Big Data overview - Home | RISE SICS · PDF fileBig Data overview SICS Software week, Sept 23-25 Cloud and Big Data Day Livio Ventura Big Data European Industry Leader for Telco, Energy

© 2013 IBM Corporation

Big Data overview

SICS Software week, Sept 23-25Cloud and Big Data Day

Livio VenturaBig Data European Industry Leader for Telco, Energy and Utilities and Digital Media


2

Agenda

� some data on Data

� Big Data and Analytics

� Targets of Big Data efforts

� Big Data sources and activities

� Working with Big Data

� Bringing it all together in a New architecture

� New trends – challenges and opportunities

� IBM’s Big Data platform

� Use cases

�Big Data Exploration

�DWH Augmentation

�Operations Analysis

�Enhanced 360°view of customer

�Security/ntelligence extension


3

some data on Data


4

Big Data and Analytics


5

Targets of Big Data efforts


6

Big Data sources and activities

http://www.ibmbigdatahub.com/infographic/big-data-imperative-why-information-governance-must-be-addressed-now

http://www.ibmbigdatahub.com/infographic/where-does-big-data-come


7

Working with Big Data

Shift

Shift

Shift

55--10%10%

6060--75%75%

1010--20%20%

6060--75%75%

1010--20%20%

55--10%10%

Illustrative Percentage of Focus Related to “Analytics”

TodayToday FutureFuture

The pyramid needs to be "flipped", shifting the focus from accessing and aggregating data, to analyzing and acting upon

insights to make better decisions, drive smarter actions and enable personalized relationship with customers.

BI & Reporting

Prescriptive

Predictive

Descriptive

http://www.ibmbigdatahub.com/SmartSixteen


8

Bringing it all together

http://www.zurich.ibm.com/pdf/isl/infoportal/Global_Technology_Outlook_2013.pdf


9

New Architecture to Leverage All Data and Analytics

Data in

Motion

Data at

Rest

Data in

Many Forms

Information Ingestion and Operational Information

Decision Management

BI and Predictive Analytics

Navigation and Discovery

IntelligenceAnalysis

Landing Area,

Analytics Zone

and Archive

� Raw Data� Structured Data� Text Analytics� Data Mining� Entity Analytics� Machine Learning

Real-time

Analytics

� Video/Audio� Network/Sensor� Entity Analytics� Predictive Exploration,

Integrated Warehouse, and Mart Zones� Discovery

� Deep Reflection� Operational� Predictive

� Stream Processing � Data Integration � Master Data

Streams

Information Governance, Security and Business Continuity


10

A revised Information Landscape

https://www.ibm.com/developerworks/community/blogs/5things/entry/5_things_to_know_about_the_new_information_architecture?lang=en


11

Opportunities

Location-based data

Social media data

Value creation with real-time

analytics

The 3 mega trends, their opportunities and challenges

Mobile SocialChanges of consumer

demographics& globalization

Challenges

Multi-channel access

Traditional segmentation

Privacy & Security issues


12

How can CSPs leverage the vast amounts of data they collect

into usable and actionable insight for the Empowered Customer?

xDRs

Billing

CRM

Location

Account

Mgt

Internet

Network

Millions of events

per second

Dropped Calls

Outgoing International Calls

Call Duration

Extra Call

Contract Expiration

Entered new cell

New Top-Up

5 minutes left on pre-paid

Invoice Issued

Congested Cells

Invoice Paid

Acquired new products

Change contracts

Brand Reputation

Customer Sentiment

Customer is roaming

Customer is at home

3 dropped calls in 10 minutes

Customer is close to a store

Customer enters a shopping area

Invoice paid + ‘liked’ competitor

Smart phone browsing pattern

Customer is watching an OTT video

Streams of

intelligence

from Social network

Changed Home Location

Broadband Saturation

Who is THIS

customer and

what do THEY

want/need?

What should I be

OFFERING specific

customers to

improve

individual ARPU /

profitability?

Actionable

insight

MDM EDW/ADW


13

• Include both structured & unstructured data (secure messaging, social media, etc)

• Integrate Data into a single “go-to” data hub, allowing LOB to self-provision data for analytics

BI / Reporting

Exploration / Visualization

FunctionalApp

IndustryApp

Predictive Analytics

Content Analytics

Analytic Applications

IBM Big Data Platform

Information Integration & Governance

Stream Computing

• Reduce latency to seconds from days

Analytics:•LOB can model and test new ideas quickly through high-performance, appliance simplicity

•Personalized offers can be created based on all data

Offer Management: Personalize offers based on full customer data -structured and unstructured - in near real-time

Enterprise Marketing

Management

Data Warehouse

Data:•Provide a consistent, cross-channel view of customer interactions

HadoopSystem

Application Development

Visualization & Discovery

Accelerators

Enterprise Marketing

Management

IBM’s Big Data Platform

SocialParticipation

SocialAnalytics

SocialEngagement

SocialMarketing

Social Customer

Anon

ym

ous

Targ

et A

udie

nce

Targ

ete

d


14

Big Data exploration

Use cases


15

Case Study link

http://public.dhe.ibm.com/com

mon/ssi/ecm/en/imc14799usen

/IMC14799USEN.PDF

Leading healthcare insurance provider call center enables

14,000 agents with single view of customer and product data

Need

• Inefficient access to huge volumes of siloedcustomer and product data reduced agent productivity and increased average call handle time. Agents needed faster access to information

Benefits

• Improved productivity for 14,000 agents, saving an average of 3 seconds on call handle time, and millions of dollars annually

• Helped ensure 99.999 percent uptime at every location, delivering a commanding query-per-second speed

• Improved application performance to support daily operations and business users at 180 sites

1515Home


16

Link to the case study

Http// need to get link from

ibm.com

Global aerospace manufacturer empowers staff with access to critical information

Need

• Improve operational efficiencies by providing a unified search, discovery and navigation capability to provide fast access to relevant information across the enterprise

Benefits

• Placed 50 additional aircraft into service worldwide during the first year without a staffing increase

• Saved USD36 million/year in supporting the 24/7 aircraft-on-ground program

• Provided supply chain visibility to reduce cycle time, saving millions of dollars on critical parts deliveries

1616Home


17

Data Warehouse augmentation

Use cases


18

Colt Technology Services Group saves USD 1.9M annually through improved Netezza business intelligence

Need

• Gain a 360-view of the customer and eliminate manual processes to identify data from over 15 systems

Benefits

• USD 1.9M in annual savings

• 90% reduction in the time to complete ‘wildcard’ searches

• More than 95% reduction in the time to gather information

1818Home


19

Elisa Corporation - Adding millions of Euros in revenue

with improved information services

Need

• Elisa Corporation sought a deeper understanding of customer needs as they expanded its offerings. However, its existing information services platform could not support the data-intensive analytics required.

Benefits

• Provides a platform to drive millions of Euros in new revenue

• Supports 200 to 600 times faster data analysis and 100 times faster load performance

• Delivers direct yearly cost savings of almost EUR800,000 (USD1 million)

1919Home


20

Operations Analysis

Use cases


21

Asian telecommunications

company reduces billing costs and improves customer satisfaction.

Need

• Could not achieve real time billing which required handling billions of Call Detail Records (CDR) per day and de-duplication against 15 days worth of CDR data

Benefits

• Real-time mediation and analysis of 5B CDRs per day

• Data processing time reduced from 12 hrs to 1 min

• Hardware cost reduced to 1/8th

• Proactively address issues (e.g. dropped calls) impacting customer satisfaction.

2121Home


22

IBM CIO Lab Analytics teamsaving IBM employees thousands of hours each day

Need

• IBM needed a faster, more efficient application to process over 600K names in BluePages, its employee directory, which has over 500K daily queries with the average search session taking two minutes

Benefits

• Offers instantaneous response time, saving over a minute on average for each search session

• Saved thousands of hours to perform over 500,000 queries each day

• Achieved rapid user adoption, with 85,000 employees moving to the new application in first two weeks

2222Home


23

Enhanced 360°view of the customer

Use cases


24

Seattle Children’s simplifies analytics and gains insight for developing new care protocols

Need

• Faced with an ever-growing volume and variety of patient data, Seattle Children’s needed a consolidated platform to support healthcare analytics and reporting

Benefits

• Provides capabilities to analyze massive volumes of hospital and patient data to provide a holistic view and insight for improving care

• Eliminates manual processes and accelerates query times by 50 to 100 percent. One query that took 14 minutes completes in 9 seconds

• Reduced clinical report generation times from months to a single day, providing additional insights and improving staff efficiencies

2424Home


25

Telecom Italia implements PureData System for Analytics, improves overall customer experience

Need

• Despite collecting myriad data about its infrastructure, Telecom Italia could not proactively identify network infrastructure failure points or determine the root causes of service issues.

Benefits

• Boosts network performance insight by 100 percent by integrating multiple data sets in a single view

• Anticipates reduced customer churn by improving customer service levels and minimizing network failure

• Gains the ability to identify and respond to network issues proactively, before customers complain or drop service

2525Home


26

Security/Intelligence extension

Use cases


27

Brocade accelerates big data

analytics with IBM

Need

• As the volume, velocity and variety of data increases, companies are seeking powerful analytics platforms that help them explore big data.

Benefits

• Gives companies unparalleled insight to help identify and respond to customer needs in near real time

• Increases customer satisfaction and retention, and lowers customer churn for Communication industry clients

• Improves service levels across the network and enables optimization of IT resources

2727Home


28

TerraEchos uses streaming data technology to support covert intelligence and surveillance sensor systems

Need

• Deployed security surveillance system to detect, classify, locate, and track potential threats at highly sensitive national lab

Benefits

• Reduces time to capture and analyze 275MB of acoustic data from hours to one-fourteenth of a second

• Enables analysis of real-time data from different types of sensors and 1,024 individual channels to support extended perimeter security

• Enables a faster and more intelligent response to any threat

2828Home


2929

Thank you

eMail: [email protected]

Mobile: +39 335 1988960

Documents

Big Data overview - Home | RISE SICS · PDF fileBig Data overview SICS Software week, Sept 23-25 Cloud and Big Data Day Livio Ventura Big Data European Industry Leader for Telco, Energy