Klarna Tech Talk: Mind the Data! Jeff Pollock InfoSphere Information Integration & Governance



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Transcription:

Klarna Tech Talk: Mind the Data! Jeff Pollock InfoSphere Information Integration & Governance

IBM s statements regarding its plans, directions, and intent are subject to change or withdrawal without notice at IBM s sole discretion. Information regarding potential future products is intended to outline our general product direction and it should not be relied on in making a purchasing decision. The information mentioned regarding potential future products is not a commitment, promise, or legal obligation to deliver any material, code or functionality. Information about potential future products may not be incorporated into any contract. The development, release, and timing of any future features or functionality described for our products remains at our sole discretion. Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will experience will vary depending upon many factors, including considerations such as the amount of multiprogramming in the user's job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results similar to those stated here 2

Accelerated Pace of Change Commerce Data Shanghai

Driven by Technology Innovations Capabilities Categories Markets Turn information into insights Deepen Engagement with customers, partners and employees Enable the agile business Accelerate product and service innovation Deliver enterprise mobility Optimize IT and business infrastructure Manage risk, security and compliance Big Data Analytics $18B 1 Mobile Enterprise $36B 2 Security Intelligence $38B 3 Cloud and Optimized Workloads $73B 4 1. IDC 2015 Market Opportunity 2. IDC & Other External Sources 2015 Opportunity 3. IDC 2015 Market Opportunity, excluding services 4. IBM internal analysis based on IDC data

Data-driven Technology = Data-driven Business Volume Variety Velocity Veracity Data at Scale Data in Many Forms Data in Motion Data Uncertainty Terabytes to petabytes of data Structured, unstructured, text, multimedia Analysis of streaming data to enable decisions within fractions of a second. Managing the reliability and predictability of inherently imprecise data types.

Data Fabric Helps Clients Build Smarter Businesses Customer Service Human Resources Logistics Technology & Product Development Sales Marketing Finance

Data Fabric Access and Provision Data Seamlessly Batch Federation Search & Browse Type 1: Normal Batch Traditional high-volume runtime Type 2: Micro-Batch Regular intervals for near-real time Type 3: ELT (SQL or MapReduce) Push processing to the data Trigger a Data Integration Job Launch data integration/ cleansing tasks through web service bindings Type 1: Relational Views, SQL Models and Nicknames give layered views into federated data Type 2: XML Views, XQuery XML documents and XQuery query semantics for data retreival Shop for Data Information Catalog Universal place to begin looking for the business data you need Type 1: Simple Search Traditional keyword search Type 2: Advanced Search Category and taxonomy search Type 2: Faceted Navigation Active browse by value or schema Type 3: Services APIs, SOA Data Services layer for SOA CDC Based / Always On Receive low-latency log-based replication from CDC and process through complex transformation with guaranteed delivery Complex Queue Transformation Guaranteed delivery from/to message queues for complex, heterogenous requirements Messaging Type 1: Message Broker Advanced Enterprise Service Bus (ESB) with the reliability of MQ Canonical Data Services Always available application services with composite data views Customer 360 Total customer visibility with business data view and social data view including Web sources Type 2: B2B Appliance Replication Type 1: Consolidation Bring data from many sources and make it available to users in one Type 2: Distribution Workload balancing Type 3: Peer to Peer Continuous bi-directional synchronization Queue-based Delivery Deliver log-based replicated changes to a message queue with guaranteed delivery XML hardware acceleration for high-speed any-to-any transformations Trading partner connectivity and support for key industry standards like HL7, X12, and EDIFACT Big Data Fabric Human-centric Data Stewardship and Data Curation Workflow managed enrichment of business data Type 1: Federated Access data via central registry Type 2: Hub and Spoke Maintain source of truth Type 3: Hybrid Master Data Leverages reference data, data by registry and local trusted data Big Data Processing (Hadoop, MPP DW), Metadata (Management, Lineage, Impact) and Governance (Glossary, Quality, Discovery etc)

Smart Data is Integrated and Governed Data Industry Focused Fastest ROI Trusted Governance Confidence Agile Frameworks Lowest TCO Single Platform Unified Blueprints Cloud Ready Best Performance Self Service Integration Rapid Discovery 9

Value from Integration and Governance Outperform Competitors Transform the Front Office Experience Establish Trusted Information 3x 80% 77% Organizations with IIG outperform their competitors Organizations rated their decision making as good or excellent Organizations establish high or very high level of trust in data 10

Mind the Data (before it gets a mind of it s own!) Data

Proven Results IBM Integration & Governance 10 of the top 10 global banks 25 of the world s leading telecoms 17 of the top 20 Chinese financial services firms 5 of the top 6 global insurance providers Top 3 global automobile manufacturers 3 of the top 5 global retailers Technology Innovation : 1 st Integrated Information Server Platform 1 st Data Governance Capabilities Built-in 1 st Mainstream Big Data ETL Platform 1 st Unified Data Domain MDM Solution 1 st Integrated Data Lifecycle & Archiving Market Leadership: #1 ETL Market Share (IDC) #1 MDM Market Share (Gartner) #1 Data Quality Vision (Gartner) #1 in Integration Capabilities (Gartner) #1 Lifecycle Management (IDC)

Get Started with IBM Big Data

Get Started with Big Data A Reference Architecture

IBM s Big Data Portfolio Smarter Analytics / Business Analytics & Optimization SPSS Cognos BigInsights Data Explorer Information Server MDM, Optim Guardium CONSULTING and IMPLEMENTATION SERVICES Sales Marketing Finance Risk IT Operations HR Performance Management Risk Analytics ANALYTICS Decision Management Business Intelligence and Predictive Analytics Content Management BIG DATA PLATFORM Hadoop System SOLUTIONS Watson and Industry Solutions Stream Computing Information Integration and Governance SECURITY, SYSTEMS, STORAGE AND CLOUD Content Analytics Data Warehouse Industry Solutions Financial Analytics Risk Analytics Threat & Fraud Workplace Analytics Customer Analytics Business Intelligence Performance Management Content Management Information Management Foundation Client Services Volume Variety Velocity Veracity

Building Confidence with Top 5 Big Data Use Cases Big Data Exploration Enhanced 360 o View of the Customer Understand confidence Determine risk Establish master record Extent to all sources Security/Intelligence Extension Automatic data protection Mask sensitive information Operations Analysis High volume data integration Automatic data protection Data Warehouse Augmentation High volume data integration Agile big data archiving and retrieval

Data Warehouse Augmentation Automotive manufacturer to build out global data warehouse Need Consolidate existing DW projects globally Deliver real-time operational reporting Integrate and gain new insights across all data sources Benefits Single infrastructure to consolidate structured, semi-structured and unstructured data Proven, enterprise-class capabilities that can be deployed quickly and are simpler to manage

Enhanced 360 o View of the Customer Financial service provider enables customer-centric cross selling Need: Federated views of data on 20 million customers View data across 160 siloed systems Benefit Empowered agents Improved cross-selling to high value clients

IBM Big Data Industry Momentum