Technologies was responsible
for the end-to-end deployment of the
hardware platform, including
installation and support. The NEON
platform operates on top of an Intel®
based Tyrone compute nodes running
two Intel® Xeon® processors E5-2609
v2, and 10GbE networking was used
to support the high-performance
compute requirement.
Netweb Technologies, famously
known for creating India’s fastest and
largest hybrid supercomputer - the
PARAM Yuva II System - ensured
timely delivery, smooth setup, and
24x7 support and service, leveraging
on their supercomputing expertise.
Making Big Data
Analytics Real
Intel® Xeon® Processor-based
Hadoop* server clusters with 10
Gigabit Intel® Ethernet Solutions acted
as the main engine behind Flytxt’s
cutting-edge Big Data solution for the
client.
Intel-based Hadoop* server clusters,
which include a total of 130 servers
split into 5 Hadoop* clusters and
standalone servers, delivered the
performance needed to handle large
data sets with tightly integrated
security features, scalability and
management. Along with these, Intel
provided irreplaceable practical
guidance and training to aid in risk
mitigation.
The Hadoop* server clusters based on
Intel® Xeon® E5 processors and Intel®
Ethernet 10 Gigabit Converged
Network Adapters delivered the
performance required by the client for
their intelligent insights need -
helping to maximize the client’s
potential, enhance customer
experience and gain larger revenues.
Delivering Maximum
Business Value
Flytxt’s Revenue Enhancer Application
was integrated over 14,000 business
KPIs. These were used to slide and
dice the whole subscriber base into
granular segments. Subscriber profile
and behaviour analytics-driven
micro-segmentation allowed the
marketers to define personalized and
relevant offers for different segments
of subscribers through churn
predictions (demographics,
Call/SMS/Data Usage, recharges,
propensity scores, personas).
The Revenue Enhancer Application
tracks billions of customer events to
identify these pre-defined triggers,
initiates sending of contextual offers
automatically to subscribers, and also
tracks for conversions and then
passes on rewards depending on the
event trigger identified.
Riding on this unique method of
maximizing the power of Big Data
Analytics to deliver the best
experience to customers, this
Netweb Technologies
provided trusted and reliable
hardware platforms that Intel
and Flytxt were looking for,
to build a cutting-edge,
next-gen solution that meets
the client’s highly-complex
and resource-intensive Big
Data requirement.”
Sanjay Lodha
Chief Executive Officer,
Netweb Technologies
Conclusion - Collaborating to Deliver a Best-in-Class
Solution
The perfect collaboration of Intel, Flytxt and Netweb Technologies delivered
a one-of-a-kind Data Analytics solution for the client. And for the first time
ever in India, this solution helped a telecom service provider to bring
together the power of ‘real-time context’ and ‘in-depth subscriber
intelligence’ to send personalized offers to millions of subscribers.
Further, this collaborative endeavour ensured that the highly-complex and
resource-intensive Big Data Analytics implementation was delivered in a
record time of just 3 months.
To summarize, this solution helped deliver exceptional benefits in the form
of increased revenue, enhanced customer experience, and maximized
learning, in turn paving the way for a winning future.
innovative solution delivered tangible
business benefits for the client that
include:
• Huge reduction in response time to
customer - from 24 hours to 30
minutes
• 5.9% incremental conversions of
subscribers month-on-month
• 55% increase in upgrade to
higher-value recharge segments
• 18.9% ARPU growth rate of target
customer base
Find the solution that’s right for your
organization. Contact your Intel
representative, visit Intel’s Business
Success Stories for IT Managers
(www.intel.com/Itcasestudies) or
explore the Intel.com IT Center
(www.intel.com/itcenter).
INFORMATION IN THIS DOCUMENT IS PROVIDED IN CONNECTION WITH INTEL® PRODUCTS. NO LICENSE, EXPRESS OR IMPLIED, BY ESTOPPEL OR OTHERWISE, TO ANY INTELLECTUAL
PROPERTY RIGHTS IS GRANTED BY THIS DOCUMENT. EXCEPT AS PROVIDED IN INTEL’S TERMS AND CONDITIONS OF SALE FOR SUCH PRODUCTS, INTEL ASSUMES NO LIABILITY
WHATSOEVER, AND INTEL DISCLAIMS ANY EXPRESS OR IMPLIED WARRANTY, RELATING TO SALE AND/OR USE OF INTEL PRODUCTS INCLUDING LIABILITY OR WARRANTIES RELATING TO
FITNESS FOR A PARTICULAR PURPOSE, MERCHANTABILITY, OR INFRINGEMENT OF ANY PATENT, COPYRIGHT OR OTHER INTELLECTUAL PROPERTY RIGHT. UNLESS OTHERWISE AGREED
IN WRITING BY INTEL, THE INTEL PRODUCTS ARE NOT DESIGNED NOR INTENDED FOR ANY APPLICATION IN WHICH THE FAILURE
OF THE INTEL PRODUCT COULD CREATE A SITUATION WHERE PERSONAL INJURY OR DEATH MAY OCCUR.
Intel may make changes to specifications and product descriptions at any time, without notice. Designers must not rely on the absence or characteristics of any features or instructions
marked “reserved” or “undefined.” Intel reserves these for future definition and shall have no responsibility whatsoever for conflicts or incompatibilities arising from future changes to them.
The information here is subject to change without notice. Do not finalize a design with this information. The products described in this document may contain design defects or errors known
as errata which may cause the product to deviate from published specifications. Current characterized errata are available on request. Contact your local Intel sales office or your distributor
to obtain the latest specifications and before placing your product order.
Intel does not control or audit the design or implementation of third party benchmark data or Web sites referenced in this document. Intel encourages all of its customers to visit the
referenced Web sites or others where similar performance benchmark data are reported and confirm whether the referenced benchmark data are accurate and reflect performance of
systems available for purchase.
This document and the information given are for the convenience of Intel’s customer base and are provided “AS IS” WITH NO WARRANTIES WHATSOEVER, EXPRESS OR IMPLIED,
INCLUDING ANY IMPLIED WARRANTY OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, AND NON INFRINGEMENT OF INTELLECTUAL PROPERTY RIGHTS. Receipt or
possession of this document does not grant any license to any of the intellectual property described, displayed, or contained herein. Intel® products are not intended for use in medical,
lifesaving, life-sustaining, critical control, or safety systems, or in nuclear facility applications.
Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark and MobileMark, are
measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other
information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For more
information go to www.intel.com/performance
Copyright © 2014 Intel Corporation. All rights reserved. Intel, the Intel logo, Intel Inside, Look Inside, and Intel Xeon are trademarks of Intel Corporation in the U.S. and/or other countries.
*Other names and brands may be claimed as the property of others.

Más contenido relacionado

La actualidad más candente

Enterprise Data Management Framework Overview
Enterprise Data Management Framework OverviewEnterprise Data Management Framework Overview
Enterprise Data Management Framework OverviewJohn Bao Vuu
 
Why Do Banks Need A Customer Data Platform?
Why Do Banks Need A Customer Data Platform?Why Do Banks Need A Customer Data Platform?
Why Do Banks Need A Customer Data Platform?Lemnisk
 
Enterprise Data Architecture Deliverables
Enterprise Data Architecture DeliverablesEnterprise Data Architecture Deliverables
Enterprise Data Architecture DeliverablesLars E Martinsson
 
Zero to Snowflake Presentation
Zero to Snowflake Presentation Zero to Snowflake Presentation
Zero to Snowflake Presentation Brett VanderPlaats
 
Snowflake SnowPro Certification Exam Cheat Sheet
Snowflake SnowPro Certification Exam Cheat SheetSnowflake SnowPro Certification Exam Cheat Sheet
Snowflake SnowPro Certification Exam Cheat SheetJeno Yamma
 
Intro to Marketo Demo
Intro to Marketo DemoIntro to Marketo Demo
Intro to Marketo DemoMarketo
 
Modern-Data-Warehouses-In-The-Cloud-Use-Cases-Slim-Baltagi
Modern-Data-Warehouses-In-The-Cloud-Use-Cases-Slim-BaltagiModern-Data-Warehouses-In-The-Cloud-Use-Cases-Slim-Baltagi
Modern-Data-Warehouses-In-The-Cloud-Use-Cases-Slim-BaltagiSlim Baltagi
 
Social Media Analytics
Social Media AnalyticsSocial Media Analytics
Social Media AnalyticsMuhammad Rifqi
 
Data Architecture Strategies
Data Architecture StrategiesData Architecture Strategies
Data Architecture StrategiesDATAVERSITY
 
What is (and who needs) a customer data platform?
What is (and who needs) a customer data platform?What is (and who needs) a customer data platform?
What is (and who needs) a customer data platform?Angela Sun
 
Agile Data Governance Tutorial
Agile Data Governance TutorialAgile Data Governance Tutorial
Agile Data Governance TutorialTami Flowers
 
Data Centric Transformation in Telecom
Data Centric Transformation in TelecomData Centric Transformation in Telecom
Data Centric Transformation in TelecomDataWorks Summit
 
Social Media Analytics
Social Media AnalyticsSocial Media Analytics
Social Media AnalyticsKelli Burns
 
Data Architecture Brief Overview
Data Architecture Brief OverviewData Architecture Brief Overview
Data Architecture Brief OverviewHal Kalechofsky
 
Data Governance — Aligning Technical and Business Approaches
Data Governance — Aligning Technical and Business ApproachesData Governance — Aligning Technical and Business Approaches
Data Governance — Aligning Technical and Business ApproachesDATAVERSITY
 
Data Profiling, Data Catalogs and Metadata Harmonisation
Data Profiling, Data Catalogs and Metadata HarmonisationData Profiling, Data Catalogs and Metadata Harmonisation
Data Profiling, Data Catalogs and Metadata HarmonisationAlan McSweeney
 
Designing An Enterprise Data Fabric
Designing An Enterprise Data FabricDesigning An Enterprise Data Fabric
Designing An Enterprise Data FabricAlan McSweeney
 
Making the Case for Legacy Data in Modern Data Analytics Platforms
Making the Case for Legacy Data in Modern Data Analytics PlatformsMaking the Case for Legacy Data in Modern Data Analytics Platforms
Making the Case for Legacy Data in Modern Data Analytics PlatformsPrecisely
 

La actualidad más candente (20)

Enterprise Data Management Framework Overview
Enterprise Data Management Framework OverviewEnterprise Data Management Framework Overview
Enterprise Data Management Framework Overview
 
Why Do Banks Need A Customer Data Platform?
Why Do Banks Need A Customer Data Platform?Why Do Banks Need A Customer Data Platform?
Why Do Banks Need A Customer Data Platform?
 
Enterprise Data Architecture Deliverables
Enterprise Data Architecture DeliverablesEnterprise Data Architecture Deliverables
Enterprise Data Architecture Deliverables
 
Zero to Snowflake Presentation
Zero to Snowflake Presentation Zero to Snowflake Presentation
Zero to Snowflake Presentation
 
Snowflake SnowPro Certification Exam Cheat Sheet
Snowflake SnowPro Certification Exam Cheat SheetSnowflake SnowPro Certification Exam Cheat Sheet
Snowflake SnowPro Certification Exam Cheat Sheet
 
Intro to Marketo Demo
Intro to Marketo DemoIntro to Marketo Demo
Intro to Marketo Demo
 
Modern-Data-Warehouses-In-The-Cloud-Use-Cases-Slim-Baltagi
Modern-Data-Warehouses-In-The-Cloud-Use-Cases-Slim-BaltagiModern-Data-Warehouses-In-The-Cloud-Use-Cases-Slim-Baltagi
Modern-Data-Warehouses-In-The-Cloud-Use-Cases-Slim-Baltagi
 
adb.pdf
adb.pdfadb.pdf
adb.pdf
 
Social Media Analytics
Social Media AnalyticsSocial Media Analytics
Social Media Analytics
 
Data Architecture Strategies
Data Architecture StrategiesData Architecture Strategies
Data Architecture Strategies
 
What is (and who needs) a customer data platform?
What is (and who needs) a customer data platform?What is (and who needs) a customer data platform?
What is (and who needs) a customer data platform?
 
Agile Data Governance Tutorial
Agile Data Governance TutorialAgile Data Governance Tutorial
Agile Data Governance Tutorial
 
Data Centric Transformation in Telecom
Data Centric Transformation in TelecomData Centric Transformation in Telecom
Data Centric Transformation in Telecom
 
Social Media Analytics
Social Media AnalyticsSocial Media Analytics
Social Media Analytics
 
Data Architecture Brief Overview
Data Architecture Brief OverviewData Architecture Brief Overview
Data Architecture Brief Overview
 
Data Governance — Aligning Technical and Business Approaches
Data Governance — Aligning Technical and Business ApproachesData Governance — Aligning Technical and Business Approaches
Data Governance — Aligning Technical and Business Approaches
 
Data Profiling, Data Catalogs and Metadata Harmonisation
Data Profiling, Data Catalogs and Metadata HarmonisationData Profiling, Data Catalogs and Metadata Harmonisation
Data Profiling, Data Catalogs and Metadata Harmonisation
 
Designing An Enterprise Data Fabric
Designing An Enterprise Data FabricDesigning An Enterprise Data Fabric
Designing An Enterprise Data Fabric
 
Data Warehouse 101
Data Warehouse 101Data Warehouse 101
Data Warehouse 101
 
Making the Case for Legacy Data in Modern Data Analytics Platforms
Making the Case for Legacy Data in Modern Data Analytics PlatformsMaking the Case for Legacy Data in Modern Data Analytics Platforms
Making the Case for Legacy Data in Modern Data Analytics Platforms
 

Similar a Netweb flytxt-big-data-case-study

How big data analytics can optimize the telecom sector
How big data analytics can optimize the telecom sector How big data analytics can optimize the telecom sector
How big data analytics can optimize the telecom sector GlobalTechCouncil
 
Rebooting IT Infrastructure for the Digital Age
Rebooting IT Infrastructure for the Digital AgeRebooting IT Infrastructure for the Digital Age
Rebooting IT Infrastructure for the Digital AgeCapgemini
 
Monetizing the Internet of Things: Creating a Connected Customer Experience
Monetizing the Internet of Things: Creating a Connected Customer ExperienceMonetizing the Internet of Things: Creating a Connected Customer Experience
Monetizing the Internet of Things: Creating a Connected Customer ExperienceZuora, Inc.
 
Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...
Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...
Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...Denodo
 
HP Communications and Media | Solutions IoT Platform
HP Communications and Media | Solutions IoT Platform HP Communications and Media | Solutions IoT Platform
HP Communications and Media | Solutions IoT Platform Norberto Enomoto
 
Century link custom_final_v4
Century link  custom_final_v4Century link  custom_final_v4
Century link custom_final_v4CMR WORLD TECH
 
Softchoice the changing world of it
Softchoice   the changing world of itSoftchoice   the changing world of it
Softchoice the changing world of itNadia Tsinokas
 
Rick Mutsaers Informatica
Rick Mutsaers InformaticaRick Mutsaers Informatica
Rick Mutsaers InformaticaBigDataExpo
 
Herding Cats in the Digital World
Herding Cats in the Digital WorldHerding Cats in the Digital World
Herding Cats in the Digital WorldCapgemini
 
Yobitel Communicaitons Corporate Brochure
Yobitel Communicaitons Corporate BrochureYobitel Communicaitons Corporate Brochure
Yobitel Communicaitons Corporate BrochureAbishek Vimala Raju
 
Digital Out of Home Multicanal, ¿Futuro… o Presente?
Digital Out of Home Multicanal, ¿Futuro… o Presente?Digital Out of Home Multicanal, ¿Futuro… o Presente?
Digital Out of Home Multicanal, ¿Futuro… o Presente?crambovisuales
 
Lead to Cash: The Value of Big Data and Analytics for Telco
Lead to Cash: The Value of Big Data and Analytics for TelcoLead to Cash: The Value of Big Data and Analytics for Telco
Lead to Cash: The Value of Big Data and Analytics for TelcoSam Thomsett
 
IDC- BMC Digital Enterprise Management Powers Digital Business Transformation
IDC- BMC Digital Enterprise Management Powers Digital Business TransformationIDC- BMC Digital Enterprise Management Powers Digital Business Transformation
IDC- BMC Digital Enterprise Management Powers Digital Business TransformationEric Lightfoot
 
Subscribed 2015: The Explosion of Smart Connected Things
Subscribed 2015: The Explosion of Smart Connected ThingsSubscribed 2015: The Explosion of Smart Connected Things
Subscribed 2015: The Explosion of Smart Connected ThingsZuora, Inc.
 
Top Digital Transformation Trends (2020)
Top Digital Transformation Trends (2020)Top Digital Transformation Trends (2020)
Top Digital Transformation Trends (2020)Cygnet Infotech
 
Next Generation Data Center - IT Transformation
Next Generation Data Center - IT TransformationNext Generation Data Center - IT Transformation
Next Generation Data Center - IT TransformationDamian Hamilton
 

Similar a Netweb flytxt-big-data-case-study (20)

How big data analytics can optimize the telecom sector
How big data analytics can optimize the telecom sector How big data analytics can optimize the telecom sector
How big data analytics can optimize the telecom sector
 
Rebooting IT Infrastructure for the Digital Age
Rebooting IT Infrastructure for the Digital AgeRebooting IT Infrastructure for the Digital Age
Rebooting IT Infrastructure for the Digital Age
 
Monetizing the Internet of Things: Creating a Connected Customer Experience
Monetizing the Internet of Things: Creating a Connected Customer ExperienceMonetizing the Internet of Things: Creating a Connected Customer Experience
Monetizing the Internet of Things: Creating a Connected Customer Experience
 
Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...
Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...
Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...
 
HP Communications and Media | Solutions IoT Platform
HP Communications and Media | Solutions IoT Platform HP Communications and Media | Solutions IoT Platform
HP Communications and Media | Solutions IoT Platform
 
Offshore Projects
Offshore ProjectsOffshore Projects
Offshore Projects
 
Microsoft's Approach to IoT
Microsoft's Approach to IoT Microsoft's Approach to IoT
Microsoft's Approach to IoT
 
Century link custom_final_v4
Century link  custom_final_v4Century link  custom_final_v4
Century link custom_final_v4
 
Softchoice the changing world of it
Softchoice   the changing world of itSoftchoice   the changing world of it
Softchoice the changing world of it
 
Big data in telecom
Big data in telecomBig data in telecom
Big data in telecom
 
Flip IT Brochure 2015
Flip IT Brochure 2015Flip IT Brochure 2015
Flip IT Brochure 2015
 
Rick Mutsaers Informatica
Rick Mutsaers InformaticaRick Mutsaers Informatica
Rick Mutsaers Informatica
 
Herding Cats in the Digital World
Herding Cats in the Digital WorldHerding Cats in the Digital World
Herding Cats in the Digital World
 
Yobitel Communicaitons Corporate Brochure
Yobitel Communicaitons Corporate BrochureYobitel Communicaitons Corporate Brochure
Yobitel Communicaitons Corporate Brochure
 
Digital Out of Home Multicanal, ¿Futuro… o Presente?
Digital Out of Home Multicanal, ¿Futuro… o Presente?Digital Out of Home Multicanal, ¿Futuro… o Presente?
Digital Out of Home Multicanal, ¿Futuro… o Presente?
 
Lead to Cash: The Value of Big Data and Analytics for Telco
Lead to Cash: The Value of Big Data and Analytics for TelcoLead to Cash: The Value of Big Data and Analytics for Telco
Lead to Cash: The Value of Big Data and Analytics for Telco
 
IDC- BMC Digital Enterprise Management Powers Digital Business Transformation
IDC- BMC Digital Enterprise Management Powers Digital Business TransformationIDC- BMC Digital Enterprise Management Powers Digital Business Transformation
IDC- BMC Digital Enterprise Management Powers Digital Business Transformation
 
Subscribed 2015: The Explosion of Smart Connected Things
Subscribed 2015: The Explosion of Smart Connected ThingsSubscribed 2015: The Explosion of Smart Connected Things
Subscribed 2015: The Explosion of Smart Connected Things
 
Top Digital Transformation Trends (2020)
Top Digital Transformation Trends (2020)Top Digital Transformation Trends (2020)
Top Digital Transformation Trends (2020)
 
Next Generation Data Center - IT Transformation
Next Generation Data Center - IT TransformationNext Generation Data Center - IT Transformation
Next Generation Data Center - IT Transformation
 

Más de IntelAPAC

Intel apj cloud big data summit sdi press briefing - panhorst
Intel apj cloud  big data summit   sdi press briefing - panhorstIntel apj cloud  big data summit   sdi press briefing - panhorst
Intel apj cloud big data summit sdi press briefing - panhorstIntelAPAC
 
Day 2 aziz apj aziz_big_datakeynote_press
Day 2 aziz apj aziz_big_datakeynote_pressDay 2 aziz apj aziz_big_datakeynote_press
Day 2 aziz apj aziz_big_datakeynote_pressIntelAPAC
 
2 pc enterprise summit cronin newfinal aug 18
2 pc enterprise summit cronin newfinal aug 182 pc enterprise summit cronin newfinal aug 18
2 pc enterprise summit cronin newfinal aug 18IntelAPAC
 
5 Cronin Steen - IOT Smart Cities
5 Cronin Steen - IOT Smart Cities5 Cronin Steen - IOT Smart Cities
5 Cronin Steen - IOT Smart CitiesIntelAPAC
 
Gab Genai Cloudera - Going Beyond Traditional Analytic
Gab Genai Cloudera - Going Beyond Traditional Analytic Gab Genai Cloudera - Going Beyond Traditional Analytic
Gab Genai Cloudera - Going Beyond Traditional Analytic IntelAPAC
 
1 RK Hiremane
1 RK Hiremane1 RK Hiremane
1 RK HiremaneIntelAPAC
 
Intel APJ Enterprise Day - Synopses of Demos at Intel Collaboration Center
Intel APJ Enterprise Day - Synopses of Demos at Intel Collaboration CenterIntel APJ Enterprise Day - Synopses of Demos at Intel Collaboration Center
Intel APJ Enterprise Day - Synopses of Demos at Intel Collaboration CenterIntelAPAC
 
Intel APJ Enterprise Day - Synopses of Demos at Intel Collaboration Center
Intel APJ Enterprise Day - Synopses of Demos at Intel Collaboration CenterIntel APJ Enterprise Day - Synopses of Demos at Intel Collaboration Center
Intel APJ Enterprise Day - Synopses of Demos at Intel Collaboration CenterIntelAPAC
 
Intel APJ Enterprise Day - Intel puts Automotive Innovation into High Gear
Intel APJ Enterprise Day - Intel puts Automotive Innovation into High GearIntel APJ Enterprise Day - Intel puts Automotive Innovation into High Gear
Intel APJ Enterprise Day - Intel puts Automotive Innovation into High GearIntelAPAC
 
Intel APJ Enterprise Day - Intro to Intel Collaboration Centre
Intel APJ Enterprise Day - Intro to Intel Collaboration CentreIntel APJ Enterprise Day - Intro to Intel Collaboration Centre
Intel APJ Enterprise Day - Intro to Intel Collaboration CentreIntelAPAC
 
Intel APJ Enterprise Day - Strategic IT, A New Way of Business
Intel APJ Enterprise Day - Strategic IT, A New Way of Business Intel APJ Enterprise Day - Strategic IT, A New Way of Business
Intel APJ Enterprise Day - Strategic IT, A New Way of Business IntelAPAC
 
Intel APJ Enterprise Day - Keynote by RK Hiremane
Intel APJ Enterprise Day - Keynote by RK HiremaneIntel APJ Enterprise Day - Keynote by RK Hiremane
Intel APJ Enterprise Day - Keynote by RK HiremaneIntelAPAC
 
Intel APJ Enterprise Day - Introduction to Intel Kabushiki Kaisha
Intel APJ Enterprise Day - Introduction to Intel Kabushiki KaishaIntel APJ Enterprise Day - Introduction to Intel Kabushiki Kaisha
Intel APJ Enterprise Day - Introduction to Intel Kabushiki KaishaIntelAPAC
 
RedHat - Intel Big Data & Cloud Summit 2013
RedHat - Intel Big Data & Cloud Summit 2013RedHat - Intel Big Data & Cloud Summit 2013
RedHat - Intel Big Data & Cloud Summit 2013IntelAPAC
 
Greg Brown - Intel Big Data & Cloud Summit 2013
Greg Brown - Intel Big Data & Cloud Summit 2013Greg Brown - Intel Big Data & Cloud Summit 2013
Greg Brown - Intel Big Data & Cloud Summit 2013IntelAPAC
 
TWSE - Intel Big Data & Cloud Summit 2013
TWSE - Intel Big Data & Cloud Summit 2013TWSE - Intel Big Data & Cloud Summit 2013
TWSE - Intel Big Data & Cloud Summit 2013IntelAPAC
 
Lynn Comp - Intel Big Data & Cloud Summit 2013 (2)
Lynn Comp - Intel Big Data & Cloud Summit 2013 (2)Lynn Comp - Intel Big Data & Cloud Summit 2013 (2)
Lynn Comp - Intel Big Data & Cloud Summit 2013 (2)IntelAPAC
 
Lynn Comp - Big Data & Cloud Summit 2013
Lynn Comp - Big Data & Cloud Summit 2013Lynn Comp - Big Data & Cloud Summit 2013
Lynn Comp - Big Data & Cloud Summit 2013IntelAPAC
 
Girish Juneja - Intel Big Data & Cloud Summit 2013
Girish Juneja - Intel Big Data & Cloud Summit 2013Girish Juneja - Intel Big Data & Cloud Summit 2013
Girish Juneja - Intel Big Data & Cloud Summit 2013IntelAPAC
 
Ron Kasabian - Intel Big Data & Cloud Summit 2013
Ron Kasabian - Intel Big Data & Cloud Summit 2013Ron Kasabian - Intel Big Data & Cloud Summit 2013
Ron Kasabian - Intel Big Data & Cloud Summit 2013IntelAPAC
 

Más de IntelAPAC (20)

Intel apj cloud big data summit sdi press briefing - panhorst
Intel apj cloud  big data summit   sdi press briefing - panhorstIntel apj cloud  big data summit   sdi press briefing - panhorst
Intel apj cloud big data summit sdi press briefing - panhorst
 
Day 2 aziz apj aziz_big_datakeynote_press
Day 2 aziz apj aziz_big_datakeynote_pressDay 2 aziz apj aziz_big_datakeynote_press
Day 2 aziz apj aziz_big_datakeynote_press
 
2 pc enterprise summit cronin newfinal aug 18
2 pc enterprise summit cronin newfinal aug 182 pc enterprise summit cronin newfinal aug 18
2 pc enterprise summit cronin newfinal aug 18
 
5 Cronin Steen - IOT Smart Cities
5 Cronin Steen - IOT Smart Cities5 Cronin Steen - IOT Smart Cities
5 Cronin Steen - IOT Smart Cities
 
Gab Genai Cloudera - Going Beyond Traditional Analytic
Gab Genai Cloudera - Going Beyond Traditional Analytic Gab Genai Cloudera - Going Beyond Traditional Analytic
Gab Genai Cloudera - Going Beyond Traditional Analytic
 
1 RK Hiremane
1 RK Hiremane1 RK Hiremane
1 RK Hiremane
 
Intel APJ Enterprise Day - Synopses of Demos at Intel Collaboration Center
Intel APJ Enterprise Day - Synopses of Demos at Intel Collaboration CenterIntel APJ Enterprise Day - Synopses of Demos at Intel Collaboration Center
Intel APJ Enterprise Day - Synopses of Demos at Intel Collaboration Center
 
Intel APJ Enterprise Day - Synopses of Demos at Intel Collaboration Center
Intel APJ Enterprise Day - Synopses of Demos at Intel Collaboration CenterIntel APJ Enterprise Day - Synopses of Demos at Intel Collaboration Center
Intel APJ Enterprise Day - Synopses of Demos at Intel Collaboration Center
 
Intel APJ Enterprise Day - Intel puts Automotive Innovation into High Gear
Intel APJ Enterprise Day - Intel puts Automotive Innovation into High GearIntel APJ Enterprise Day - Intel puts Automotive Innovation into High Gear
Intel APJ Enterprise Day - Intel puts Automotive Innovation into High Gear
 
Intel APJ Enterprise Day - Intro to Intel Collaboration Centre
Intel APJ Enterprise Day - Intro to Intel Collaboration CentreIntel APJ Enterprise Day - Intro to Intel Collaboration Centre
Intel APJ Enterprise Day - Intro to Intel Collaboration Centre
 
Intel APJ Enterprise Day - Strategic IT, A New Way of Business
Intel APJ Enterprise Day - Strategic IT, A New Way of Business Intel APJ Enterprise Day - Strategic IT, A New Way of Business
Intel APJ Enterprise Day - Strategic IT, A New Way of Business
 
Intel APJ Enterprise Day - Keynote by RK Hiremane
Intel APJ Enterprise Day - Keynote by RK HiremaneIntel APJ Enterprise Day - Keynote by RK Hiremane
Intel APJ Enterprise Day - Keynote by RK Hiremane
 
Intel APJ Enterprise Day - Introduction to Intel Kabushiki Kaisha
Intel APJ Enterprise Day - Introduction to Intel Kabushiki KaishaIntel APJ Enterprise Day - Introduction to Intel Kabushiki Kaisha
Intel APJ Enterprise Day - Introduction to Intel Kabushiki Kaisha
 
RedHat - Intel Big Data & Cloud Summit 2013
RedHat - Intel Big Data & Cloud Summit 2013RedHat - Intel Big Data & Cloud Summit 2013
RedHat - Intel Big Data & Cloud Summit 2013
 
Greg Brown - Intel Big Data & Cloud Summit 2013
Greg Brown - Intel Big Data & Cloud Summit 2013Greg Brown - Intel Big Data & Cloud Summit 2013
Greg Brown - Intel Big Data & Cloud Summit 2013
 
TWSE - Intel Big Data & Cloud Summit 2013
TWSE - Intel Big Data & Cloud Summit 2013TWSE - Intel Big Data & Cloud Summit 2013
TWSE - Intel Big Data & Cloud Summit 2013
 
Lynn Comp - Intel Big Data & Cloud Summit 2013 (2)
Lynn Comp - Intel Big Data & Cloud Summit 2013 (2)Lynn Comp - Intel Big Data & Cloud Summit 2013 (2)
Lynn Comp - Intel Big Data & Cloud Summit 2013 (2)
 
Lynn Comp - Big Data & Cloud Summit 2013
Lynn Comp - Big Data & Cloud Summit 2013Lynn Comp - Big Data & Cloud Summit 2013
Lynn Comp - Big Data & Cloud Summit 2013
 
Girish Juneja - Intel Big Data & Cloud Summit 2013
Girish Juneja - Intel Big Data & Cloud Summit 2013Girish Juneja - Intel Big Data & Cloud Summit 2013
Girish Juneja - Intel Big Data & Cloud Summit 2013
 
Ron Kasabian - Intel Big Data & Cloud Summit 2013
Ron Kasabian - Intel Big Data & Cloud Summit 2013Ron Kasabian - Intel Big Data & Cloud Summit 2013
Ron Kasabian - Intel Big Data & Cloud Summit 2013
 

Último

Role of Consumer Insights in business transformation
Role of Consumer Insights in business transformationRole of Consumer Insights in business transformation
Role of Consumer Insights in business transformationAnnie Melnic
 
why-transparency-and-traceability-are-essential-for-sustainable-supply-chains...
why-transparency-and-traceability-are-essential-for-sustainable-supply-chains...why-transparency-and-traceability-are-essential-for-sustainable-supply-chains...
why-transparency-and-traceability-are-essential-for-sustainable-supply-chains...Jack Cole
 
Predictive Analysis - Using Insight-informed Data to Plan Inventory in Next 6...
Predictive Analysis - Using Insight-informed Data to Plan Inventory in Next 6...Predictive Analysis - Using Insight-informed Data to Plan Inventory in Next 6...
Predictive Analysis - Using Insight-informed Data to Plan Inventory in Next 6...ThinkInnovation
 
6 Tips for Interpretable Topic Models _ by Nicha Ruchirawat _ Towards Data Sc...
6 Tips for Interpretable Topic Models _ by Nicha Ruchirawat _ Towards Data Sc...6 Tips for Interpretable Topic Models _ by Nicha Ruchirawat _ Towards Data Sc...
6 Tips for Interpretable Topic Models _ by Nicha Ruchirawat _ Towards Data Sc...Dr Arash Najmaei ( Phd., MBA, BSc)
 
IBEF report on the Insurance market in India
IBEF report on the Insurance market in IndiaIBEF report on the Insurance market in India
IBEF report on the Insurance market in IndiaManalVerma4
 
Presentation of project of business person who are success
Presentation of project of business person who are successPresentation of project of business person who are success
Presentation of project of business person who are successPratikSingh115843
 
Decision Making Under Uncertainty - Is It Better Off Joining a Partnership or...
Decision Making Under Uncertainty - Is It Better Off Joining a Partnership or...Decision Making Under Uncertainty - Is It Better Off Joining a Partnership or...
Decision Making Under Uncertainty - Is It Better Off Joining a Partnership or...ThinkInnovation
 
Decoding Movie Sentiments: Analyzing Reviews with Data Analysis model
Decoding Movie Sentiments: Analyzing Reviews with Data Analysis modelDecoding Movie Sentiments: Analyzing Reviews with Data Analysis model
Decoding Movie Sentiments: Analyzing Reviews with Data Analysis modelBoston Institute of Analytics
 
DATA ANALYSIS using various data sets like shoping data set etc
DATA ANALYSIS using various data sets like shoping data set etcDATA ANALYSIS using various data sets like shoping data set etc
DATA ANALYSIS using various data sets like shoping data set etclalithasri22
 
Digital Indonesia Report 2024 by We Are Social .pdf
Digital Indonesia Report 2024 by We Are Social .pdfDigital Indonesia Report 2024 by We Are Social .pdf
Digital Indonesia Report 2024 by We Are Social .pdfNicoChristianSunaryo
 
Bank Loan Approval Analysis: A Comprehensive Data Analysis Project
Bank Loan Approval Analysis: A Comprehensive Data Analysis ProjectBank Loan Approval Analysis: A Comprehensive Data Analysis Project
Bank Loan Approval Analysis: A Comprehensive Data Analysis ProjectBoston Institute of Analytics
 
Statistics For Management by Richard I. Levin 8ed.pdf
Statistics For Management by Richard I. Levin 8ed.pdfStatistics For Management by Richard I. Levin 8ed.pdf
Statistics For Management by Richard I. Levin 8ed.pdfnikeshsingh56
 
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...Boston Institute of Analytics
 

Último (16)

Data Analysis Project: Stroke Prediction
Data Analysis Project: Stroke PredictionData Analysis Project: Stroke Prediction
Data Analysis Project: Stroke Prediction
 
Role of Consumer Insights in business transformation
Role of Consumer Insights in business transformationRole of Consumer Insights in business transformation
Role of Consumer Insights in business transformation
 
why-transparency-and-traceability-are-essential-for-sustainable-supply-chains...
why-transparency-and-traceability-are-essential-for-sustainable-supply-chains...why-transparency-and-traceability-are-essential-for-sustainable-supply-chains...
why-transparency-and-traceability-are-essential-for-sustainable-supply-chains...
 
Predictive Analysis - Using Insight-informed Data to Plan Inventory in Next 6...
Predictive Analysis - Using Insight-informed Data to Plan Inventory in Next 6...Predictive Analysis - Using Insight-informed Data to Plan Inventory in Next 6...
Predictive Analysis - Using Insight-informed Data to Plan Inventory in Next 6...
 
6 Tips for Interpretable Topic Models _ by Nicha Ruchirawat _ Towards Data Sc...
6 Tips for Interpretable Topic Models _ by Nicha Ruchirawat _ Towards Data Sc...6 Tips for Interpretable Topic Models _ by Nicha Ruchirawat _ Towards Data Sc...
6 Tips for Interpretable Topic Models _ by Nicha Ruchirawat _ Towards Data Sc...
 
IBEF report on the Insurance market in India
IBEF report on the Insurance market in IndiaIBEF report on the Insurance market in India
IBEF report on the Insurance market in India
 
2023 Survey Shows Dip in High School E-Cigarette Use
2023 Survey Shows Dip in High School E-Cigarette Use2023 Survey Shows Dip in High School E-Cigarette Use
2023 Survey Shows Dip in High School E-Cigarette Use
 
Insurance Churn Prediction Data Analysis Project
Insurance Churn Prediction Data Analysis ProjectInsurance Churn Prediction Data Analysis Project
Insurance Churn Prediction Data Analysis Project
 
Presentation of project of business person who are success
Presentation of project of business person who are successPresentation of project of business person who are success
Presentation of project of business person who are success
 
Decision Making Under Uncertainty - Is It Better Off Joining a Partnership or...
Decision Making Under Uncertainty - Is It Better Off Joining a Partnership or...Decision Making Under Uncertainty - Is It Better Off Joining a Partnership or...
Decision Making Under Uncertainty - Is It Better Off Joining a Partnership or...
 
Decoding Movie Sentiments: Analyzing Reviews with Data Analysis model
Decoding Movie Sentiments: Analyzing Reviews with Data Analysis modelDecoding Movie Sentiments: Analyzing Reviews with Data Analysis model
Decoding Movie Sentiments: Analyzing Reviews with Data Analysis model
 
DATA ANALYSIS using various data sets like shoping data set etc
DATA ANALYSIS using various data sets like shoping data set etcDATA ANALYSIS using various data sets like shoping data set etc
DATA ANALYSIS using various data sets like shoping data set etc
 
Digital Indonesia Report 2024 by We Are Social .pdf
Digital Indonesia Report 2024 by We Are Social .pdfDigital Indonesia Report 2024 by We Are Social .pdf
Digital Indonesia Report 2024 by We Are Social .pdf
 
Bank Loan Approval Analysis: A Comprehensive Data Analysis Project
Bank Loan Approval Analysis: A Comprehensive Data Analysis ProjectBank Loan Approval Analysis: A Comprehensive Data Analysis Project
Bank Loan Approval Analysis: A Comprehensive Data Analysis Project
 
Statistics For Management by Richard I. Levin 8ed.pdf
Statistics For Management by Richard I. Levin 8ed.pdfStatistics For Management by Richard I. Levin 8ed.pdf
Statistics For Management by Richard I. Levin 8ed.pdf
 
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...
 

Netweb flytxt-big-data-case-study

  • 1. Intel has taken a leadership role to bring Hadoop* to enterprises, enabling scalable, cost-effective analytical solutions in the market. Our ecosystem partners like Flytxt are a great example of how we are accelerating the solution for faster adoption across enterprises. CASE STUDY Intel® Xeon® Processor E5 Product Family Intel® Server Systems Intel® Ethernet 10 Gigabit Adapters Big Data Analytics Telecommunications Transforming Data Insights into Business Value with Big Data Analytics Intel partners with Flytxt and Netweb Technologies to deliver one of the largest Big Data Analytics deployments for a leading telecom service provider in India The telecommunications industry is a melting pot of data. The steady growth in the number of users coupled with the advent of multiple smartphones and their complex features and abilities has led to the existence of voluminous and widely variable data, all conceived at high velocity and scattered across departments and business units. One of India’s leading telecom service providers sought to establish market leadership and deliver customer satisfaction by providing personalized and contextually relevant offers to their customers in real-time. Flytxt Analytics platform leveraging high performance Intel® based servers from Netweb Technologies running Hadoop* clusters brought an entirely new dimension in the way the telecom service provider could utilize the full power of data available with them to enhance customer experience and increase revenue. Challenges • More real time than near-real-time: Obtaining insights in real time, at the velocity in which data is generated, and then using these insights to take decisions in real time, was a major challenge for the telecom service provider. The latency between the subscriber initiated event to insight and then to action needed to be minimized greatly. Legacy systems struggled to meet this requirement and hence the telecom service provider could not respond to the customers’ needs within the window of relevance. • More relevant than categorized: The telecom service provider generated huge volumes of subscriber data at various sources. Up to 4 terabytes of data were generated in a day, and these data had to be analysed for taking instant decisions. Processing such voluminous and varied data to generate insight for decision making presented a daunting challenge, in terms of technology and the time involved. This in turn meant that offers were not always relevant to subscribers and specific marketing needs like churn prevention and margin optimization were not met. • Closing the loop - gratification in real time: The telecom service provider had disjointed systems for data processing, campaign execution and rewards gratification. This meant a long delay between target generation to campaign execution to call-to-action to gratification. RadhaKrishna Hiremane Regional Product Marketing Manager, Intel Corporation
  • 2. Why Big Data Matters Data is exploding at an astounding rate. Billions of connected devices - ranging from PCs and smartphones to sensor devices such as RFID readers and traffic cams - generate this flood of complex structured and unstructured data. Unstructured data is heterogeneous and variable in nature, and comes in many formats including text, document, image, video, and more. A critical component in the telecommunications industry, unstructured data is growing faster than structured data. As a new, relatively untapped source of insight, unstructured data analytics can reveal important interrelationships that were previously difficult or impossible to determine. Big Data Analytics is a technology-enabled strategy for gaining richer, deeper, and more accurate insights into customers and the business, and ultimately gaining competitive advantage. By processing a steady stream of real-time data, organizations can make time-sensitive decisions faster than ever before, monitor emerging trends, course-correct rapidly, and jump on new business opportunities. Flytxt is a leading provider of Big Data Analytics powered solutions with a focus on enabling mobile operators to derive measurable economic value from subscriber data. The company offers customer experience, revenue management and insight monetization solutions as well as consultancy services. Flytxt solutions are deployed with leading operators across APAC and EMEA, serving more than 500 million subscribers; generating around $350 million incremental revenue for operators till now. Flytxt has won many industry awards and recognitions like Frost & Sullivan ICT Awards 2014 for Product Innovation Leadership in Marketing Analytics, Gartner Cool Vendor, NASSCOM* League of 10, CEM Excellence* Award for Middle East, Aegis* Graham Bell Award for Innovation in Mobile Advertising, BID* International Quality Award, Red Herring* Asia 100 and IEEE Cloud Computing Challenge. Flytxt has its headquarters in Netherlands, corporate office in Dubai and global delivery centres in Trivandrum and Mumbai. Flytxt also has presence in London, Kuala Lumpur, Lagos, Nairobi, Dhaka and New Delhi. Spotlight on Flytxt Solutions • Flytxt: NEON, a Big Data Analytics Platform and Revenue Enhancer Application - based on an Intel® Architecture-based real-time, fully integrated Hadoop* platform, powers the client’s real-time contextual trigger-driven marketing campaigns. • Netweb Technologies: Flytxt’s Big Data Analytics Solution was deployed on highly resource-intensive Netweb's Tyrone servers powered by Intel® Xeon® processors. • Intel: Hadoop* clusters based on Intel® Xeon® E5 processors and Intel® Ethernet 10 Gigabit Converged Network Adapters. Impact • Enhanced Customer Experience: Response time to customer events reduced from 24 hours to 30 minutes. • High Conversion Rate: 5.9% incremental conversions of subscribers month-on-month. • Maximized Migration to Higher Value Base: 55% of the customers moved to higher-value recharge segments. • Rapid Growth in ARPU: Target customer base clocked a net ARPU growth of 18.9%. This is a first of its kind deployment of this scale in the telecom world, where a Big Data Analytics solution enabled a telecom service provider to bring together the power of ‘real- time context’ and ‘in-depth subscriber intelligence’ to send personalized offers to their millions of subscribers in real time. Prateek Kapadia Chief Technology Officer, Flytxt
  • 3. current legacy system, which was struggling with the huge load of data, by implementing a cutting-edge real-time marketing system leveraging on the advantages of Big Data Analytics to enhance the customer experience and drive incremental revenue. Integrated Big Data Analytics for Big Success Flytxt, a leading provider of Big Data Analytics powered solutions, empowered their client to transform the way they provide customer satisfaction, positively impacting their business in a huge way. Flytxt’s multi-dimensional integrated Analytics framework addressed the challenges and complexities of new age information asset processing and accelerated sustained economic value generation from data for the client. Flytxt Integrated Analytics framework enabled the telecom service provider do analytics faster, deeper, and in a more efficient and objective-driven way from a single easy to use interface, reducing the ‘data to decision’ time significantly. Riding the Big Data Wave. Addressing Big Challenges. The client, one of India’s leading telecom service providers, in their constant endeavour to stay ahead of the competition in the highly volatile and competitive Indian market was looking to ramp up their customer service platform, enhance the average revenue per user (ARPU) and reduce customer churn considerably. And with tight regulatory intervention and number portability options further intensifying the price competition in the market, the client stood in the cusp of great challenges and opportunities. The Big Data challenges facing the client, who has a subscriber base close to 200 million, were gargantuan and can be gauged from the intimidating number of data being handled regularly including 3.5TB of data and 4 billion events per day, 200 million subscribers, 20,000+ data jobs, 530 million triggers, 7,000+ broadcast rules, 21,000+ tracking rules, and 14,000 tags/KPIs per subscriber. The client was looking to refresh their Netweb is a leading provider of High Performance Computing, Big Data and Storage solutions, and has been a trusted name for providing best-in-class solutions for almost two decades. Netweb Technologies has seven offices globally in India, Singapore, and South East Asia. Netweb Technologies provides best-in-class products that deliver solutions combining speed, reliability, and scalability with energy efficiency to deliver maximum ROI at lower TCO. Netweb Technologies is widely recognized for its implementation of the PARAM Yuva II System, India’s fastest hybrid supercomputer till date and is also well-known for its out of the box, totally customizable solutions. Netweb Technologies provides custom configured solutions for HPC environments and related applications for verticals that span across Pharma, Manufacturing, Oil and Gas, Animation R&D, Earth Sciences, Defense, Science and Technology in India and other developing economies around the world. Spotlight on Netweb Technologies
  • 4. Hadoop* server clusters powered by Intel® Xeon® processors can enable near-real-time discoveries. Driving the Big Data Revolution. Making a Big Difference. Leveraging on their deep expertise in Big Data Analytics, Flytxt delivered an intelligent and powerful Analytics solution to capture the behavioural pattern of existing subscribers and provide relevant offers and deals tailored to the customer’s need. With its Integrated, Multi-Dimensional Analytics Framework, Flytxt enabled the following capabilities for the telecom service provider: • Predictive Analytics: Predict the propensity to churn, winback, purchase, etc. • Prescriptive Analytics: Suggest best channel, offer, price affinity based on given business objective/context • Heuristic Analytics: Behavioural customer segmentation based on marketer/expert/SME hypothesis and experience This was made possible through the deployment of Flytxt’s Revenue Enhancer Application, a game-changing solution powered by NEON, which is a Big Data Analytics powered revenue and customer experience management platform for telecom service providers. NEON’s rich set of applications enabled the telecom service provider’s marketing team to run a wide variety of real-time trigger-based campaigns in areas like loyalty and retention, churn management, usage and recharge stimulation, VAS marketing and product up-selling/ cross-selling. The following triggers were utilized by the telecom service provider to maximize their customers’ experience: • Recharge Trigger: Recharge for ‘ n’ denomination, ‘n’th recharge of the day etc. • Balance Trigger: Balance going below the threshold • OG Call (Voice): First/‘n’th minute call of the day • Local On-Net OG Call (Voice) • National Calling Outgoing (Voice) • International Calling Outgoing (Voice) • Roaming OG Call (Voice): Trigger on roaming • SMS Count: ‘n’th SMS • GPRS Usage, etc. Segment Product Rol Location Marketing programs Infrastructure Descriptive Exploratory Heuristic Predictive Prescriptive Fig. 2: Flytxt Integrated, Multi-Dimensional Analytics Framework
  • 5. With real-time marketing, Analytics driven decisions and actions were integrated into the business workflows in no time. This reduced the telecom service provider's response time to customer actions from days to seconds. Closed-loop workflow also allowed the marketers to perform experimentations quickly to iteratively improve marketing effectiveness. For example, it allowed the operator to run A/B testing to choose the best campaign, creative, time and channel for a given segment. Powering Big Data Analytics with Powerful Hardware Netweb Technologies, a leading provider of Server, Storage and HPC solutions, played a critical role in enabling the solution and was a key driving force behind the daunting setup of a solution of this scale. The powerful NEON platform, which powers Flytxt’s intelligent solution, runs on Intel® Xeon® processor E5 v2 product family based Tyrone* Servers. Netweb Technologies was responsible for the end-to-end deployment of the hardware platform, including installation and support. The NEON platform operates on top of an Intel® based Tyrone compute nodes running two Intel® Xeon® processors E5-2609 v2, and 10GbE networking was used to support the high-performance compute requirement. Netweb Technologies, famously known for creating India’s fastest and largest hybrid supercomputer - the PARAM Yuva II System - ensured timely delivery, smooth setup, and 24x7 support and service, leveraging on their supercomputing expertise. Making Big Data Analytics Real Intel® Xeon® Processor-based Hadoop* server clusters with 10 Gigabit Intel® Ethernet Solutions acted as the main engine behind Flytxt’s cutting-edge Big Data solution for the client. Intel-based Hadoop* server clusters, which include a total of 130 servers split into 5 Hadoop* clusters and standalone servers, delivered the performance needed to handle large data sets with tightly integrated security features, scalability and management. Along with these, Intel provided irreplaceable practical guidance and training to aid in risk mitigation. The Hadoop* server clusters based on Intel® Xeon® E5 processors and Intel® Ethernet 10 Gigabit Converged Network Adapters delivered the performance required by the client for their intelligent insights need - helping to maximize the client’s potential, enhance customer experience and gain larger revenues. Delivering Maximum Business Value Flytxt’s Revenue Enhancer Application was integrated over 14,000 business KPIs. These were used to slide and dice the whole subscriber base into granular segments. Subscriber profile and behaviour analytics-driven micro-segmentation allowed the marketers to define personalized and relevant offers for different segments of subscribers through churn predictions (demographics, Call/SMS/Data Usage, recharges, propensity scores, personas). The Revenue Enhancer Application tracks billions of customer events to identify these pre-defined triggers, initiates sending of contextual offers automatically to subscribers, and also tracks for conversions and then passes on rewards depending on the event trigger identified. Riding on this unique method of maximizing the power of Big Data Analytics to deliver the best experience to customers, this Netweb Technologies provided trusted and reliable hardware platforms that Intel and Flytxt were looking for, to build a cutting-edge, next-gen solution that meets the client’s highly-complex and resource-intensive Big Data requirement.” Sanjay Lodha Chief Executive Officer, Netweb Technologies
  • 6. Conclusion - Collaborating to Deliver a Best-in-Class Solution The perfect collaboration of Intel, Flytxt and Netweb Technologies delivered a one-of-a-kind Data Analytics solution for the client. And for the first time ever in India, this solution helped a telecom service provider to bring together the power of ‘real-time context’ and ‘in-depth subscriber intelligence’ to send personalized offers to millions of subscribers. Further, this collaborative endeavour ensured that the highly-complex and resource-intensive Big Data Analytics implementation was delivered in a record time of just 3 months. To summarize, this solution helped deliver exceptional benefits in the form of increased revenue, enhanced customer experience, and maximized learning, in turn paving the way for a winning future. innovative solution delivered tangible business benefits for the client that include: • Huge reduction in response time to customer - from 24 hours to 30 minutes • 5.9% incremental conversions of subscribers month-on-month • 55% increase in upgrade to higher-value recharge segments • 18.9% ARPU growth rate of target customer base Find the solution that’s right for your organization. Contact your Intel representative, visit Intel’s Business Success Stories for IT Managers (www.intel.com/Itcasestudies) or explore the Intel.com IT Center (www.intel.com/itcenter). INFORMATION IN THIS DOCUMENT IS PROVIDED IN CONNECTION WITH INTEL® PRODUCTS. NO LICENSE, EXPRESS OR IMPLIED, BY ESTOPPEL OR OTHERWISE, TO ANY INTELLECTUAL PROPERTY RIGHTS IS GRANTED BY THIS DOCUMENT. EXCEPT AS PROVIDED IN INTEL’S TERMS AND CONDITIONS OF SALE FOR SUCH PRODUCTS, INTEL ASSUMES NO LIABILITY WHATSOEVER, AND INTEL DISCLAIMS ANY EXPRESS OR IMPLIED WARRANTY, RELATING TO SALE AND/OR USE OF INTEL PRODUCTS INCLUDING LIABILITY OR WARRANTIES RELATING TO FITNESS FOR A PARTICULAR PURPOSE, MERCHANTABILITY, OR INFRINGEMENT OF ANY PATENT, COPYRIGHT OR OTHER INTELLECTUAL PROPERTY RIGHT. UNLESS OTHERWISE AGREED IN WRITING BY INTEL, THE INTEL PRODUCTS ARE NOT DESIGNED NOR INTENDED FOR ANY APPLICATION IN WHICH THE FAILURE OF THE INTEL PRODUCT COULD CREATE A SITUATION WHERE PERSONAL INJURY OR DEATH MAY OCCUR. Intel may make changes to specifications and product descriptions at any time, without notice. Designers must not rely on the absence or characteristics of any features or instructions marked “reserved” or “undefined.” Intel reserves these for future definition and shall have no responsibility whatsoever for conflicts or incompatibilities arising from future changes to them. The information here is subject to change without notice. Do not finalize a design with this information. The products described in this document may contain design defects or errors known as errata which may cause the product to deviate from published specifications. Current characterized errata are available on request. Contact your local Intel sales office or your distributor to obtain the latest specifications and before placing your product order. Intel does not control or audit the design or implementation of third party benchmark data or Web sites referenced in this document. Intel encourages all of its customers to visit the referenced Web sites or others where similar performance benchmark data are reported and confirm whether the referenced benchmark data are accurate and reflect performance of systems available for purchase. This document and the information given are for the convenience of Intel’s customer base and are provided “AS IS” WITH NO WARRANTIES WHATSOEVER, EXPRESS OR IMPLIED, INCLUDING ANY IMPLIED WARRANTY OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, AND NON INFRINGEMENT OF INTELLECTUAL PROPERTY RIGHTS. Receipt or possession of this document does not grant any license to any of the intellectual property described, displayed, or contained herein. Intel® products are not intended for use in medical, lifesaving, life-sustaining, critical control, or safety systems, or in nuclear facility applications. Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark and MobileMark, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For more information go to www.intel.com/performance Copyright © 2014 Intel Corporation. All rights reserved. Intel, the Intel logo, Intel Inside, Look Inside, and Intel Xeon are trademarks of Intel Corporation in the U.S. and/or other countries. *Other names and brands may be claimed as the property of others.