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Line 9: + + + + + + + − Business Drivers:+ − • Enhanced service delivery+ − • Evidence based policies, research and evaluation+ − • Strengthened reporting capacity and story telling+ − • Enriched internal services+ − • Improved regulation and enforcement+ − + − • 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+ − + + + + − Laying the foundation 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
ISED Departmental Data Strategy Placemat (view source)
Revision as of 15:16, 13 January 2021
, 15:16, 13 January 2021no edit summary
('''Francais''': ) ('''Home Page''': [[ISED Data Strategy]])
('''Francais''': [[Stratégie ministérielle d'ISDE en matière de données]]) ('''Home Page''': [[ISED Data Strategy]])
[[File:ThewayforwardplacematENG.png|none|frame]]
== ISED Departmental Data Strategy: The Way Forward ==
== ISED Departmental Data Strategy: The Way Forward ==
=== Mission: ===
=== Mission: ===
By providing employees with the data, skills and tools they need, we will achieve excellence in serving Canadians and Canadian businesses.
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''' ====
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?
|
|}
==== 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.
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.
== Data Governance ==
=== Laying the foundations: '''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)
=== Building the momentum: Culture shift across ISED ===
* Data Steward and Champion network established
* Implement & oversee data processes
=== Adopting a data culture: 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 ==
=== Laying the foundations: '''Data access challenges are well understood''' ===
* Inventory & evaluation of data assets
* Inventory data sharing agreements
* Assessment of legislative & policy framework for data sharing
=== Building the momentum: '''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
=== Adopting a data culture: '''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 ==
=== Laying the foundations: '''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
=== Building the momentum: '''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
=== Adopting a data culture: '''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 ==
=== Laying the foundations: '''Baseline and identify skills gaps''' ===
* Identify business needs
* Assess data literacy
* Identify data-related learning and development
=== Building the momentum: '''Our workforce begins to transform''' ===
* Develop career path & data competencies
* Upskill and retrain new and existing staff
* Recruitment strategy based on required data skills
=== Adopting a data culture: '''We have trained people to reach our goals''' ===
* Ongoing recruitment & development
* Talent retention initiative
* Data as core competency for career development
== Innovation ==
=== Laying the foundations: '''Foundation for change is established''' ===
* Early opportunities identified
* First data analytics pilots undertaken
* Success stories shared
=== Building the momentum: '''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
=== Adopting a data culture: '''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 ==
=== Laying the foundations: '''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)
=== Building the momentum: '''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
=== Adopting a data culture: '''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
