Big Data overview SICS Software week, Sept 23-25 Cloud and Big Data Day Livio Ventura Big Data European Industry Leader for Telco, Energy and Utilities and Digital Media
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 2
some data on Data 3
Big Data and Analytics 4
Targets of Big Data efforts 5
Big Data sources and activities 6 http://www.ibmbigdatahub.com/infographic/where-does-big-data-come http://www.ibmbigdatahub.com/infographic/big-data-imperative-why-information-governance-must-be-addressed-now
Working with Big Data BI & Reporting Today Future 60-75% Prescriptive Shift Predictive 5-10% Descriptive 10-20% Shift 10-20% 5-10% Shift 60-75% Illustrative Percentage of Focus Related to Analytics 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. 7 http://www.ibmbigdatahub.com/smartsixteen
Bringing it all together 8 http://www.zurich.ibm.com/pdf/isl/infoportal/global_technology_outlook_2013.pdf
New Architecture to Leverage All Data and Analytics Streams Real-time Analytics Intelligence Analysis Data in Motion Data at Rest Information Ingestion and Operational Information Stream Processing Data Integration Master Data Video/Audio Network/Sensor Entity Analytics Predictive Landing Area, Analytics Zone and Archive Raw Data Structured Data Text Analytics Data Mining Entity Analytics Machine Learning Exploration, Integrated Warehouse, and Mart Zones Discovery Deep Reflection Operational Predictive Decision Management BI and Predictive Analytics Navigation and Discovery Data in Many Forms Information Governance, Security and Business Continuity 9
A revised Information Landscape 10 https://www.ibm.com/developerworks/community/blogs/5things/entry/5_things_to_know_about_the_new_information_architecture?lang=en
The 3 mega trends, their opportunities and challenges Mobile Social Changes of consumer demographics & globalization Opportunities Challenges Location-based data Social media data Value creation with real-time analytics Multi-channel access Traditional segmentation Privacy & Security issues 11
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 Invoice Issued Invoice Paid Contract Expiration Acquired new products Change contracts Entered new cell Customer is roaming Customer is at home New Top-Up 5 minutes left on pre-paid Changed Home Location Brand Reputation Customer Sentiment from Social network Broadband Saturation Congested Cells Streams of intelligence 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 MDM EDW/ADW Actionable insight Who is THIS customer and what do THEY want/need? What should I be OFFERINGspecific customers to improve individual ARPU / profitability? 12
IBM s Big Data Platform Analytics: LOB can model and test new ideas quickly through highperformance, appliance simplicity Personalized offers can be created based on all data Data: Provide a consistent, crosschannel view of customer interactions Reduce latency to seconds from days Include both structured & unstructured data (secure messaging, social media, etc) Integrate Data into a single goto data hub, allowing LOB to self-provision data for analytics BI / Reporting Analytic Applications Exploration / Visualization Visualization & Discovery Hadoop System Functional App Industry App Predictive Analytics IBM Big Data Platform Application Development Accelerators Stream Computing Information Integration & Governance Content Analytics Enterprise Marketing Management Data Warehouse Offer Manage ment: Personalize offers based on full customer data - structured and unstructured - in near real-time Social Participation Social Analytics Social Engagement Social Marketing Social Customer Anonymous Target Audience Targeted 13
Use cases Big Data exploration 14
Leading healthcare insurance provider call center enables 14,000 agents with single view of customer and product data Need Case Study link http://public.dhe.ibm.com/com mon/ssi/ecm/en/imc14799usen /IMC14799USEN.PDF Inefficient access to huge volumes of siloed customer 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-persecond speed Improved application performance to support daily operations and business users at 180 sites 15 15 Home
Global aerospace manufacturer empowers staff with access to critical information Need Link to the case study Http// need to get link from ibm.com 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 16 16 Home
Use cases Data Warehouse augmentation 17
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 18 18 Home
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) 19 19 Home
Use cases Operations Analysis 20
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 1/8 th Proactively address issues (e.g. dropped calls) impacting customer satisfaction. 21 21 Home
IBM CIO Lab Analytics team saving 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 22 22 Home
Use cases Enhanced 360 view of the customer 23
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 24 24 Home
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 25 25 Home
Use cases Security/Intelligence extension 26
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 27 27 Home
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 28 28 Home
Thank you email: l.ventura@it.ibm.com Mobile: +39 335 1988960 29 29