How to Govern Integrated Data and Prove it
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1 How to Govern Integrated Data and Prove it Chris Atkinson Solution Architect for Financial Services, MarkLogic 1 June 2018 MARKLOGIC CORPORATION
2 The Data Lake Schema On-Read Ingest As-is Any Shape Join at read time No upfront modeling No Information Loss Great for reporting / analysis SLIDE: 2 1 June 2018 MARKLOGIC CORPORATION
3 Data Lake Operational & Governance Challenges Application Security Many Components Scripts / Plugins Security Risk Performance Transactions Audit / Lineage SLIDE: 3 1 June 2018 MARKLOGIC CORPORATION
4 Two Solution Problem Data Lake / Reporting Hub Multiple Models Schema-On-Read Non-Transactional OLAP Focus ETL Operational / Application DB Single Model Schema-On-Write Transactional safe OLTP Focus SLIDE: 4 1 June 2018 MARKLOGIC CORPORATION
5 Operational Data Hub Multi-model database Schema-On-Read Transactional Discovery Indexing OLTP & OLAP SLIDE: 5 1 June 2018 MARKLOGIC CORPORATION
6 A Practical Approach
7 Harry Remove me plz Erm what?! How the #$&! A Typical Governance Issue ABC Bank Finance Retail Mailer Breach Notify Consent Report breaches Security by design Subject requests Right to be forgotten Forget me! I m done! Finance 2 man days Insurance Mailer 2 man days 2 man days 2 man days Lawyer Compliance 2 man days SLIDE: 7 1 June 2018 MARKLOGIC CORPORATION
8 How Did This Happen? Data integrated poorly Lack of operationalization Insufficient security Missing chain-of-custody SLIDE: 8 1 June 2018 MARKLOGIC CORPORATION
9 Advice: Solve the Tactical Problem First Pick the quick win Use as requirements building block Pick an appropriate technology Use these budgets to transform Iterate and extend SLIDE: 9 1 June 2018 MARKLOGIC CORPORATION
10 Unstructured A Document Database Phone Transcript Text Store Objects or entire entities Retains original structure Structured data Poly-structured Data Unstructured Data Structured Structured Customer Profile JSON Trade Event XML Polystructured Financial Report PDF SLIDE: 10 1 June 2018 MARKLOGIC CORPORATION
11 Get An Accurate View of Harry s Consent Ingest metadata Source #1 Marketing Native sys_id Sys_consent API Resolve At Query Time Source #2 Mortgages Source #3 Retail Credits Index Secure metadata ID Consent Cust_ID Cust_Consent Source #4 Insurance Audit Semantic Mappings Sys_ID same as Cust_ID ID same as Cust_ID Sys consent same as Cust_Consent Consent same as Cust_Consent SLIDE: 11 1 June 2018 MARKLOGIC CORPORATION
12 Solve the Relevance Problem for Harry Retail Banking Profile sys_id : harry1234 Sys_ harry@gmail.com Sys_consent : TRUE Sys_type : Purchase Sys_last Purchase type : Automobile Sys_purchase date : 10/04/2018 Sys_balance : -200 Sys_overdraft Insurance Profile : 800 sys_id : harvu1234 Sys_ harry@gmail.com Sys_consent : TRUE Sys_type : Car-Insurance Sys_purchase date : 31/06/2017 Marketing API Query Time Customer 360 view Additional attributes Expose native data Cross functional View Instantly available SLIDE: 12 1 June 2018 MARKLOGIC CORPORATION
13 Operationalize Harry s Data Materialise Operational Entities Customer Profile Entity Marketing API Query & Update Customer View Updated By Ingest Updated Via API High Performance Transactional Safe OLTP Customer 360 view Insurance API Query & Update Customer View Mortgage API Query & Update Customer View SLIDE: 13 1 June 2018 MARKLOGIC CORPORATION
14 Related? New Attributes Large in relation Attributes Large High Update Rate Large Query Read? Append Attributes Create a New entity Query Perf Bad? Guidelines For Entities Materialise Query entity SLIDE: 14 1 June 2018 MARKLOGIC CORPORATION
15 Protect Harry s Personal Data by Default ID : harry harry@gmail.com account : standard Consent : TRUE Notes : Bobs number is Database Protected Paths Element Level Security Protect Unknown Attributes Protect Known Unsafe Attributes Safe Direct Data Access Easier Security Management SLIDE: 15 1 June 2018 MARKLOGIC CORPORATION
16 Prevent Harry s Data Being Stolen Technical User Profile Update API Read & Update Consent Normal Roles Assign Permissions Read/Update Unrestricted Access {consent} {ID} AMP GetUpdateUser() Amplified Role Assign Permission Update Read/Update Profile Encrypt the DB Declarative Access only Amplify Permissions Data File Security Limits Compromised Access GetUpdateUser() Database Encryption SLIDE: 16 1 June 2018 MARKLOGIC CORPORATION
17 Trace How Harry s Data Is Used PROV-O Ontology W3C Standard Implement via Graph/RDF Track ALL required Provenance Full lineage AGENT 10:14 Branch User Started At Attributed to 10:15 Ended At Harrys Profile ENTITY Message 3527f751s Derived From Generated by Ingest Module ACTIVITY SLIDE: 17 1 June 2018 MARKLOGIC CORPORATION
18 Identify Harry s Risk & Prove It! Campaign Breach Impacts Data Usage Data Access PII Locations Harry Hcu1235 Has Profile Attributed to Harrys Profile Purpose Of Started at Generated by :00 Used By Marketing System Purpose Of Started at Ended at : :02 Decline Consent Consent Portal SLIDE: 18 1 June 2018 MARKLOGIC CORPORATION
19 Trace Harry s History PROVO will not capture physical changes Unitemporal API provides time travel Hcprofile hcprofile.3426 (Latest) hcprofile.3427 Hcprofile (Latest) hcprofile (Latest) Retains history Protects from tampering 01 SEP 01 SEP System Time 22 SEP Optimizes find Latest version Turn around requests rapidly with ease SLIDE: 19 1 June 2018 MARKLOGIC CORPORATION
20 Temporal Lineage Basic Problem - Standard temporal inserts deviate over time - Effects joins on static data - Effects PROV-O source tracking Solution temporal:statement-set-documentversion-uri Source Target Source Target Order.xml (v1) entity.xml (v1) Order.6271.xml (v1) entity.5362.xml (v1) Order.6272.xml (v1) entity.5362.xml (v1) Order.6271.xml (v1) entity.5362.xml (v1) Order.xml (v2) entity.xml (v2) Order.6273.xml (v2) entity.5363xml (v2) SLIDE: 20 1 June 2018 MARKLOGIC CORPORATION
21 Outcome : Harry Is Delighted! Protected his data Didn t spam him Added value where needed A trusted service partner Harry becomes a sneezer SLIDE: 21 1 June 2018 MARKLOGIC CORPORATION
22 Data Hub With Governance All-in-One Operational Data Hub combined capabilities Complete suite of governance features Fully integrated Reduced data risk Faster time to results Proven track record SLIDE: 22 1 June 2018 MARKLOGIC CORPORATION
23 Questions?
24 LEARN MORE MarkLogic for Financial Services Post-trade processing Regulatory reporting and compliance Customer 360 Investment research and management Advanced content distribution Fraud detection SLIDE: 24 1 June 2018 MARKLOGIC CORPORATION
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