PRACTICAL CONSIDERATIONS FOR SHARING PUBLIC INFORMATION DAN FINERTY SAS CANADA. Copyr i g ht 2015, SAS Institut e Inc. All rights reser v e d.

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1 PRACTICAL CONSIDERATIONS FOR SHARING PUBLIC INFORMATION DAN FINERTY SAS CANADA

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3 CHALLENGE RAPIDLY CHANGING LANDSCAPE Ontario Open-Government Recent Legislation 83 Privacy Act 88 Freedom of Information & Protection of Privacy Act 04 Personal Information Protection and Electronic Documents Act

4 OPPORTUNITY MERGING INTERNAL & EXTERNAL DATA Ministry of Social Development (NZ) 1. Virtual Diabetes Repository (VDR) - Integration of hospital and general practices with 6 internal databases linked ethnicity to diabetes prevalence leading to targeted health programs 2. Welfare Reform (Police, Education, Social Development) Reduced number of people receiving unemployment benefits due to gainful employment Decreased rate of people returning to benefit Improved case management and training initiatives

5 OUTCOMES CREATING OR CONSUMING PUBLIC INFORMATION Major Types of Information Personally Identifiable Information (PII) Internal & External Dissemination Data Structure of Information Backwards (Reporting) Forwards (Predictive) Establishing Polices & Measurements

6 ISSUES PRIVACY When do you apply protection? Who is trusted to access information? Delegation? How do I audit access? Who do I inform?

7 ISSUES ANTICIPATED USAGE OF DATA What s the question? How many people enrolled? Where are they registered? How many are likely to enroll? Double cohort like 2003? What influences where students enroll?

8 ISSUES DATA STRUCTURE Efficient storage Fast retrieval Defined schema WIDE tables /Time series data Iteration (build, test, repeat) Schema-less

9 OPPORTUNITY HIDDEN INSIGHTS: ENGLISH AS A SECOND LANGUAGE

10 DATA GOVERNANCE & MANAGEMENT

11 DATA GOVERNANCE THE DATA MANAGEMENT JOURNEY GETTING STARTED You can get there from here!

12 DATA GOVERNANCE ADDRESSING THE PROBLEMS It s really that simple? Enable policy-driven Data Management best practices

13 DATA MANAGEMENT DATA GOVERNANCE PROGRAM ROLES Executive Sponsorship Strategy Protect, enhance, and fund the program Data Governance Tactics Provide oversight, create policies and procedures, assess compliance, manage risks Data Stewardship Data Management Operations Develop & support the asset per governing policies & standards

14 Implement Appropriate Structure

15 FIRST STEPS LINEAGE All Relationships Origin >> Destination(s) Default views: Relationship, Governance and Impact view Identify when protection needs to be applied Governance Impact Analysis

16 FIRST STEPS BUSINESS DATA NETWORK Control and manage enterprise wide term definition Workflow-based term management Secured enterprise wide governance Granular role-based user access Effectively manage large variety of definitions Customizable term templates Save IT efforts and gain efficiency with integrated software components and collaboration

17 FIRST STEPS WORKFLOW ENABLEMENT FOR POLICY IMPLEMENTATION Collaborative term management Workflows for create, edit and delete of business terms Term type individual workflows Workflow capabilities secured by roles Customer specific workflow designer Workflow in SAS Workflow Studio

18 FIRST STEPS QUALITY: PROFILING/STANDARDIZATION QUICK WINS

19 FIRST STEPS DISTRIBUTION/STANDARDIZATION

20 DATA GOVERNANCE A DAY IN THE LIFE OF A DATA STEWARD

21 SAS DATA MANAGEMENT IT S ALL ABOUT THE DATA IN THE RIGHT PLACE efficiently move data between systems AT THE RIGHT TIME support all data delivery latencies and architectures IN THE RIGHT FORM structure, cleanse data for operational systems or analysis TO THE RIGHT PEOPLE govern data use, apply business semantics, collaborate with data

22 PRACTICAL CONSIDERATIONS FOR SHARING PUBLIC INFORMATION DAN FINERTY SAS CANADA

23 SAS DATA MANAGEMENT VALIDATION SAS isn t just about analytics Firms engage with SAS to benefit from data management (ETL, MDM, and DQ), - Forrester WAVE BI platforms 2013: scored SAS highly for the business user capabilities to perform data integration tasks. - Forrester Wave Agile BI high levels of satisfaction with capabilities, in particular with the data access, data filtering and manipulation, advanced descriptive analytics - Gartner Magic Quad 2014 for Advanced Analytics Platform Data access and integration and the ability to support large volumes of data are the main reasons customers choose SAS, according to the survey... - Gartner BI and Analytic Platforms 2014