Roles Strategy & Transformation
Business Analyst
Accountable for eliciting, analysing and managing requirements through a change and for validating solutions against them.
3tasks in this job
10skills it uses
6tools named
The skills this job leans on most
- 1Writing verifiable requirements and acceptance criteriaNeeded in 3 of 3 tasks
- 2Diagnosing operational handoffs and flowNeeded in 2 of 3 tasks
- 3Mapping proposed process changes and control impactsNeeded in 2 of 3 tasks
- 4Eliciting needs through interviews, workshops and observationNeeded in 2 of 3 tasks
- 5Maintaining requirements traceability and change controlNeeded in 2 of 3 tasks
ToolsMicrosoft ExcelMicrosoft Power BIMicrosoft SQL Server (with SSMS)SnowflakePower QueryJiraAzure DevOpsSalesforceMicrosoft Dynamics 365 Sales and Customer InsightsMicrosoft 365 CopilotCelonisSAP SignavioMicrosoft VisioServiceNow
All 3 tasks, where people get stuck and all 10 skills
Tasks
- Verify project deliverables and accept a controlled handoff
- Elicit, analyse and manage requirements for a data, analytics or system change
- Analyse a current business process from event and operational data and define the future-state process
Where people get stuck
All skills
- Diagnosing operational handoffs and flow
- Eliciting needs through interviews, workshops and observation
- Mapping proposed process changes and control impacts
- Writing verifiable requirements and acceptance criteria
- Defining measurable outcomes and leading indicators
- Escalating unresolved risks with evidence and clear ownership
- Maintaining a risk register with owners, triggers and responses
- Mapping customer journeys and evidence gaps
- Mapping stakeholders' decisions, constraints and needs
- Specifying decision-useful reports
Paths to start
Tool Path
Excel for Analysis and Decision Models
Build and check Excel workbooks others can trust.
- Modules
- 5 open
- Runs in
- Your browser
Skill Path
Discovering Requirements and Defining Metrics
Turn stakeholder needs into verifiable requirements and governed metric definitions with owners, grain and acceptance tests.
- Modules
- 5 open
- Practice data
- Raket Parts
Coming soonService, Process and Operations Improvement
5tasks in this job
64skills it uses
14tools named
The skills this job leans on most
- 1Diagnosing operational handoffs and flowNeeded in 3 of 5 tasks
- 2Writing verifiable requirements and acceptance criteriaNeeded in 3 of 5 tasks
- 3Mapping proposed process changes and control impactsNeeded in 2 of 5 tasks
- 4Coordinating accountable handoffs between teamsNeeded in 1 of 5 tasks
- 5Verifying project progress against accepted outcomesNeeded in 1 of 5 tasks
ToolsMicrosoft ExcelMicrosoft Power BIMicrosoft SQL Server (with SSMS)SnowflakePower QueryJira+ 8 more
All 5 tasks, where people get stuck and all 64 skills
Tasks
- Define and govern a KPI metric contract
- Assess data quality and fitness for a stated use
- Verify project deliverables and accept a controlled handoff
- Elicit, analyse and manage requirements for a data, analytics or system change
- Analyse a current business process from event and operational data and define the future-state process
Where people get stuck
- Maintaining requirements traceability and change control
- Discovering process variants from event logs
All skills
- Coordinating accountable handoffs between teams
- Diagnosing operational handoffs and flow
- Mapping proposed process changes and control impacts
- Verifying project progress against accepted outcomes
- Writing verifiable requirements and acceptance criteria
- Analysing event sequences, states and durations
- Applying data classification and handling rules
- Assessing data source credibility and fitness for a question
- Assessing lawful basis, purpose compatibility and minimisation for data reuse
- Assigning and operating data ownership and stewardship
- Calculating and interpreting percentages, rates and ratios
- Choosing an analytical method to fit the question and data
- Choosing and justifying missing-data treatments
- Combining tables safely: cardinality, fan-out and conservation of totals
- Comparing groups
- Decomposing one's own tasks for AI assistance
- Defining measurable outcomes and leading indicators
- Defining the analysis population: filters, nulls, dates and time zones
- Describing distributions with summaries and plots
- Designing and interpreting hypothesis tests
- Designing and validating digital analytics event measurement
- Designing and versioning data contracts for consumers
- Designing efficient and reproducible investigations
- Diagnosing data quality exceptions
- Diagnosing duplicate records
- Diagnosing incorrect query and calculation results
- Discovering process variants from event logs
- Eliciting needs through interviews, workshops and observation
- Eliciting the decision behind an analytical request
- Escalating unresolved risks with evidence and clear ownership
- Establishing and declaring data grain
- Estimating quantities and differences with intervals
- Exploring data to find patterns that survive validation
- Fitting, checking and interpreting inferential regression models
- Forecasting project cost and schedule from progress evidence
- Formulating answerable data questions
- Governing shared data definitions
- Influencing change without formal authority
- Interpreting averages, weighted measures and mix effects
- Interpreting policy scope and delegated authority limits
- Investigating anomalies
- Investigating procurement spend leakage and duplicate commitments
- Judging whether a change exceeds normal variation
- Maintaining a risk register with owners, triggers and responses
- Maintaining requirements traceability and change control
- Managing master data identities and exceptions
- Mapping customer journeys and evidence gaps
- Mapping stakeholders' decisions, constraints and needs
- Monitoring data quality and freshness in production
- Planning delivery dependencies and the critical path
- Preparing analysis-ready datasets reproducibly
- Prioritising work by evidenced value, cost, risk and confidence
- Profiling data
- Reading business metrics
- Reading charts and dashboards correctly, including their state
- Repairing data defects reversibly under owner authority
- Selecting charts for evidence and decisions
- Specifying decision-useful reports
- Standardising and cleaning data under agreed rules
- Testing competing explanations with discriminating evidence
- Training reproducible machine learning models
- Working through stakeholder conflict over evidence and responsibility
- Writing data quality rules
- Writing evidence-led findings and auditable recommendations with their limits
Paths to start
Skill Path
Data Preparation: Cleaning, Repair and Reconciliation
Check whether a table is fit for the job, then clean, repair and reconcile it with the evidence to back it.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Exploratory Data Analysis and Pattern Discovery
Describe a distribution honestly and decide which unusual records need checking before anyone acts.
- Modules
- 5 open
- Practice data
- Raket Parts
Tool Path
SQL for Analysis
Answer real business questions with SQL, from your first query to finding why a number moved.
- Modules
- 5 open
- Runs in
- Your browser
5tasks in this job
72skills it uses
13tools named
The skills this job leans on most
- 1Diagnosing operational handoffs and flowNeeded in 3 of 5 tasks
- 2Writing verifiable requirements and acceptance criteriaNeeded in 3 of 5 tasks
- 3Mapping proposed process changes and control impactsNeeded in 2 of 5 tasks
- 4Coordinating accountable handoffs between teamsNeeded in 1 of 5 tasks
- 5Verifying project progress against accepted outcomesNeeded in 1 of 5 tasks
ToolsMicrosoft Power BIMicrosoft PurviewMicrosoft SQL Server (with SSMS)SnowflakeSalesforceServiceNow+ 7 more
All 5 tasks, where people get stuck and all 72 skills
Tasks
- Define and govern a KPI metric contract
- Assess data quality and fitness for a stated use
- Verify project deliverables and accept a controlled handoff
- Elicit, analyse and manage requirements for a data, analytics or system change
- Analyse a current business process from event and operational data and define the future-state process
Where people get stuck
- Maintaining requirements traceability and change control
- Discovering process variants from event logs
All skills
- Coordinating accountable handoffs between teams
- Diagnosing operational handoffs and flow
- Mapping proposed process changes and control impacts
- Verifying project progress against accepted outcomes
- Writing verifiable requirements and acceptance criteria
- Analysing event sequences, states and durations
- Applying data classification and handling rules
- Assessing data source credibility and fitness for a question
- Assessing lawful basis, purpose compatibility and minimisation for data reuse
- Assigning and operating data ownership and stewardship
- Calculating and interpreting percentages, rates and ratios
- Choosing an analytical method to fit the question and data
- Choosing and justifying missing-data treatments
- Combining tables safely: cardinality, fan-out and conservation of totals
- Comparing groups
- Decomposing one's own tasks for AI assistance
- Defining measurable outcomes and leading indicators
- Defining the analysis population: filters, nulls, dates and time zones
- Describing distributions with summaries and plots
- Designing and interpreting hypothesis tests
- Designing and validating digital analytics event measurement
- Designing and versioning data contracts for consumers
- Designing efficient and reproducible investigations
- Diagnosing data quality exceptions
- Diagnosing duplicate records
- Diagnosing incorrect query and calculation results
- Diagnosing misleading data visualisations
- Disclosing AI contribution to professional work
- Discovering process variants from event logs
- Eliciting needs through interviews, workshops and observation
- Eliciting the decision behind an analytical request
- Escalating unresolved risks with evidence and clear ownership
- Establishing and declaring data grain
- Estimating quantities and differences with intervals
- Exploring data to find patterns that survive validation
- Fitting, checking and interpreting inferential regression models
- Forecasting project cost and schedule from progress evidence
- Formulating answerable data questions
- Giving specific developmental feedback on data and AI work
- Governing shared data definitions
- Independently checking analytical conclusions and claims
- Influencing change without formal authority
- Interpreting averages, weighted measures and mix effects
- Interpreting policy scope and delegated authority limits
- Investigating anomalies
- Investigating procurement spend leakage and duplicate commitments
- Judging the materiality of defects and deficiencies for the intended use
- Judging whether a change exceeds normal variation
- Maintaining a risk register with owners, triggers and responses
- Maintaining requirements traceability and change control
- Managing master data identities and exceptions
- Mapping customer journeys and evidence gaps
- Mapping stakeholders' decisions, constraints and needs
- Monitoring data quality and freshness in production
- Planning delivery dependencies and the critical path
- Preparing analysis-ready datasets reproducibly
- Prioritising work by evidenced value, cost, risk and confidence
- Profiling data
- Reading business metrics
- Reading charts and dashboards correctly, including their state
- Repairing data defects reversibly under owner authority
- Sampling and reviewing a team's work against standards
- Selecting charts for evidence and decisions
- Specifying decision-useful reports
- Standardising and cleaning data under agreed rules
- Testing competing explanations with discriminating evidence
- Training reproducible machine learning models
- Verifying AI-assisted outputs against sources
- Verifying reports and dashboards before and after release
- Working through stakeholder conflict over evidence and responsibility
- Writing data quality rules
- Writing evidence-led findings and auditable recommendations with their limits
All tools
- Microsoft Power BI
- Microsoft Purview
- Microsoft SQL Server (with SSMS)
- Snowflake
- Salesforce
- ServiceNow
- Microsoft Excel
- Jira
- Azure DevOps
- Microsoft 365 Copilot
- Celonis
- SAP Signavio
- Microsoft Visio
Paths to start
Skill Path
Data Preparation: Cleaning, Repair and Reconciliation
Check whether a table is fit for the job, then clean, repair and reconcile it with the evidence to back it.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Exploratory Data Analysis and Pattern Discovery
Describe a distribution honestly and decide which unusual records need checking before anyone acts.
- Modules
- 5 open
- Practice data
- Raket Parts
Tool Path
SQL for Analysis
Answer real business questions with SQL, from your first query to finding why a number moved.
- Modules
- 5 open
- Runs in
- Your browser
About the role
Accountable for eliciting, analysing and managing requirements through a change and for validating solutions against them. Delivers requirement sets, process models and acceptance criteria with success metrics that can be verified from data. Differs from Product Manager in defining what a solution must do rather than deciding product value.
Also called Business Systems Analyst, Business Process Analyst