In my last blog post, I shared what a 360-degree view of data means when centered around data lineage principles. Today, in my final blog post of this data lineage series, I’ll discuss how Perficient’s Data Governance Maturity Model can help enhance your data programs.
Given the power of data lineage to augment and enforce an established enterprise data management program, it often helps to have an experienced partner on the team. Perficient’s Data Lineage Assessment and Strategic Roadmap evaluates how prepared an organization is for developing a data lineage program and creates a strategic and actionable implementation roadmap, from assessment through requirements definition and solution architecture.
As a precursor to the integration of data governance tools around data lineage, it may be prudent to assess the firm’s readiness for such an undertaking. The Perficient Data Governance Maturity Model can provide great insight into the overall state of a data governance program. Here too, Perficient’s experts can provide guidance and expertise in performing an independent, unbiased evaluation of the overall data program, revealing those aspects of governance requiring attention first.
Data Governance Maturity Model
| Level 1: Reactive | Level 2: Aware | Level 3: Proactive | Level 4: Integrated | Level 5: Automated | |
|---|---|---|---|---|---|
| Cadence | No defined policies, manual processes, and no visibility | Departmental policies, project-specific processes, and no visibility | Enterprise policies, some cross-project processes, and some visibility | Enterprise policies and processes, some measurements, and visibility | Complete policy measurements and process visibility as well as continuous improvement |
| Program | No formal program | Informal or ad-hoc program | Formal or ad-hoc program with defined agenda | Formal program with defined agenda and risk mitigation readiness | Semi-automated and formal program with defined agenda and litigation readiness |
| Self Service (Data/BI) | Costly, manual, and outsourced | Discovery still costly, manual, and outsourced | Discovery mostly manual with some IT support | Data discovery and data lineage with profiling and analysis alongside business/IT collaboration | Fully automated, documented, and governed |
| Platform | No platform, decisions stored on local/shared drives, email collaboration, and no automated assessment capability | Team-based governance, content stored on local/shared drives, shared drive collaboration, and user manual assessment | Departmental governance, organizing content stored on shared drives, governance system, and departmental manual assessment | Enterprise governance, enterprise collaboration, and enterprise data architecture | Fully automated, self-learning enterprise governance, and enterprise data architecture |
| Data Remediation & Learning | Manual, ad-hoc, and reactive; no lessons learned | Manual, ad-hoc but proactive; tacit lessons learned | Mostly manual, limited proactiveness, briefly documented knowledge base, and random audits | Automated, data catalog and glossary, as well as limited knowledge base | Self-remediation, self-learning, and a documented knowledge base |
| Data Literacy | Data governance is driven by IT and focused on technical side of execution | While organizational change management (OCM) is a known topic of discussion, it has been “postponed” until later | The business impact of DG is articulated. In addition, the training and communication plans have been outlined and defined | OCM including communication and training are “tasks” for every project and are allocated hours and budget | OCM is centralized; business users are aligned with OCM policies and procedures across the enterprise |
If you are interested in learning more about this topic, consider downloading our Supercharging Data Governance in Financial Services With Data Lineage guide.
If you have any questions about our data lineage capabilities or would like to discuss the topic directly with me, feel free to reach out at David.Willner@perficient.com.
