Clean Data Toolkit

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More Uses of the Clean Data Toolkit:

  • Organize: filter and Clean Data by reviewing reports, and performance indicators to locate and accurate problems.

  • Compile and Clean Data sets from multiple sources.

  • Methodize: effectively communicate and collaborate with Agile software Development Teams to facilitate Clean Data handoffs between internal and external systems.

  • Manage and Clean Datasets using an extraction and reporting programming language to ensure Data integrity, and apply methods to validate data to ensure high quality results.

  • Extract and Clean Data from multiple data sources.

  • Simplify a bloated architecture due to mergers and shadow IT; reduce application count to industry benchmarks; provide a Clean Data Driven view of Business Activities.

  • Extract, manage and Clean Data from various different platforms.

  • Direct: filter and Clean Data, and locate and correct code problems.

  • Devise: filter and Clean Data by reviewing data sources.

  • Orchestrate: filter and Clean Data by reviewing reports and performance indicators to locate and correct code problems.

  • Develop tools to ingest, merge, and Clean Datasets.

  • Make thoughtful judgements on Data Quality to Clean Data sources for import.

  • Extract and Clean Data from various sources.

  • Ensure Clean Data Collection with proper governance throughout the data pipeline.

  • Devise: wrangle messy e commerce data into Clean Datasets for analysis and reporting.

  • Lead: filter and Clean Data by reviewing incoming data sets.

  • Explore deep dive into current data and advocate change in processes to ensure Clean Data is collected throughout the different Business Processes.

  • Develop: filter and Clean Data by reviewing reports and performance indicators to create transparency around operational problems and challenges.

  • Gather data and supporting details to analyze and Clean Data for inclusion in reports.

  • Devise: filter and Clean Data by reviewing reports and data from multiple sources, and performance indicators to locate and correct code problems.

  • Collaborate with the other Data Curation teams, to improve and maintain the Core Data entities that are going to serve as a base for all business use cases that depend on Clean Data.

  • Ensure you facilitate; lead process disparate data sources and form a high integrity, high quality, Clean Data asset.

  • Lead a grasp of the fundamental importance of Clean Data to empower successful Digital Marketing initiatives, in support of larger Business Objectives.

  • Develop mechanisms to ingest, analyze, validate, normalize, and Clean Data.

  • Extract, manage and Clean Data from various platforms.


Save time, empower your teams and effectively upgrade your processes with access to this practical Clean Data Toolkit and guide. Address common challenges with best-practice templates, step-by-step Work Plans and maturity diagnostics for any Clean Data 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 Clean Data specific requirements:

STEP 1: Get your bearings

Start with...

  • The latest quick edition of the Clean Data 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 999 new and updated case-based questions, organized into seven core areas of Process Design, this Self-Assessment will help you identify areas in which Clean Data improvements can be made.

Examples; 10 of the 999 standard requirements:

  1. What risks do you need to manage?

  2. Who should receive measurement reports?

  3. What are the Clean Data use cases?

  4. What are the barriers to increased Clean Data production?

  5. Why is this needed?

  6. What are the potential basics of Clean Data fraud?

  7. How can you better manage risk?

  8. What projects are going on in the organization today, and what resources are those projects using from the resource pools?

  9. Where do you need to exercise leadership?

  10. Is the Quality Assurance team identified?

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 Clean Data book in PDF containing 994 requirements, which criteria correspond to the criteria in...

Your Clean Data 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 Clean Data Self-Assessment and Scorecard you will develop a clear picture of which Clean Data 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 Clean Data 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 Clean Data projects with the 62 implementation resources:

  • 62 step-by-step Clean Data Project Management Form Templates covering over 1500 Clean Data project requirements and success criteria:

Examples; 10 of the check box criteria:

  1. Cost Management Plan: Eac -estimate at completion, what is the total job expected to cost?

  2. Activity Cost Estimates: In which phase of the Acquisition Process cycle does source qualifications reside?

  3. Project Scope Statement: Will all Clean Data project issues be unconditionally tracked through the Issue Resolution process?

  4. Closing Process Group: Did the Clean Data Project Team have enough people to execute the Clean Data Project Plan?

  5. Source Selection Criteria: What are the guidelines regarding award without considerations?

  6. Scope Management Plan: Are Corrective Actions taken when actual results are substantially different from detailed Clean Data Project Plan (variances)?

  7. Initiating Process Group: During which stage of Risk planning are risks prioritized based on probability and impact?

  8. Cost Management Plan: Is your organization certified as a supplier, wholesaler, regular dealer, or manufacturer of corresponding products/supplies?

  9. Procurement Audit: Was a formal review of tenders received undertaken?

  10. Activity Cost Estimates: What procedures are put in place regarding bidding and cost comparisons, if any?

Step-by-step and complete Clean Data Project Management Forms and Templates including check box criteria and templates.

1.0 Initiating Process Group:

2.0 Planning Process Group:

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 Clean Data 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 Clean Data project or Phase Close-Out
  • 5.4 Lessons Learned



With this Three Step process you will have all the tools you need for any Clean Data project with this in-depth Clean Data Toolkit.

In using the Toolkit you will be better able to:

  • Diagnose Clean Data 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 Clean Data 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 Clean Data investments work better.

This Clean Data 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.