A practical approach towards Big Data in the context of the upcoming EU data privacy and data protection regulation.

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1 A practical approach towards Big Data in the context of the upcoming EU data privacy and data protection regulation SAS Forum 2015

2 Privacy What s ongoing? Safe Harbour EU - GDPR White house NL Data Breach 3 Russian localization law

3 GDPR: When? Commission & parliament focus Data subject s rights Tripartite (Q2-Q3) Time Companies & Org. rights Parliament approval 03/2014 Current Council Final publishing 01/2016 This push for data protection rights is apparent in the General Data Protection Regulation (the Regulation ), which is still in draft form. In addition to Mr. Juncker, the new European Data Protection supervisor, Mr. Giovanni Buttarelli, and several members of the European Parliament, including the German member of parliament who has been central to driving through the Regulation, Mr. Jan Philipp Albrecht, have all called for the Regulation to be finalized this year or end of Jan * Based upon insights available at this point & best guess estimations 4

4 Why are data breaches such a big issue for a company? Fines*: Up to 5% or 10% of (global) turnover or up to 100 MIO Euro GDPR Data breach Cost/ breached record = +200 Informing data subjects & gov. Personal liability Conviction s Financial losses Board, CEO and shares affected *fines are already being imposed in the EU based upon the current legislation (e.g. Italy, Spain, Ireland, ) Reputation loss & loss of customer/supplier/e mployee trust 5

5 Regulatory Do we only need to care about privacy because of this new National & EU regulations? Strong growth in Data breaches Increased (EU) citizen concern about their privacy Execute privacy Roadmap Hard for companies to differentiate 6

6 GDPR: Privacy is about more than just consent: Any processing of personal identifiable information data portability data breaches capturing and managing all types of consent, channels, texts, products, type of consent, data privacy by design, data minimisation data exchange (Safe harbour is invalid, ) 7

7 What (personal) data will be affected? Personal data & information must be accurate and kept up-to-date & kept in a form which permits identification no longer than necessary. privacy by design Store the personal data/information/conte nt Document the use* of personal data/information/conte nt * processing, data mining, analytics, distribution, 8

8 Anonymization = Privacy by design 10

9 Legal Information management capabilities are the key to privacy compliance The path to compliance is paved with IM capabilities 12

10 Data privacy as a limitation/opportunity to information mgt. 13

11 Data mastering & consent handling Do I have consent? How do I master consent and personal data? Privacy/conse nt master Party-MDM Data Quality Sensitive data warnings Metadata Mgt. Privacy by design Data & Information governance 14

12 Data Quality Personal data is blocked for processing if quality is not ok Privacy/conse nt master Party-MDM Data Quality Sensitive data warnings Information lifecycle mgt. Privacy by design Data & Information governance 16

13 Ok, MDM and Data Quality, but what about Big Data? Data lake 2) Consent for data lake? Sensitive data? 19 1) Privacy assured shore data

14 Big data processing Big Data Processing Data lake Manage Data Lake input Metadata Mgt. Party-MDM Sensitive data warnings Data Quality Privacy/conse nt master Privacy by design Data & Information governance 20

15 Gain customer trust Differentiate on privacy Towards Value out of big data & Privacy compliance Analytics/insight Data science/discovery Operational use Pull your data into a green privacy compliant shore - Data & information governance - Policies & enforcement - MDM & Privacy master - Information en solution architecture - Metadata (fish finder in data lakes) - Data Quality - Integration - Information lifecycle mgt. - PII scope - Data privacy by design & data minimization DPO & Org & governance/enforcement (combi legal, ) Manage your data lake input Check sensitive data Check consent

16 Analytics Can I still profile, data mine personal (children) data? Can we use personal data in BI/Advanced analytics and to what level do we ananymize? What about data science? Privacy/conse nt master Party-MDM Data Quality Sensitive data warnings Metadata Mgt. Privacy by design Data & Information governance

17 (Big) Data exchange? Privacy/conse nt master Can I still exchange (Big) personal data to other countries? BCR, Safe country list, Party-MDM Data Quality Sensitive data warnings Metadata Mgt. Privacy by design Data & Information governance 24

18 Data breach What do I need (to do) in case of a (Big) Data breach? Data breach prevention Data breach scenario Data Quality Breach on breach prevention? Privacy/conse nt master Party-MDM

19 Monitoring and reporting on privacy? Information lifecycle What does a company (DPO) need to monitor and report with regards to privacy? 26 Data Quality Privacy/conse nt master Party-MDM Reporting Data quality reports as part of audit. Operational & analytical Segmentatio n

20 Data quality relevant to most privacy topics Data mastering & consent handling Monitoring and reporting on privacy Data breach MDM Data Quality Info/Data gov. Data processing Data exchange Analytics Big data processing 29

21 UI / Portal Service layer Service layer Approach: Data privacy & protection as a service? Data quality service Industry specifc metadata mgt. Security, automated request handling, Service requests Identity Mgt. Analytics Master (MDM) Metadata-mgt (repository) E-com CRM Analytics ERP Archiving Operational Party MDM Identity Mgt. Service reply s ESB, industry specific messages, 30 Analytics Master (ECM) Doc. mgt

22 UI / Portal Service layer Service layer Approach: Data privacy & protection as a service? Data quality service Industry specifc metadata mgt. Metadata-mgt (repository) Security, automated request handling, Service requests BI E-com CRM Analytics ERP Archiving Operational Party MDM Identity Mgt. DWH DQ Identity Mgt. Service reply s ESB, industry specific messages, 31 Analytics Master (ECM) Doc. mgt

23 Concluding: Privacy as a positive differentiator B2B vs B2C - behind every B there s a C Use privacy as an opportunity - explain the customer upon asking consent the value Privacy as an opportunity for information management including big data & data science Privacy as a differentiator (Nike, Apple, ) 32

24 Closing remark: The ability to ensure privacy & protection of person s data is becoming a crucial differentiator for more and more companies and their customers. 33

25 Thank you An Information Management and Data Insight company 34 Inpuls Duwijckstraat Lier Belgium T M Jan.Henderyckx@inpuls.eu Web:

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