Big Data Use Case Deep Dive 5 Game Changing Use Cases for Big Data

Transcription

1 Big Data Use Case Deep Dive 5 Game Changing Use Cases for Big Data

2 Disruptive forces impact long standing business models across industries Pressure to do more with less Shift of power to the consumer Proliferation of big data 2 Data is the new oil. Data is just like crude. It s s valuable, but if unrefined it cannot really be used. Clive Humby We have an economy based on a resource that is not only renewable, but self-generating. Running out is not a problem, drowning in it is. John Naisbitt

3 The demand for big data solutions is real The healthcare industry spends roughly $250 billion on healthcare fraud, per year. By 2016, this could grow to more than $400 billion a year. 1 One rogue trader at a leading global financial services firm created $2 billion worth of losses, almost bankrupting the company. $93 billion in total sales is missed each year because retailers don t have the right products in stock to meet customer demand. 6 billion global subscribers in the telco industry are demanding unique and personalized offerings that match their individual lifestyles. 2 Source: 1. FBI Financial Crimes Report UN Telecom Agency Report, Oct

4 The fact is analysis is expanding from enterprise data to big data, creating new cost-effective opportunities for competitive advantage Traditional Approach Structured, analytical, logical New Approach Creative, holistic thought, intuition Transaction Data Internal App Data Mainframe Data OLTP System Data ERP Data Data Warehouse Structured Repeatable Linear Traditional Sources Hadoop and Streams Unstructured Exploratory Dynamic New Sources Multimedia Web Logs Social Data Text Data: s Sensor data: images RFID 4

5 A recent Institute for Business Value study highlights how organizations are adopting big data in four phases Big data adoption When segmented into four groups based on current levels of big data activity, respondents showed significant consistency in organizational behaviors Total respondents n = 1061 Totals do not equal 100% due to rounding 5

6 And everyone can develop and leverage big data it s not just for data scientists Business Users...offer personalized price promotions to different customer segments in real-time Administrators...secure, manage, and optimize data access and analysis operations GPS External Data Business Executives...get real-time reports and analysis based on data inside as well as outside the enterprise (web, social media etc.) Business Development... find and deliver new mechanisms to monetize network traffic and partner with upstream content providers 6 Data Scientists... analyze subscriber usage pattern in realtime and combine that with the profile for delivering promotional or retention offers Business Analysts... analyze social media buzz for the new services/offerings to gauge initial success and any course correction needed Developers... develop new Apps and detailed algorithms in response to user and business requirements

7 The 5 Key Use Cases Big Data Exploration Find, visualize, understand all big data to improve decision making Enhanced 360 o View of the Customer Extend existing customer views (MDM, CRM, etc) by incorporating additional internal and external information sources Security/Intelligence Extension Lower risk, detect fraud and monitor cyber security in real-time Operations Analysis Analyze a variety of machine data for improved business results Data Warehouse Augmentation Integrate big data and data warehouse capabilities to increase operational efficiency 7

8 1. Big Data Exploration Explore and mine big data to find what is interesting and relevant to the business for better decision making Requirements Explore new data sources for potential value Mine for what is relevant for a business imperative Assess the business value of unstructured content Uncover patterns with visualization and algorithms Prevent exposure of sensitive information Industry Examples Customer service knowledge portal Insurance catastrophe modeling Automotive features and pricing optimization Chemicals and Petroleum conditioned base maintenance Life Sciences drug effectiveness 8

9 1. Big Data Exploration: In Practice Exploration User Experience Analytics Experience Application Builder Integration & Governance Streams BigInsights Data Explorer Warehouse Connector Framework CM, RM, DM RDBMS Feeds Web 2.0 Web CRM, ERP File Systems 9

10 2. Enhanced 360º View of the Customer Optimize every customer interaction by knowing everything about them Requirements Create a connected picture of the customer Mine all existing and new sources of information Analyze social media to uncover sentiment about products Add value by optimizing every client interaction Industry Examples Smart meter analysis Telco data location monetization Retail marketing optimization Travel and Transport customer analytics and loyalty marketing Financial Services Next Best Action and customer retention Automotive warranty claims 10

11 2. Enhanced 360º View of the Customer: In Practice SOURCE SYSTEMS CRM Name: J Robertson Address: 35 West 15 th Address: Pittsburgh, PA Cognos BI Cognos Consumer Insight ERP Name: Janet Robertson Address: 35 West 15 th St. Address: Pittsburgh, PA Legacy Name: Address: Jan Robertson 36 West 15 th St. Address: Pittsburgh, PA o View of Party Identity InfoSphere Data Explorer InfoSphere MDM First: Last: Address: City: State/Zip: Gender: Age: DOB: Janet Robertson 35 West 15 th St Pittsburgh PA / F 48 1/4/64 BigInsights Streams Warehouse Unified View of Party s Information 11

12 3. Security and Intelligence Extension: Enhance traditional security solutions to prevent crime by analyzing all types and sources of big data 12 Requirements Enhanced Intelligence and Surveillance Insight Real-time Cyber Attack Prediction and Mitigation Crime Prediction and Protection Analyze data-in-motion and at rest to: Find associations Uncover patterns and facts Maintain currency of information Analyze network traffic to: Discover new threats sooner Detect known complex threats Take action in real-time Analyze telco and social data to: Gather criminal evidence Prevent criminal activities Proactively apprehend criminals Industry Examples Government threat and crime prediction and prevention Insurance claims fraud

13 3. Security/Intelligence Extension: Diagram I2 Analyst s Notebook Connectors Network Telemetry Monitoring Appliance (Optional) Real-time Ingest & Processing InfoSphere Streams Video/audio Network Geospatial Predictive Big Data Storage & Analytics InfoSphere BigInsights Data Warehouse Deep analytics Operational analytics Criminal Information Tracking System Surveillance Monitoring System Guardium Data Activity Monitoring Connectors Text and entity analytics Data mining Machine learning Large scale structured data management Security Info & Event Mgmt (SIEM) Flow of Data 13

14 4. Operations Analysis: Needs Apply analytics to machine data for greater operational efficiency Requirements Analyze machine data to identify events of interest Apply predictive models to identify potential anomalies Combine information to understand service levels Monitor systems to avoid service degradation or outages Industry Examples Automotive advanced condition monitoring Chemical and Petroleum condition-based Maintenance Energy and Utility condition-based maintenance Telco campaign management Travel and Transport real-time predictive maintenance 14

15 4. Operations Analysis: Diagram Raw Logs and Machine Data Only store what is needed Data Security & Monitoring Machine Data Accelerator Indexing, Search Statistical Modeling Root Cause Analysis Real-time Analysis Federated Navigation & Discovery 15

16 5. Data Warehouse Augmentation: Needs Exploit technology advances to deliver more value from an existing data warehouse investment while reducing cost Requirements Add new sources to existing data warehouse investments Optimize storage and provide query-able archive Rationalize for greater simplicity and lower cost Enable complex analytical applications with faster queries Examples Pre-Processing Hub Query-able Archive Exploratory Analysis Operational Reporting Real-time Scoring Segmentation and Modeling Scale predictive analytics and business intelligence 16

17 5. Data Warehouse Augmentation: Diagram 1 Pre-Processing Hub 2 Query-able Archive 3 Exploratory Analysis Streams Real-time processing Data Explorer BigInsights Landing zone for all data BigInsights Data Explorer Find and view the data Can combine with unstructured information BigInsights Streams Offload analytics for microsecond latency Data Warehouse Data Warehouse Data Warehouse 17

18 IBM provides a holistic and integrated approach to big data & analytics Enterprise Fraud Fraud Solutions Healthcare Next Best Analytics Action Social Social Media Media Analytics Analytics Enabling organizations to: Discover and assemble relevant information Analytics and Decision Management Decision Predictive Content Decision Visualizatio Visualization Analytics Analytics Management Manageme n & Discovery nt & Discovery Big Data Platform Content Content Hadoop Manageme Data Stream Stream Data Management System Warehouse nt Warehouse Computing Computing Information Integration and Governance Information Integration and Governance Big Data Infrastructure: Systems, Storage and Cloud Acceleration & Application Development Analyze patterns and predict outcomes Visualize and explore for answers Take action and automate processes Optimize analytical performance and IT costs Manage, govern & secure information 18

19 Big Data and Information Integration / Governance Integrate & Link Big Data High performance load and read from BigInsights Integrate seamlessly w/existing enterprise Data lineage & impact analysis across the data supply chain Cleanse and Validate Big Data Accuracy and entity matching with social data and standardization of machine data Cleanse and match final results of big data analysis before reporting Protect Big Data Active monitor trap any unexpected access and breaches Mask sensitive data to ensure data protection and industry compliance Audit & Archive Big Data Create queryable archive for exploratory analysis of historical data Ensure compliance with Immutable archive and secure access to the data Master Big Data BigInsights will be a supplier of data to MDM and consume MDM data in the analysis Link BigInsights and trusted golden records Entity resolution at extreme scale 19

20 We are closing the skills gap 20

21 And we are driving hundreds of new Analytics and Big Data programs Active Relationships with 200+ Universities Around the World Building new programs and enhancing existing programs to train the skilled professionals of the future in: Analytics Big Data Business Intelligence and Analytics Predictive Analytics Computing and Informatics Math, Statistics Operations Research Data Science Majority of new programs are Masters level in Business Schools 21

22 And building an extensive business partner ecosystem for Big Data and Analytics (Over 330 partners!) CC&G Partners 22

23 So how do you get started with big data? Big data adoption Educate Focused on knowledge gathering and market observations Explore Developing strategy and roadmap based on business needs and challenges Engage Piloting big data initiatives to validate value and requirements Execute Deployed two or more big data initiatives and continuing to apply advanced analytics Join the business community Validate and realize business value 23 Join the technical community Big data case studies, whitepapers and IBM Institute for Business Value reports ibmbigdatahub.com IBM Briefings, Solution Centers Self-paced learning, exploration with downloads & test environment BigDatauniversity.com, YouTube Big Data Channel IBM Readiness Assessment for Big Data -Prioritized business use cases -Recommend big data platform Learn the technology & gain expertise Solution Design & Proof of Concept -Validate business value of the big data use case -Demonstrate big data capabilities to execute use case Enterprisewide big data initiatives -Incremental value across multiple use cases -Leverage investment from re-using the same big data platform -Enterprise data platform to support analytics

24 Think Big: Your Business Depends on It Leverage analytics as a game-changer Embrace big data to maximize your business outcomes Get inspired and take action 24

25 Watson combines transformational capabilities to deliver a new world experience 1 2 Understands natural language and human style communication Generates and evaluates evidencebased hypothesis Watson understands me. Watson engages me. Watson learns and improves over time. Watson helps me discover. Watson establishes trust. 3 Adapts and learns from training, interaction, and outcomes Watson has endless capacity for insight. Watson operates in a timely fashion. 25

26 Introducing the IBM Watson Group Software Systems and Technology Services Watson Cognitive systems, like Watson, are helping to usher in a new era of computing. An era where systems interact in natural language and learn with each interaction and outcome. An era that leverage Big Data, the new natural resource, putting content into context, allowing individuals to make informed, evidence based decisions with the confidence and supporting evidence that facilitates trust and transparency. 26

27 The Watson Family IBM Watson Solutions Bespoke solutions designed to meet some of industries most demanding needs leveraging cognitive capabilities IBM Watson Advisors IBM Watson Ecosystems Products based on Watson s core attributes and capabilities IBM Watson Cognitive Fabric APIs, tools, methodologies, SDKs, and infrastructure that fuels Watson IBM Watson family The Watson Developer Cloud, Watson Content Store and Watson Talent Hub driving innovation from partners IBM Watson Foundations Provides Big Data and core analytical capabilities which serve as the foundation for Watson 27

28 THINK Big Big Data Gerald Aufmuth IBM Information Management CTP für Data Management und Data Warehousing IBM Europe A Software Group IBM Österreich Obere Donaustrasse Wien Tel: +43-(0) Mobil: [email protected] 28

29 Thank you