A 360 Degree View of Anything

Transcription

1 A 360 Degree View of Anything Sara Mazer, Principal Solutions Architect MarkLogic Corporation

2 Data is Growing at a Staggering Rate 44 ZB 8 ZB Source: IDC SLIDE: 2

3 Enterprise IT Faces Unprecedented Challenge Leveraging Both Heterogeneous and Unstructured Data 12% Structured 88% Unstructured Reference Data OLTP Warehouse Archives Data Marts? SLIDE: 3

4 Relational Databases Are Not Designed to Solve This Problem Explosion of Heterogeneous Data Inability of Companies to Store, Manage, and Search Their Data ZB Reference Data ZBs OLTP Warehouse Structured Unstructured Archives Data Marts? Unstructured Data Source: IDC SLIDE: 4

5 The Endless Cycle of Data Normalization Take snapshot of current data Build master data model based 1 on initial view 2 x 4 Revise static model & restart process for new data Extract, transform, & load data into data model 3 SLIDE: 5

6 The Endless Cycle of Data Normalization Take snapshot of current data Build master data model based 1 on initial view years $2M++ x 4 Revise static model and restart process for new data Extract, transform, and load data into data model 3 SLIDE: 6

7 Data layer Simple and Fast Data Integration With NoSQL Load data as-is - index data 1 now and transform over time 2 Agile application development without constraints - and with a stable data layer Time-to-completion: 3 months Time-to-completion: 3 months SLIDE: 7

8 THE SHIFT AWAY FROM RELATIONAL

9 Generational Shift in Database Market Relational Era For all your structured data! Bad for unstructured Difficult for heterogeneous Proprietary hardware Expensive Hierarchical Era For your application data!" Proprietary hardware Expensive Any Structure Era For all your data! Massive scale Built for heterogeneous and unstructured data Faster time-to-results Commodity hardware Fraction of the cost SLIDE: 9

10 Operational Database Market Static for Over a Decade Gartner Online Transaction Processing RDMBS Magic Quadrant by Betsy Burton and Kevin H. Strange, May 2, 2002 Gartner Magic Quadrant for Operational Database Management Systems by Donald Feinberg, Merv Adrian, Nick Heudecker, October 21, 2013 SLIDE: 10

11 2014: MarkLogic Only NoSQL Vendor in Leaders Quadrant 2014 *Gartner Magic Quadrant for Operational Database Management Systems by Donald Feinberg, Merv Adrian, Nick Heudecker, October 16, 2014 SLIDE: 11

12 Enterprise Capability: A Corporate IT Requirement ACID: ATOMIC, CONSISTENT, ISOLATED, DURABLE Uncompromised Data & Transaction Resiliency "Don't lose your data!" SECURITY Enterprise-grade, Fine-grained Access "Protect your data!" HIGH AVAILABILITY DISASTER RECOVERY Automatic Failover, Replication, Backup/Recovery "Prepare for the worst!" SLIDE: 12

13 Core Differentiator: Purpose-built for the Enterprise RELATIONAL OPEN SOURCE ACID TRANSACTIONS SECURITY HIGH AVAILABILITY & DISASTER RECOVERY SCHEMA-AGNOSTIC SCALE-OUT ELASTIC TIERED STORAGE SEMANTICS SLIDE: 13

14 PROVEN IN THE ENTERPRISE & EXPANDING USE CASES

15 What s possible with a new approach? 360

16 COMPETITIVE

17 Industry News and Events Competitive Timelines Alerting Customer/Patient Data Literature, Publications, SPL Competitive 360 Sales Data Knowledge Discovery Search & Query SLIDE: 17 <triple> <subject> IRIID </subject> <predicate> value </predicate> <object> ABC 123 </object> </triple> </description> Content Enrichment Geospatial & Map Integration

18 PATIENT

19 Patient 360 Medical Charts (Patient history, demographics, vitals, physician notes ) Education Services (Content, documents, classes, videos, blogs) Scheduling System (Exam rooms, doctor/nurse schedules, patient appointments, equipment, location/geospatial) Medical Imagery (X-rays, labs, photos, patient info, dates, prescribing doctor) Call Center System (History, case notes, call recordings) SLIDE: 19 Patient Billing (Treatments, billing codes, insurance information, credit card info, payment notes) Prescription System (Prescriptions, refills, doctor notes, allergies, drug interactions)

20 Patient 360 Medical Charts (Patient history, demographics, vitals, physician notes ) Education Services (Content, documents, classes, videos, blogs) Scheduling System (Exam rooms, doctor/nurse schedules, patient appointments, equipment, location/geospatial) Medical Imagery (X-rays, labs, photos, patient info, dates, prescribing doctor) Call Center System (History, case notes, call recordings) SLIDE: 20 Patient Billing (Treatments, billing codes, insurance information, credit card info, payment notes) Prescription System (Prescriptions, refills, doctor notes, allergies, drug interactions)

21 Enabling Multi-Dimensional Views of Patients Physician/Payer Data: Holistic view of an individual Activities: View medical history, tests and allergies Epidemiologist Data: Biographic, diagnosis & location Activities: Analyze aggregates and temporal and geospatial distributions Adverse Event Researcher Data: Prescriptions history, hospitalizations and doctors visits Activities: Detect anomalies, predictive analytics and trend analysis Patient s Record? Anonymized Information? Anonymized Information SLIDE: 21

22 SUPPLY CHAIN

23 Supply 360 Structured and Unstructured Data Store Profile - Locational data - Order history - Assortment - Receipt/DC Store Supplier Profile - Type/history - Supply/SKU - Capacity - Receipt/DC - Order receipt - Payment Carrier/Logistics - Shipment data - Logistics data - Payment - Location Supplier Carrier/ Logistics Supplier 360 Value Prop. Improved forecast Accuracy Lower Inventory investment Reduced out-of-stocks Lower total landed costs Reduced mark downs Consumer & External - Consumer profile - Demographics - Weather - Location - Seasonality Consumer & External SLIDE: 23 Provide one consolidated view real time across the supply chain on design objects, bids & contracts, forecasts, inventory, documents, and shipments COPYRIGHT 2014 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.

24 REGULATORY

25 MarkLogic Adverse Events/Drug Reaction Profiles 360 View SAS, Excel Signal Profile Review Application Alerting Web Application After MarkLogic Simple, Fast Data Integration Bring together documents, data, and triples from over 90 different sources within and outside of Monsanto Powerful, Intelligent Data Layer Data analytics that leverage Monsanto s ontologies and uses semantics as the glue to answer new questions (e.g., What are all of the genomic elements (in)directly contributing, regulating or modulating a specified developmental or physiological Load data process as in is a plant or crop species? ) More Relevant Content Delivery Contextually tailor access to information by leveraging the user s role, context, activity, and location to dynamically deliver the right information FAERS Europe VIGIBASE Enterprise Scale IND, NDA, MedLINE EMBASE STRIDE All of Periodic the required Safety enterprise features HA/DR, security, etc. plus other features such as Updates Flexible Replication and Tiered Storage SLIDE: 25

26 Medical Device Submissions PDF Combine and enrich information from multiple sources Medical device manufacturer packets Adverse events reporting Data can now be searched & analyzed from one location Compare to past data on same classes of devices Compare to past packet contents (what s new, have issues been addressed, etc.) SLIDE: 26

27 HEALTHCARE.GOV

28 Health insurance for millions of Americans Before MarkLogic Unable to handle complexity Impossible data model Development too slow Limited scalability Inflexible to change After MarkLogic Built for Today s Data Schema-agnostic data model that could handle various data sources and adapt to later changes with policies and regulations Agile Development 18-month timeframe from procurement to launch for what has been called the most complex government-it project of all-time Secure and Trusted Did not have to sacrifice any of the enterprise features required, and could rely on a system with government-grade security, ACID transactions, and HA/DR Successful Deployment Over 8 Million people signed up for health insurance in less than 5 months SLIDE: 28

29 8,000,000+ new beneficiaries 150,000+ concurrent users 0 zero data loss SLIDE: 29

30 ONE PLATFORM

31 Search & Query ACID Transactions Enterprise Search, Database, and App Services High Availability / Disaster Recovery Replication Government-grade Security Scalability & Elasticity On-premise or Cloud Deployment DATABASE SEARCH Hadoop for Storage & Compute Semantics Faster Time-to-Results APPLICATION SERVICES SLIDE: 31

32 BETTER INSIGHT WITH SEMANTICS

33 Semantics to Link Data Data model to manage relationships and link together data triples (Subject-Predicate-Object) describe single facts Collections of facts describe complex real-world scenarios "John Smith" livesin "London" isin "England"! livesin SLIDE: 33

34 Semantic World Document World Linked Open Data (Free semantic facts available to anyone) The World of Triples Facts in Documents (Part of metadata or added with authoring tools) Proprietary Semantic Facts (Facts and Taxonomies in your organization) Facts from Free-Flowing Text (Derived from semantic enrichment) SLIDE: 34

35 MarkLogic Semantics Use Cases Semantic Search Make use of billions of facts to make your search app better Dynamic Semantic Publishing Manage nuggets of information, deliver as mashups Information Aggregation and Reduced ETL Aggregate atomic pieces of data Link same/similar/related documents and data SLIDE: 35

36 EX: British Standards Institute "Compliance Navigator" Find all the standards I need to read before building a "cardiac catheter" Ex. Search for "cardiac catheters" also returns results for: safety requirements for devices that stimulate nerves sterilization of implantable devices SLIDE: 36