Data Management Strategic Planner
TechWish | Minneapolis | www.resume-library.com |
Sample Tasks
Program management of data management projects and initiatives.
Data Management strategic goals, objectives, and roadmap.
Data management maturity assessments.
Key metrics and dashboards to measure and track data and program maturity.
Data focused policies, standards, and operational processes.
Provide knowledge transfer.
Qualifications
Good understanding of the concepts, methods and techniques used:
Analytics, for example diagnostic, descriptive, predictive and prescriptive.
AI, for example graph analysis, machine learning and natural language processing.
Data management, for example data integration (ETL) or metadata.
Data architecture, for example the difference between data warehouse, data lake or data hub.
Data structures, for example structured, semi structured and unstructured data.
Data governance, for example MDM, data quality and data stewardship practices.
Statistical skills, for example understanding the difference between correlation and causation.
Project management capabilities, for example understanding of project management concepts to organize their own work and the ability to collaborate with project managers to align business expectations with the D&A team delivery capabilities.
For this, the role can collaborate with project managers.
Business case development, for example to help develop support for experimenting with selected use cases or measuring the impact/business value created. For this, the role can collaborate with business analysts.
Decision modeling, for example support decision makers and improve complicated decisions that involve trade-offs among alternative courses of action by using decision-problem models. For this, the role can collaborate with decision engineers.
UX/design, for example by creating products and visualizations that are easy to work with and support the activities required by the end users. For this, the role can collaborate with the design team.
Basic Understanding/Principles for:
Programming languages like SQL, Python or R and notebooks like R Studio or other tools.
Data integration tools like Informatica, Talend, and other industry tools.
Analytics and business intelligence tools like Microsoft Power BI or Tableau.
DSML platforms like Dataiku, SAS or IBM Watson Studio.
Communication - ability to convey information to diverse audiences in a way that is easily understood and actionable.
Facilitation- ability to host sessions to elicit ideas from others, understand their issues and encourage group participation.
Creative thinking - ability to frame new concepts that spur use case ideation for business participants and brainstorming with business users about future product and services.
Teamwork – ability to work with business as well IT teams.
Collaboration – ability to foster group problem solving and solution creation with business and technical team members.
Relationship management – ability to create relationships and building trust with internal and external stakeholders quickly.
Storytelling – ability to create a consistent storyline for better understanding and raising data management efforts and literacy.
Influencing – ability to assert ideas and persuade others to gain support across an organization or to adopt new behaviors.
Presentation - comfortable with public speaking and the ability to creatively and concisely express ideas to business and technical audiences.
Program management of data management projects and initiatives.
Data Management strategic goals, objectives, and roadmap.
Data management maturity assessments.
Key metrics and dashboards to measure and track data and program maturity.
Data focused policies, standards, and operational processes.
Provide knowledge transfer.
Qualifications
Good understanding of the concepts, methods and techniques used:
Analytics, for example diagnostic, descriptive, predictive and prescriptive.
AI, for example graph analysis, machine learning and natural language processing.
Data management, for example data integration (ETL) or metadata.
Data architecture, for example the difference between data warehouse, data lake or data hub.
Data structures, for example structured, semi structured and unstructured data.
Data governance, for example MDM, data quality and data stewardship practices.
Statistical skills, for example understanding the difference between correlation and causation.
Project management capabilities, for example understanding of project management concepts to organize their own work and the ability to collaborate with project managers to align business expectations with the D&A team delivery capabilities.
For this, the role can collaborate with project managers.
Business case development, for example to help develop support for experimenting with selected use cases or measuring the impact/business value created. For this, the role can collaborate with business analysts.
Decision modeling, for example support decision makers and improve complicated decisions that involve trade-offs among alternative courses of action by using decision-problem models. For this, the role can collaborate with decision engineers.
UX/design, for example by creating products and visualizations that are easy to work with and support the activities required by the end users. For this, the role can collaborate with the design team.
Basic Understanding/Principles for:
Programming languages like SQL, Python or R and notebooks like R Studio or other tools.
Data integration tools like Informatica, Talend, and other industry tools.
Analytics and business intelligence tools like Microsoft Power BI or Tableau.
DSML platforms like Dataiku, SAS or IBM Watson Studio.
Communication - ability to convey information to diverse audiences in a way that is easily understood and actionable.
Facilitation- ability to host sessions to elicit ideas from others, understand their issues and encourage group participation.
Creative thinking - ability to frame new concepts that spur use case ideation for business participants and brainstorming with business users about future product and services.
Teamwork – ability to work with business as well IT teams.
Collaboration – ability to foster group problem solving and solution creation with business and technical team members.
Relationship management – ability to create relationships and building trust with internal and external stakeholders quickly.
Storytelling – ability to create a consistent storyline for better understanding and raising data management efforts and literacy.
Influencing – ability to assert ideas and persuade others to gain support across an organization or to adopt new behaviors.
Presentation - comfortable with public speaking and the ability to creatively and concisely express ideas to business and technical audiences.
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