Nyheter i SAS Data Management med SAS versjon 9.4

Transcription

1 make connections share ideas be inspired Nyheter i SAS Data Management med SAS versjon 9.4 Terje Vatle Nordic CoE, Data Management C o p y r i g h t , S A S I n s t i t u t e I n c. A l l r i g h t s r e s e r v e d.

2 Agenda Hvorfor SAS Data Management? Hva kan du gjøre med SAS Data Management? Nyheter med SAS 9.4-basert Data Management SAS Access SAS Data Integration Studio SAS Data Management Platform SAS Master Data Management

3 COMPETITIVE ADVANTAGE Hvorfor SAS Data Management? Tilrettelegging for analyse Preppe store og små data Lasting What will rett happen inn if these i in-memory trends continue? appliance Why is this happening? In-database datakvalitet What will happen next? BUSINESS INTELLIGENCE Hvor går grensene for SQL? What is the best that can happen? Alerts Statistical analysis Drill down Ad hoc SAS DM kan gjøre reports kompliserte beregninger Standard reports Cleansed Source data data DEGREE OF INTELLIGENCE Forecasting Predictive modeling Optimization BUSINESS ANALYTICS Which actions are required? Where exactly is the problem? How many, how often? What happened? SAS DM er én løsning for datakvalitet, dataintegrasjon, tilgang, føderasjon og MDM Operasjonalisering av analyse 3

4 Hva kan du gjøre med SAS Data Management? Business glossary & rules Matching / Entity Resolution Profiling & Monitoring Reporting & dashboarding Stewardship, Remediation Multi-domain MDM Reference data management Relationship management & lineage Workflows / Enrichment Data abstraction Data aggregation Data caching Data Governance Data Integration Data Quality Master Data Management Data Federation Enterprise Data Access Data Migration Data Preparation for Analytics DWH and data marts Data Access Engine / Db connectors (incl. Hadoop) Event stream processing ETL & ELT, SOA and Messaging support

5 36 Years of Data Management and Governance Experience SAS Data Management Customers in 60k sites across 134 countries 90% of the Fortune 500 companies use SAS 24% reinvestment in R&D Leader Gartner Magic Quadrant Data Integration COE Advisory Workshops (Exec Briefing, Assessments, Strategy & Roadmap) SAS Best Practices Data Quality DW Pioneers Data Governance Master Data Management Leader in Advanced Data Visualization - Forester Leader in Big Data Analytics - Forester Data Federation Leader Gartner Magic Quadrant Champion Bloor Research Leader Information Difference Enterprise Data Access 2nd Largest Data Access & Management Vendor - IDC

6 Data Access Connectors & Access Engines Transparent access to data stored on a variety of platforms and formats (>60 different sources) Data residing in Applications as well as metadata stores Structured, semi-structured and unstructured data Data at rest and data streams Event stream processing Continuously analyzes data as it is received for real time decision making Bank transaction fraud detection Real-time analysis of social data streams Personalized online offers based on navigation

7 Data Integration Integrated data quality to stop bad data at the source, deduplicate, standardize, etc A B Interactive, visual data integration development environment that enables collaboration and reusability

8 Data Federation Query and use of data across multiple systems without the physical movement of source data People Processes Technology Virtual Data Layer SAS Federation Server Oracle DB2 Terad ata SQL Server SAP SAS Datas ets ODBC Other

9 Data Federation People Processes Technology End Users Power users Contractors Auditors 3 rd parties Orders Call center Customer onboarding Customer Service Off shore Virtual Data Layer SAS Federation Server BI tools Analytic apps Spreadsheets Data Warehouse MDM Summary data Personal data Customers Recent Activities Dashboard summary data Public data Private data Products Suppliers Complete detailed data SAS Federation Server Drivers

10 SAS Data Federation

11 Data Quality In-database: SAS Data Quality Accelerator for 6 Remediate & Improve 1 Define the terms and sources 5 Monitor & Publish DQ measurement 2 Discover & Profile the Data 4 Apply injection and execution 3 Design data quality standards

12 Master Data Management Single view of key data across multiple business applications and channels MDM Cross-functional collaboration and business process optimisation Cross-channel integration, KYC, Integrated Marketing, M&A readiness

13 Data Governance Formal orchestration of people, processes and technology to leverage data as a corporate asset Data Management processes DQ Remediation Business rules Consensus Collaboration Roles & Responsibilities Ownership, stewardship, accountability Business data glossary Data validation and DQ monitoring Reporting & dashboarding Transparency

14 Nyheter i SAS Data Management SAS Plattform Integration Alle server connections via SAS metadata Brukere, grupper, roller, jobber, tabeller mm Webapplikasjoner SAS Data Management Console* SAS Job Monitoring* SAS Visual Process Orchestration* Bonus: Clustering af SAS Metadata Server i SAS 9.4 Tilgjengelighet Performance * P.t. kun i SAS Data Management Advanced kommer i Standard til vinter

15 SAS Data Management Console Application Bar RSS Reader Monitoring Portlet

16 SAS Visual Process Orchestration Web Browser SAS Folders S SAS Web Application Server PO Design PO Execute Data Management Server 1 Data Management Server N SAS DI Server E XX Server Visual Process Orchestration Process Jobs

17 SAS Visual Process Orchestration

18 Nyheter i SAS Data Integration Studio 4.7 (SAS 9.4) Cut/Copy/Paste i Process Flow Diagram DI Studio LASR TM Load/unload transforms (production) Kalle Web Services fra DI Jobs via SOAP transform Kalle Web Services fra DI Jobs via REST transform

19 In-database data quality SAS DATA QUALITY ACCELERATOR FOR Only Selective DQ Features Parsing Mr. Roy G Biv Jr Extraction Blue mens long-sleeved buttondown collar denim shirt Pattern Analysis Identification Analysis First vendor in the market! DQ functions executed as stored procedure, leveraging SAS Knowledge Base (QKB) John Smith = Name / SAS = Organization Gender Analysis Standardization, Casing Matching Jane Smith = F - Sam Adams = M = (919) John Smith / J. Smith / Mr. Jon Smith Benefits Fast DQ processes for large data volumes Processes 500 times more data Data Cleansing To Decision making 99% faster

20 SAS MDM 4.1

21 Enklere og raskere å få ny innsikt Rapid Report Development Faster Time To Value Business Agility Validate Reporting Approaches Federation Server Virtual Data Layer Acquiring Data needed for reports from sources Start DWH Rollout DWH Mktg. CRM Finance

22 SAS Data Management - Sammendrag Én integrert løsning Tilgang Datakvalitet Dataintegrasjon MDM Føderasjon Muliggjør analyse Tilrettelegging Operasjonalisering

23 make connections share ideas be inspired Takk for oppmerksomheten! Terje Vatle C o p y r i g h t , S A S I n s t i t u t e ICopyright n c. A l l 2010, r i gsas h t s Institute r e s Inc. e r vall e rights d. reserved.