Trust In Data. Conditio Sine Qua Non For Shared Data Value. SAS Presentation, 21 Oct instance Congress

Transcription

1 Trust In Data Conditio Sine Qua Non For Shared Data Value SAS Presentation, 21 Oct instance Congress Copyright 2014, SAS Institute Inc. All rights reserved.

2 Data Needs To Flow To Realize Its Full Potential

3 AN EVOLUTION IN DATA SHARING SILO INTRA INTER VALUE VALUE

4 SHARED DATA VALUE: GENERATING EFFICIENCIES

5 SHARED DATA VALUE: BETTER PREDICTIONS

6 THE BENEFITS OF SHARED DATA VALUE FOR PRIVATE/PUBLIC SECTOR The aggregate economic impact from applications based on Open Data across the EU27 economy is estimated to be 140 billion annually. Source:

7 LACK OF DATA QUALITY = LACK OF TRUST Source: InsightSquared infographic

8 MISALIGNMENT OF CONCERNS BETWEEN STAKEHOLDERS = MISTRUST 72% of European citizens are concerned that their personal data may be misused, and they are particularly worried that companies may be passing on their data to other companies without their permission. Source:

9 A LACK OF TRUST CAN PULL THE ECOSYSTEM APART & DESTROY VALUE Source:

10 DATA GOVERNANCE TO REINFORCE / REINSTALL TRUST IN DATA Responsible for championing, sanctioning and raising awareness & support for the data governance program and information as an asset. The organizing framework for establishing strategy, objectives and policies for corporate data. Responsible for defining, monitoring, educating and advocating for appropriate usage & management of critical enterprise information assets. The tactical execution of day-to-day activities required to implement data governance policies and ensure information is created, stored and utilized appropriately.

11 SIX PRIMARY FUNCTIONS OF DATA MANAGEMENT TO FOSTER TRUST

12 DATA REQUIREMENTS QUESTIONS Do you proactively address information or data requirements as a step in your business analysis / requirements gathering process?

13 DATA ARCHITECTURE QUESTIONS Do you have data modelling standards in place? Do you capture policies, definitions and rules on your data? Do you promote the use of common standard codes and definitions? Do you make them visible internally / externally? Is your infrastructure reading for Data-As-A-Service? Do you have APIs, Service-Oriented-Architecture mindset?

14 DATA ADMINISTRATION QUESTIONS Do you know and communicate the validity date of your data? Value Big Data Data In Motion Traditional Data Data In Rest Time

15 DATA ADMINISTRATION QUESTIONS Is data security taken seriously at your organization? If not, why not? Who has access to the customer data you re collecting? And who is accessing this data? What proactive steps have you taken to make sure the data you re collecting is secure? Can you and how long does it take to answer a citizen to his question of How is my data being used / secured and who had access to it? Do you avoid unnecessary replication of data?

16 DATA QUALITY QUESTIONS Do you know the current health of your data? Do you monitor it? Do you have controls in place to detect and fix quality issues as soon as they happen? Is data quality the sole responsibility of IT or is it a shared responsibility between business and IT? Do you have a data quality service level agreement in place? How do you make the cost of bad data quality visible in the organization? Is it linked to business metrics?

17 DATA QUALITY QUESTIONS

18 METADATA MANAGEMENT QUESTIONS Do your users know what information is available? Where it is? How to get it? What it can(not) be used for?

19 PRIVACY & COMPLIANCE QUESTIONS? Are you categorizing your data around privacy constraints? All data is not considered equal. Do you understand how and where your data is changing hands? Do you have designated data stewards who understand the data lineage, from a system, people & process perspective? Does your organization have a privacy policy? Do you tell your customers when a request is made for their data? How long would it take you to gather this info?

20 IMPORTANT QUESTION: WHO IS OWNER OF THE DATA? Volunteered Data Observed Data Inferred Data

21 TAKEAWAYS Data needs to flow and be shared to realize its full potential. The value of data sharing is huge, both for the private and public sector. Trust is key to keep data flowing between all stakeholders. Quality, misalignment of concerns & security breaches can instill mistrust and destroy shared data value. A data governance framework needs to be in place (both on an intra & inter-organization level) to reinstall trust and realize the maximum shared data value potential.

22 QUESTIONS? Copyright 2014, SAS Institute Inc. All rights reserved.

23 MATHIAS COOPMANS Senior Business Strategist Direct: Mobile: Twitter: Copyright 2014, SAS Institute Inc. All rights reserved.