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Line 33: − {|+ − !+ − !+ − + − ! − − ! − === <u>Adopting a data culture</u> === − |- − | − ==== '''Data governance''' ==== − _____________ − |'''Data-related leadership established''' Line 51:
Line 42: − _______________________+ − |'''Culture shift across ISED''' − ___________________________________________+ − |'''People value their data and treat it as an asset''' − __________________________+ − |-+ − |+ − ==== '''Data Access''' ====+ − _____________ − |'''Data access challenges are well understood''' − − _______________________+ − |'''Work on transformative data access initiatives''' − ___________________________________________+ − |'''ISED data are open by default'''+ − _______________________+ − |-+ − |+ − ==== '''Data Framework''' ==== − _____________ − |'''Data framework and models are developed''' − _______________________+ − |'''Put in place data framework and models'''+ − ___________________________________________+ − |'''Protection of data via privacy by design'''+ − _______________________+ − |-+ − |+ − − _____________ − |'''Baseline and identify skills gaps''' − _______________________+ − |'''Our workforce begins to transform'''+ − ___________________________________________+ − |'''We have trained people to reach our goals'''+ − _______________________+ − |-+ − |+ − + − _____________ − |'''Foundation for change is established''' − _______________________+ − |'''Experimentation begins to yield results'''+ − ___________________________________________+ − |'''Innovation becomes common business practice'''+ − _______________________+ + + + + + + + + + + + + + + + + + + + + + + + +
ISED Departmental Data Strategy Placemat (view source)
Revision as of 16:14, 13 January 2021
, 16:14, 13 January 2021no edit summary
==== 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 ==
=== <u>Laying the foundations</u> ===
=== Laying the foundations: '''Data-related leadership established''' ===
=== <u>Building the momentum</u> ===
* Chief Data Office
* Chief Data Office
* Data Governance Structure
* Data Governance Structure
* Identify processes to manage data at enterprise level (sharing & storing protocols)
* Identify processes to manage data at enterprise level (sharing & storing protocols)
=== Building the momentum: Culture shift across ISED ===
* Data Steward and Champion network established
* Data Steward and Champion network established
* Implement & oversee data processes
* 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
* Monitor adoption of data processes & standards aligned with GoC
* Data Stewards facilitate access to data
* Data Stewards facilitate access to data
== Data Access ==
=== Laying the foundations: '''Data access challenges are well understood''' ===
* Inventory & evaluation of data assets
* Inventory & valuation of data assets
* Inventory data sharing agreements
* Inventory data sharing agreements
* Assessment of legislative & policy framework for data sharing
* Assessment of legislative & policy framework for data sharing
=== Building the momentum: '''Work on transformative data access initiatives''' ===
* Develop common consent statement for data sharing
* Develop common consent statement for data sharing
* Create roadmap for a data sharing hub
* 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
* 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
* Launch common consent statement for data sharing & monitor data sharing
* Deploy self-service data sharing hub
* Deploy self-service data sharing hub
* Expand data sharing to all levels of government
* 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
* 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
* 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
* Process to handle and use data are known
* Quality assurance standards developed Data standards launched
* Quality assurance standards developed Data standards launched
* Framework for ethical & secure data use implemented
* Framework for ethical & secure data use implemented
* Data models in place across the department
* 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
* 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''' ===
==== '''Talent''' ====
* Identify business needs
* Identify business needs
* Assess data literacy
* Assess data literacy
* Identify data-related learning and development
* Identify data-related learning and development
=== Building the momentum: '''Our workforce begins to transform''' ===
* Develop career path & data competencies
* Develop career path & data competencies
* Upskill and retrain new and existing staff
* Upskill and retrain new and existing staff
* Recruitment strategy based on required data skills
* Recruitment strategy based on required data skills
=== Adopting a data culture: '''We have trained people to reach our goals''' ===
* Ongoing recruitment & development
* Ongoing recruitment & development
* Talent retention initiative
* Talent retention initiative
* Data as core competency for career development
* Data as core competency for career development
== Innovation ==
==== '''Innovation''' ====
=== Laying the foundations: '''Foundation for change is established''' ===
* Early opportunities identified
* Early opportunities identified
* First data analytics pilots undertaken
* First data analytics pilots undertaken
* Success stories shared
* Success stories shared
=== Building the momentum: '''Experimentation begins to yield results''' ===
* Roll-out successful pilots to other sectors
* Roll-out successful pilots to other sectors
* Continue to communicate approaches and use cases
* Continue to communicate approaches and use cases
* Identify mechanism for making decisions on proposed innovative solutions
* Identify mechanism for making decisions on proposed innovative solutions
=== Adopting a data culture: '''Innovation becomes common business practice''' ===
* Initiate departmental analytics support
* Initiate departmental analytics support
* Develop Free Agent data talent matching service (data-skilled talent pool for short-term work)
* Develop Free Agent data talent matching service (data-skilled talent pool for short-term work)
* Establish data science pipeline
* Establish data science pipeline
== Technology ==
=== Laying the foundations: '''Higher organizational awareness of existing solutions''' ===
* Early opportunities identified
* First data analytics pilots undertaken
* Success stories shared
=== Building the momentum: '''New tools and processes put in place''' ===
* 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
{|
!
!
=== <u>Laying the foundations</u> ===
!
=== <u>Building the momentum</u> ===
!
=== <u>Adopting a data culture</u> ===
|-
|-
|
|
