- Data issues are deeply rooted and extremely complex. Not only do organizations have trouble choosing a starting point for bad data, but they also have difficulty finding the root cause of the issue. As a result, data audits can be long, tedious initiatives, that offer little insight into the data issues.
- Traditional data audits are too narrowly focused on security and compliance. Availability and trust issues need to be uncovered as well.
- Organizations are not aware of all their data sources.
- Organizations are conducting data audits that are ineffective, only focusing on issues and failing to get to the root of the problem.
- Data audits are failing to provide insight into possible solutions and problem resolution.
- A combination of technical profiling and user profiling will help you understand where issues are and why they exist.
- An annual data audit initiative will continually revise and fine-tune ongoing practices, processes, and procedures for the management and handling of data within the organization.
- You can’t do everything at once. Pick a process, see some early victories, gain momentum, and repeat.
Impact and Result
- Prepare for the audit: Prepare in advance to make the audit process smoother and less time-intensive. Identify and create an inventory of all data sources that are within the scope of your data audit. Use these data sources to understand which users would provide a valuable, insightful interview. Schedule interviews and complete technical profiling.
- Conduct audit: Interview relevant stakeholders identified in the audit preparation. Use insight from these interviews to complete user profiling. Update the data sources and data inventory with any information that may have been missed.
- Analyze and assess results: Get to the root of the problem through conducting a root cause analysis. Find out why the issues are occurring.
- Correct plan: You know what the issues are and you now know why they are being caused. Create the corrective plan through prioritizing initiatives and data activities. Use a combination of short-term and long-term initiatives.
This guided implementation is a five call advisory process.
Guided Implementation #1 - Prepare for a data audit
Call #1 - Determine the benefits a data audit will provide.
Call #2 - Prepare a context diagram, stakeholder interview schedule, and data source inventory for review.
Guided Implementation #2 - Conduct the data audit and review results
Call #1 - Complete user interviews and discuss results.
Call #2 - Complete the root cause analysis/ fishbone diagram. Discuss results.
Call #3 - Discuss the corrective plan and the short-term and long-term plans to rectify data issues.
Book Your Workshop
Onsite workshops offer an easy way to accelerate your project. If you are unable to do the project yourself, and a Guided Implementation isn't enough, we offer low-cost onsite delivery of our project workshops. We take you through every phase of your project and ensure that you have a roadmap in place to complete your project successfully.
Module 1: Make the Case and Structure the Project
- Understand why it is important to treat data as an asset and how data fits into the corporate strategy.
- Realize the value of a data audit and how it can help you efficiently manage your data to gain a competitive advantage.
- Explore the affects new trends in trust, availability, compliance, and security will pose on your organization.
- Identify drivers, goals, and objectives for conducting a data audit.
- Create the project team.
- Complete data audit charter.
Key Benefits Achieved
- An understanding of the benefits of a data audit and whether it is right for your organization.
- Completed data audit project charter to be used to gain buy stakeholder buy-in.
Understand the corporate strategy.
- A go/ no-go decision for conducting the data audit.
Determine the organization's data pain points.
- List of organizational data pain points.
Identify availability, trust, compliance, and security issues.
Identify the drivers, goals, and objectives for the data audit.
Scope the project.
Assemble the project team.
- Data audit project team.
Complete the data audit charter.
- Completed data audit project charter
Module 2: Prepare and Conduct the Data Audit
- Prepare for the audit, identify and create an inventory of all data sources and resources that end users require to do their jobs, determine who is responsible for data sources, and summarize audit findings.
- Conduct the audit by completing user profiling and technical profiling.
Key Benefits Achieved
- Understand how the audit process works, how data is created, and archived.
- A combination of technical profiling and user profiling will help the client identify where issues are and why they exist.
Create a context diagram.
Document data sources in the Data Source Inventory Tool.
- A comprehensive list of all data sources within the data audit project scope.
Identify users for interviews.
- Completed Data Audit Interview Schedule.
Review results of the technical assessment. Discuss and draw hypothesis.
- A completed technical assessment identifying problem data trust issues.
Conduct a mock interview.
Complete the Data Audit Scorecard Tool.
- A completed Data Source Inventory Template to act as a point of reference for all data sources within the project scope.
Update the data context diagram.
Summarize key issues.
Module 3: Review and Analyze Data Audit Findings
- Analyze data audit results and identify the root cause of data inefficiencies.
Key Benefits Achieved
- Understand why data issues and inefficiencies exist and what the cause is.
Perform a root cause analysis using fishbone diagrams.
- A completed root cause analysis with a thorough understanding of the issues contributing to trust, availability, compliance, and security issues.
Discuss the root causes for trust, availability, compliance, and security issues.
- A shortlist of solutions for improvement.
Brainstorm solutions for improvement.
Module 4: Create a Corrective Plan
- Develop a two-fold plan, that will outline short-term and long-term corrective actions.
- Identify the types of policies your organization requires and how to communicate policy changes to end users.
- Understand various techniques that can be used to maintain data quality and integrity: types of automated technologies available, data quality and integrity maintenance checks, and data governance..
Key Benefits Achieved
- An understanding of each data source and whether it is under-performing, over-performing, or on target when compared to data requirements.
- Immediate opportunities for improvement.
- Identify recommended future blueprints and data initiatives.
Identify underperforming data sources.
- An understanding of which data sources are underperforming and on target and where priorities should lie for clean-up efforts.
Identify immediate opportunities for improvement.
- Identification of activities that need to be adopted from planning, control, development, and operations.
Highlight activitiy groups that need focus for long-term corrective planning.