BIG DATA GREAT VALUE.

Transcription

1 BIG DATA GREAT VALUE. For those who want to be ahead of the field. T-Systems Big Data

2 ON THE LOOKOUT FOR NEW SOURCES OF VALUE CREATION. WHAT WILL DRIVE BUSINESSES IN FUTURE? From the black gold of the industrial i era to the new riches of the information age. Old sources dry up, while new ones emerge. The future belongs to the digital explorers T-Systems Big Data

3 BIG DATA: FAST-GROWING RAW MATERIAL DEPOSITS. RESOURCES ASKING TO BE DEVELOPED. 250 million s a day 5 million transactions ta sacto s per second Data volumes double every 18 months 24 Exabytes of data growth 85% per day unstructured data T-Systems Big Data

4 SOME KEY FIGURES. IN A 60-SECOND FLASH. 695,000 STATUS UPDATES 168 M S SENT 600+ NEW VIDEOS 11 MILLION INSTANT MESSENGERN CONNECTIONS 6, NEW PHOTOS 694,445 QUERIES 2,100 CHECK-INS 90,000+ TWEETS $ 219,000. REVENUE T-Systems Big Data

5 BIG DATA. FEATURES AND ADDED VALUE. ANALYTICS creates VALUE value comes from knowing more than the rest T-Systems Big Data

6 SEEING THE OPPORTUNITIES. RECOGNIZING NEW POTENTIALS. Complex simulations and trend analyses improve and accelerate product development and market maturity. Better insights into markets and customer needs enable tailormade products and services. Make decisions faster and more intelligently. Machines and sensor data optimize production processes. Traffic data and route planning saves costs and CO 2, and improves logistics and distribution. Projecting financial data results in better forecasts, indentifies fraud and risk mitigation. Opportunities for new business models. T-Systems Big Data

7 BIG DATA MINING: THE VALUE CREATION PIPELINE. Mining for data processing transporting storing refining implementing ANALYTICS-AS-A-SERVICE T-Systems Big Data

8 MINING FOR DATA. IN-HOUSE AND EXTERNALLY! Mining for data processing transporting storing refining implementing Until now: updated answers to structured databases and repetitive, with mostly standardized questions.!? Perfect: link up the two Today: New answers on the basis of unstructured data and creative, variable questions. Weather data Financial data Measurement data Laws, guidelines JPEG, PDF, etc. files Tweets, Likes & Co. Reports Traffic data Machine and sensor data And a lot more Health data T-Systems Big Data

9 PROCESSING DATA IN REAL TIME. WITH THE RIGHT TECHNOLOGIES AND PROCESS KNOW-HOW. Mining for data processing transporting storing refining implementing Business Problem Legacy BI High performance BI Hadoop Ecosystem Backward-looking analysis Quasi-real-time analysis Using data out of business applications i (In-Memory) Ui Using data out of business applications Forward-looking predictive analysis Questions defined d in the moment, using data from many sources Technology Solution SAP Business Objects IBM Cognos MicroStrategy costategy Structured Limited (2 3 TB in RAM) Selected Vendors Oracle Exadata SAP HANA Data Type/Scalability Structured Limited (1 PB in RAM) Cloudera Hadoop distribution Splunk (visualization) Structured or unstructured Quasi unlimited (20 30 PB) T-Systems Big Data

10 TAKING THE EXISTING WITH YOU. GENERATING MORE EFFICIENCY. Mining for data processing transporting storing refining implementing BUSINESS INTELLIGENCE TOOLS AND ANALYTICAL APPLICATIONS Reporting Dashboard Analyse OLAP Data & Text Mining Predictive Analytics Operational Intelligence Stuctured and unstructured data Complex event processing Data Warehouse Appliance Data Mart Cube Real-time data processing and analysis Data integration ETL Static data Flowing data Transactional OLTP DBMS Business Hadoop, Cloud Applications NoSQL, SaaS ERP, CRM, etc. Log-Daten EXISTING DATA SOURCES NEW DATA SOURCES T-Systems Big Data

11 SAVE DATA SECURELY. IN THE BIG DATA CLOUD FROM T-SYSTEMS. Mining for data processing transporting storing refining implementing 90 Twin Core Data Centers worldwide with 120,000m 000m² total surface area. Legacy BI, In-memory technology and Hadoop Ecosystem from one source 99.98% Strictest security standards and German data protection guidelines. availability guaranteed. T-Systems Big Data

12 REFINING DATA. ANSWERS TO QUESTIONS YOU DIDN T EVEN THINK TO ASK. Mining for data processing transporting storing refining implementing Automate semantic analyses Recognize patterns, meanings, correlations Data aascientists s wanted ANALYTICS creates VALUE value comes from knowing more than the rest. Preparing analyses and making them of universal use T-Systems Big Data

13 IMPLEMENTING BIG DATA TO GENERATE PROFIT. SELECTED USE CASES. CASES Mining for data processing transporting storing refining Intelligent News Discovery Automatic research of video, audio and online print files Semantic analyses and results visualization practically in real time Realtime Security Analytics Threats identified securely and blocked immediately Comprehensive monitoring of unlimited data volumes and types Connected Car: Traffic and Diagnostics Real-time reaction to vehicle conditions and traffic situations Increased customer loyalty due to individual service provision Secure product development Smarter Energy Management Optimized use of resources for all energy sources due to real-time forecasts Forecasts in real time Customer-specific prices implementing Efficient Fleet Management Driving tips in real time Competitive advantage p g thanks to cost reductions Lower fuel consumption and CO2 emissions Better planning of routes and cargo loads Campaign Analytics Real-time monitoring of marketing campaigns Consideration of all sources and formats Efficient campaign management T-Systems Big Data Smarter Procurement Transparency across all suppliers and prices Stronger negotiating position in purchasing Efficient cashflow management

14 T-SYSTEMS BIG DATA. THE ADVANTAGES AT A GLANCE. Mining for data processing transporting storing refining implementing Provision of an end-to-end value creation pipeline for business intelligence & Big Data solutions: Mining for data, processing, transporting, saving, enhancing and implementing it profitably Also as an Analytics-as-a-Service/ On-demand model Best price, best function technologies Available immediately, simple and fast scalability High-performing VPN/MPLS network infrastructures t Transition concepts for entry into the Big Data World T-Systems Big Data

15 YOUR BIG DATA MINING PROGRAM. BIG DATA READINESS ASSESSMENT. ASSESSMENT IN 3 PHASES Phase 1 Analysis of challenges facing you Identification of relevant systems and processes Specifying the potentials and requirements Phase 2 Evaluation Prioritizing the Big Data potentials Solution design Operation and maintenance concept Simulation of selected scenarios with initial cost-benefit analysis Phase 3 Development of your Big Data strategy Defining your Big Data roadmap Strategy with comprehensive analysis of costs, savings potentials, ROI and business case T-Systems Big Data

16 OUR OFFER FOR A TRIAL RUN. WHERE DO YOU STAND? Assessment Phase 1 5 Sustainable optimization of your business Big Data optimization Phase 1 First processes optimized Analyse Ihrer Herausforderungen Identifikation der relevanten Systeme und Prozesse First projects before finalization First projects launched Konkretisierung der Potenziale und Anforderungen Big Data execution Big Data strategy Big Data CoE A f First d concepts & PoC Big Data initiatives 0 No Big Data Legacy applications T-Systems Big Data

17 Backup

18 DATA PROCESSING AND ANALYSIS IS NOT NEW. THE QUALITY AND QUANTITY ARE. Over the past 50 years, operative data have been summarized, evaluated and presented to management to support decision-making processes. MIS DSS EUS EIS FIS DWH OLAP Data Miningi CPM BPM Analytical Applications Operational BI EIS FIS Business Analytics Based on: Humm, B/Wietek B./Wietek, F. (2005, S. 4) T-Systems Big Data

19 BIG DATA USE CASES BY BUSINESS FUNCTION. Marketing & Sales Product Development & Research Product Service & Support Distribution & Logistics Finance & Controlling Online Marketing Campaign Optimization Big Data for Point of Sales Optimization/Cross Selling Big Data for Point of Sales Optimization/Cross Selling Competitive Analysis using Online Press, Social Media with Scraping and Text Analysis Customer Churn Analysis for Prepaid Telco business (behavior based) Optimize Target Group Marketing for online banking based on trading/depot transactions Using Online Forums for Product Development & Sentiment t Analysis Social Media Usage for Macro/Micro Trend analysis Massive Parallel Processing for Drug Testing in Pharma CERN number crunching for test data (40GB/sec) Production Optimization using Sensor Data and Machine 2 Machine Communication Predictive Maintenance & Prediction (Combat unwanted production stops) Production Planning for Seasonal Goods (multi factor ) Supply Chain Optimization controlling own and OEM production capacity Truck transportation optimization (transport order navigational data, combined with traffic data) Road Charge Optimization (real time adaptation of fees according to current traffic) Customer Individual Discounts for products on websites and call centers (multi factor, real time) Financial Simulation and Scenario Calculations Financial Simulation and Scenario Calculations Online Fraud Detection (Credit Card transactions, etc.) Risk Controlling (Market Risk/Value at Risk) Detection of unknown financial risk (e.g. for real estate loans) T-Systems Big Data

20 BIG DATA MARKET POTENTIAL. Global Big Data Market CAGR 2012/2016 Services: + 41 % Software: + 45 % Hardware: + 32 % Source: PAC Breakdown by Vertical in 2016 Breakdown per Region in % Germany 19% Others 30% Banking 25% Rest of the World 25% Western 8% Insurance Europe 8% Telecommunication 8% Retail 16% Manufacturing 11% Public 44% USA Source: PAC T-Systems Big Data

21 POTENTIAL OFFERED BY BIG DATA TECHNOLOGY IN TERMS OF BUSINESS. N = 254 Data governance Precise financial reporting Improvement of compliance aspects Recognizing new potential for business Optimizing existing business cases Better information basis for corporate decisions Detailed information Better corporate control Better information management Information obtained faster Cost optimization Source: IDC-Survey Big Data in Germany, T-Systems Big Data

22 COMMON APPLICATION MISTAKES IN BIG DATA PROJECTS. Companies in many fields of business gain vital knowledge by evaluating Big Data. The most important application areas are marketing, sales and operational management. Brand Management 8 Other HR Logistics 22 Customer Service 30 Product Development 32 Finance 32 IT Analytics 33 Risk Management 35 Sales 38 Operations 43 Marketing Source: Forrester Research, Inc.: How Forrester Clients are using Big Data, September T-Systems Big Data

23 TRANSFORMATION POTENTIAL OFFERED BY BIG DATA. The economic sectors that can expect profound changes in the coming years. Data intensity today: 2012 Data intensity in future: = low/10 = high 1 = low/10 = high Data growth per year Big Data business model Potential for transformation Industrial % medium Mobility & Logistics % very high Professional Services % high Finance & Insurance % high Healthcare % very high Government/Education % very high Utilities % medium IT, Telco, Media % very high Retail Wholesale % very high Source: Experton Group 2012 T-Systems Big Data