Participate in Big Data Quality Assurance functions throughout the lifecycle to ensure Customer Satisfaction and requirements are met.
More Uses of the Data Quality Assurance Toolkit:
- Guide: own Data Quality Assurance and management protocols/processes.
- Maintain technical and analytical skills to ensure Data Quality Assurance and Quality Control.
- Represent the measurement operations team in meetings as subject matter authority on Data Quality Assurance.
- Ensure Data Quality Assurance and establish SLAs for data publishes.
- Devise: design and implement Data Quality check framework for Data Quality Assurance.
- Pilot: implement best practice Data Quality Assurance mechanisms.
- Be accountable for coordinating Data Quality Assurance to address findings, trends, and data related activities.
- Organize and merge data from multiple sources, and run Data Quality Assurance checks.
- Oversee: Data Quality Assurance management organizational research.
- Collaborate with others regarding Data Management, and in the planning and implementation of Data Quality Assurance plans.
- Be accountable for coordinating Data Quality Assurance in order to address findings, trends, and data related activities.
- Be accountable for providing leadership on data acquisition and Data Quality Assurance.
- Drive: design, develop and maintain Data Quality Assurance framework.
Save time,, empower your teams and effectively upgrade your processes with access to this practical Data Quality Assurance Toolkit and guide. Address common challenges with best-practice templates, step-by-step Work Plans and maturity diagnostics for any Data Quality Assurance related project.
Download the Toolkit and in Three Steps you will be guided from idea to implementation results.
The Toolkit contains the following practical and powerful enablers with new and updated Data Quality Assurance specific requirements:
STEP 1: Get your bearings
- The latest quick edition of the Data Quality Assurance Self Assessment book in PDF containing 49 requirements to perform a quickscan, get an overview and share with stakeholders.
Organized in a Data Driven improvement cycle RDMAICS (Recognize, Define, Measure, Analyze, Improve, Control and Sustain), check the…
- Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation
Then find your goals...
STEP 2: Set concrete goals, tasks, dates and numbers you can track
Featuring 992 new and updated case-based questions, organized into seven core areas of Process Design, this Self-Assessment will help you identify areas in which Data Quality Assurance improvements can be made.
Examples; 10 of the 992 standard requirements:
- Do your data infrastructure projects experience a high level of risk from poor Data Quality, lack of source data knowledge, insufficient budget, understaffing, scope creep, and other factors?
- Are automated processes being risk assessed for Data Quality, the accuracy of algorithms and outputs and is Internal Audit equipped to confirm that technologies are working as intended?
- Is your organization looking for an interface to support Data Stewardship activity and Data Remediation as Data Quality Business Rules are violated to support Data Governance?
- What detailed security requirements are implemented and tested in the Quality Assurance system as part of the system user roles and authorization administration deliverable?
- What could it look like if data infrastructure was sufficiently built out for a given issue area out to dramatically improve Data Quality and enable learning at scale?
- Does the platform enable you to establish key Data Quality metrics, monitor them on an ongoing basis, and receive alerts on items that fall out of acceptable ranges?
- Are chart numbers or abstract numbers available for your organizations data so that you can track cases back to your own system for Data Quality purposes?
- Does the procedure assure objective evidence exists that the software performs required functions and data rights are consistent with the subcontract?
- Are there any standardised Data Quality reports or expressions that can be associated with data - either directly in database, or as part of metadata?
- Has your organization defined the role of a Data Steward to assist with correction of Data Issues as the system processes Data Quality Business Rules?
Complete the self assessment, on your own or with a team in a workshop setting. Use the workbook together with the self assessment requirements spreadsheet:
- The workbook is the latest in-depth complete edition of the Data Quality Assurance book in PDF containing 992 requirements, which criteria correspond to the criteria in...
Your Data Quality Assurance self-assessment dashboard which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next:
- The Self-Assessment Excel Dashboard; with the Data Quality Assurance Self-Assessment and Scorecard you will develop a clear picture of which Data Quality Assurance areas need attention, which requirements you should focus on and who will be responsible for them:
- Shows your organization instant insight in areas for improvement: Auto generates reports, radar chart for maturity assessment, insights per process and participant and bespoke, ready to use, RACI Matrix
- Gives you a professional Dashboard to guide and perform a thorough Data Quality Assurance Self-Assessment
- Is secure: Ensures offline Data Protection of your Self-Assessment results
- Dynamically prioritized projects-ready RACI Matrix shows your organization exactly what to do next:
STEP 3: Implement, Track, follow up and revise strategy
The outcomes of STEP 2, the self assessment, are the inputs for STEP 3; Start and manage Data Quality Assurance projects with the 62 implementation resources:
- 62 step-by-step Data Quality Assurance Project Management Form Templates covering over 1500 Data Quality Assurance project requirements and success criteria:
Examples; 10 of the check box criteria:
- Roles and Responsibilities: What should you do now to prepare for your career 5+ years from now?
- Assumption and Constraint Log: Do you know what your customers expectations are regarding this process?
- Project or Phase Close-Out: If you were the Data Quality Assurance project sponsor, how would you determine which Data Quality Assurance project team(s) and/or individuals deserve recognition?
- Scope Management Plan: Are milestone deliverables effectively tracked and compared to Data Quality Assurance project plan?
- Cost Management Plan: Schedule preparation â how will the schedules be prepared during each phase of the Data Quality Assurance project?
- Human Resource Management Plan: Specific - is the Objective Clear in terms of what, how, when, and where the situation will be changed?
- Duration Estimating Worksheet: Define the work as completely as possible. What work will be included in the Data Quality Assurance project?
- Responsibility Assignment Matrix: Are material costs reported within the same period as that in which BCWP is earned for that material?
- Stakeholder Analysis Matrix: Are the required specifications for products or services changing?
- Activity Duration Estimates: Find an example of a contract for information technology services. Analyze the key features of the contract. What type of contract was used and why?
1.0 Initiating Process Group:
2.0 Planning Process Group:
- 2.1 Data Quality Assurance Project Management Plan
- 2.2 Scope Management Plan
- 2.3 Requirements Management Plan
- 2.4 Requirements Documentation
- 2.5 Requirements Traceability Matrix
- 2.6 Data Quality Assurance project Scope Statement
- 2.7 Assumption and Constraint Log
- 2.8 Work Breakdown Structure
- 2.9 WBS Dictionary
- 2.10 Schedule Management Plan
- 2.11 Activity List
- 2.12 Activity Attributes
- 2.13 Milestone List
- 2.14 Network Diagram
- 2.15 Activity Resource Requirements
- 2.16 Resource Breakdown Structure
- 2.17 Activity Duration Estimates
- 2.18 Duration Estimating Worksheet
- 2.19 Data Quality Assurance project Schedule
- 2.20 Cost Management Plan
- 2.21 Activity Cost Estimates
- 2.22 Cost Estimating Worksheet
- 2.23 Cost Baseline
- 2.24 Quality Management Plan
- 2.25 Quality Metrics
- 2.26 Process Improvement Plan
- 2.27 Responsibility Assignment Matrix
- 2.28 Roles and Responsibilities
- 2.29 Human Resource Management Plan
- 2.30 Communications Management Plan
- 2.31 Risk Management Plan
- 2.32 Risk Register
- 2.33 Probability and Impact Assessment
- 2.34 Probability and Impact Matrix
- 2.35 Risk Data Sheet
- 2.36 Procurement Management Plan
- 2.37 Source Selection Criteria
- 2.38 Stakeholder Management Plan
- 2.39 Change Management Plan
3.0 Executing Process Group:
- 3.1 Team Member Status Report
- 3.2 Change Request
- 3.3 Change Log
- 3.4 Decision Log
- 3.5 Quality Audit
- 3.6 Team Directory
- 3.7 Team Operating Agreement
- 3.8 Team Performance Assessment
- 3.9 Team Member Performance Assessment
- 3.10 Issue Log
4.0 Monitoring and Controlling Process Group:
- 4.1 Data Quality Assurance project Performance Report
- 4.2 Variance Analysis
- 4.3 Earned Value Status
- 4.4 Risk Audit
- 4.5 Contractor Status Report
- 4.6 Formal Acceptance
5.0 Closing Process Group:
- 5.1 Procurement Audit
- 5.2 Contract Close-Out
- 5.3 Data Quality Assurance project or Phase Close-Out
- 5.4 Lessons Learned
In using the Toolkit you will be better able to:
- Diagnose Data Quality Assurance projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices
- Implement evidence-based best practice strategies aligned with overall goals
- Integrate recent advances in Data Quality Assurance and put Process Design strategies into practice according to best practice guidelines
Defining, designing, creating, and implementing a process to solve a business challenge or meet a business objective is the most valuable role; In EVERY company, organization and department.
Unless you are talking a one-time, single-use project within a business, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?'
This Toolkit empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Data Quality Assurance investments work better.
This Data Quality Assurance All-Inclusive Toolkit enables You to be that person.
Includes lifetime updates
Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.