Data Governance & Reporting
It isn't as simple as making your data secure, you need to define the path to and from the single source of the truth, from the system storage to the reporting usage, from who creates data to who uses it and why.
We are here to help.
To better manage data governance and reporting of said data within your business, please consider the following:
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Data governance is the framework of policies, standards, roles, processes, and controls that ensure an organization’s data is:
- Accurate
- Consistent
- Secure
- Available
- Compliant
It defines who can do what with data, when, and under what conditions.
This includes the presentation of data and how an organization turns data into actionable information.
Control and continual improvement over data management needs to follow a good and true development life cycle.
- Requirements gathering & Specification validation
- Design & build to specification
- Testing and test plans
- Deployment & Release controls
- On-going maintenance & version control
And not withstanding:
- Standard definitions for metrics
- Approved datasets (“single source of truth”)
- Naming conventions
- Access permissions
1. Policies & Standards
Rules that define how data is handled across its lifecycle:
- Data classification (sensitive, confidential, public)
- Naming conventions
- Data retention rules
- Compliance (e.g., GDPR, HIPAA)
2. Roles & Responsibilities
Clearly defined ownership:
- Data Owners – accountable for data quality and usage
- Data Stewards – manage data definitions and consistency
- Data Custodians – handle storage, security, and infrastructure
3. Data Quality Management
Ensures data is:
- Complete
- Accurate
- Timely
- Valid
Typical activities:
- Data validation
- Data cleansing
- Monitoring quality metrics
4. Metadata Management
Managing “data about data”:
- Data dictionaries
- Data lineage (where data comes from and flows)
- Business definitions
5. Security & Privacy Controls
Protecting sensitive data:
- Role-based access control (RBAC)
- Encryption
- Audit logging
- Privacy compliance
6. Data Lifecycle Management
Controls data from creation to retirement:
- Creation/ingestion
- Storage
- Usage
- Archival
- Deletion
7. Reporting Platforms & Tools
There are many avenues to presenting data to consumers, including but not limited to:
- Power BI
- Tableau
- SQL Server Reporting Services (SSRS)
- Excel-based reporting
- Cloud analytics tools
The following base objectives exist:
- Improve decision-making through reliable data
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Consistent and trusted insights
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- Reduce risk (legal, compliance, security)
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Provide transparency
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- Enable data sharing across departments
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Support strategic and operational goals
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These are typically delivered via the following formats:
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Operational Reporting
- Hourly, shift, day, weekly reporting of performance
- Short Interval control measures
- Targets
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Analytical Reporting
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Trends and insights over define periods
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Regulatory & Compliance Reporting
- Corporate oversight
- Standards body
- Governmental regulations
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Executive Dashboards
- Hight-level KPIs
- Visual summaries for management
Typical feeds for reporting:
- Internal
- Manually recorded data
- Unstructured Excel workbooks
- Non-integrated software sources
- Databases, data warehouses and datamarts
- External data lakes and data hubs
- Other propriatory external data sources
When it comes to data governance and ultimately the reporting of good sound data we find that many custodians of the company's data fail to manage who creates data and who consumes data, and seldom asks the question why a user needs access to specific data.
Firstly, your organisation needs to understand what data is has and how it connects. What data feeds business processes; what comes in and what goes out to the next process in line.
Once an audit of your data estate has been concluded and a clear picture of what you have, what you use and what drives your business, you need to slow down.