Stratégie ministérielle d'ISDE en matière de données

(Francais: Stratégie ministérielle d'ISDE en matière de données) (Home Page: ISED Data Strategy)

ISED Departmental Data Strategy: The Way Forward

Vision:

ISED leverages the power of data to foster a growing, competitive and knowledge based economy.

Mission:

By providing employees with the data, skills and tools they need, we will achieve excellence in serving Canadians and Canadian businesses.

Business Drivers Enhanced service delivery Evidence based policies, research and evaluation Strengthened reporting capacity and story telling Enriched internal services Improved regulation and enforcement
Goals Canadians and Canadian businesses are better informed and served ISED adopts a data culture where data are discoverable, accessible, secure and of high quality ISED's talent base is enhanced with new skills and experimentation is promoted Public trust is honoured by ensuring that data are handled ethically and securely

What are we doing?

There are six pillars of the ISED Data Strategy, each of which has high level initiatives in three phases of implementation; laying the foundation, building the momentum and adopting a data culture. The following table addresses each pillar by phase of implementation.

	Laying the foundations	Building the momentum	Adopting a data culture
Data governance _____________	Data-related leadership established Chief Data Office Data Governance Structure Identify key data stewards & champions Identify processes to manage data at enterprise level (sharing & storing protocols) _______________________	Culture shift across ISED Data Steward and Champion network established Implement & oversee data processes _______________________	People value their data and treat it as an asset Monitor adoption of data processes & standards aligned with GoC Data Stewards facilitate access to data _______________________
Data Access _____________	Data access challenges are well understood Inventory & valuation of data assets Inventory data sharing agreements Assessment of legislative & policy framework for data sharing _______________________	Work on transformative data access initiatives Develop common consent statement for data sharing Create roadmap for a data sharing hub Partner with Sectors to pilot data sharing and data integration Investigate data sharing opportunities across all levels of government _______________________	ISED data are open by default Launch common consent statement for data sharing & monitor data sharing Deploy self-service data sharing hub Expand data sharing to all levels of government _______________________
Data Framework _____________	Data framework and models are developed Data standards, including Common Business Profile and dictionaries, developed and piloted Framework for ethical, secure use & storage of data developed Detailed data models for collection, acquisition, processing and storage conceptualized and piloted _______________________	Put in place data framework and models Process to handle and use data are known Quality assurance standards developed Data standards launched Framework for ethical & secure data use implemented Data models in place across the department _______________________	Protection of data via privacy by design Staff confidently conduct work with high quality data, with well-established data standards, definitions, and the privacy and security of Canada's data assured _______________________
Talent _____________	Baseline and identify skills gaps Identify business needs Assess data literacy Identify data-related learning and development _______________________	Our workforce begins to transform Develop career path & data competencies Upskill and retrain new and existing staff Recruitment strategy based on required data skills _______________________	We have trained people to reach our goals Ongoing recruitment & development Talent retention initiative Data as core competency for career development _______________________
Innovation _____________	Foundation for change is established Early opportunities identified First data analytics pilots undertaken Success stories shared _______________________	Experimentation begins to yield results Roll-out successful pilots to other sectors Continue to communicate approaches and use cases Identify mechanism for making decisions on proposed innovative solutions _______________________	Innovation becomes common business practice Initiate departmental analytics support Develop Free Agent data talent matching service (data-skilled talent pool for short-term work) Establish data science pipeline _______________________
Technology _____________	Higher organizational awareness of existing solutions Determine technology requirements Establish technology strategy Experiment with technology solutions for data (management, sharing, creation, data analytics) Roadmap for Client Relationship Management (CRM) _______________________	New tools and processes put in place Implement technology strategy Business processes for use of new technologies On-site storage, common data software suite Business analytics tools available _______________________	Internal technology keeps pace with innovation Integrated suite of IT tools for data and analytics Departmental Client Relationship Management with Common Business Profile Continual evaluation of Next Generation technology with new tech use on demand _______________________