Big Data in Government: What Are the Talent Needs? McMaster University Big Data Forum

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1 Big Data in Government: What Are the Talent Needs? McMaster University Big Data Forum

2 Big data in government The Canadian government holds large amounts of administrative and transactional, as well as data collected for statistical purposes Data is usually highly structured Data quality varies, tends to be higher for fields used for administrative purposes Potential for collection of data from interactions with public. Difficult to know how much is being collected, how structured, quality Could include data on interactions with government web sites, government employees Government potentially can use data from non-government sources, whether purchased or acquired from open data resources. Again, difficult to know extent of present use 2

3 Potential uses of big data by government Some uses are likely to be driven by predictive correlations, rather than by experimental methods or structural models Border security uses a wide range of data, including non-government sources, timeliness critical Analysis of crime patterns is used to improve policing Health data analysis used to detect illness, improve care and care delivery Integrity (detection of fraud, errors) uses a wide range of data, potentially including non-government sources. High value of timeliness (detect before the check is issued) Other uses are more likely to involve experimentation or structural modelling Improving program delivery and quality of interactions with government Improving program operations Experimental evaluation of program designs (possible interface with behavioural economics) Research in support of policy 3

4 Big data in government and business Government is not driven to use big data to compete for customers, profits But many government uses have a bottom line in reduced costs, increased security, better services, program efficiencies These are important considerations in a period of budgetary pressures High degree of public scrutiny and sensitivity to government intrusions leads to quite risk-averse environment Government also faces a range of legal and regulatory requirements related to privacy, safeguarding of individual information 4

5 How to do big data in government Define business requirements Need to have a sense of long-term business opportunities, but Build incrementally, don t take Field of Dreams approach Develop the architecture for use of big data for policy purposes Using existing data sets Combining outside data sets with government data sets Creating new data, for example, through on-line experiments Confidentiality considerations dictate use internally or at Statistics Canada Plan to augment and iterate Identify gaps Iterate Leverage the substantive effort to build talent on an incremental basis In collaboration with outside parties to the extent possible 5

6 Talent needs for big data in government Need to develop managerial capacity to carry out big data projects Requires managers with sufficient knowledge of big data methods, potential and limitations Need through understanding of business requirements Need ability to adapt big data approaches to government environment Need technical capacity to implement big data applications Internal capacity versus purchased services will be an issue Context of fiscal constraints, potentially competing information systems priorities Renewing infrastructure Implementing open data initiatives For policy applications, same skill requirements as above, plus Knowledge of policy issues, modelling skills, skills in establishing, implementing, analysing experiments Some of these skills exist or will be developed internally, some from hiring new graduates and others, some from external collaborations 6

7 Models for external collaboration on big data projects Models for collaboration with academic partners include External researchers access to data at trusted sites Collaboration between external, internal researchers Expand data availability Confidentiality considerations continue to apply, even for data stripped of personal identifiers in light of big data capabilities for re-idenfication These projects will compete for knowledgeable personnel during the building phase of establishing infrastructure to best use big data 7

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