Data Domain Toolkit

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Review and update Data Quality Rules in applications and confirm accuracy and availability of data for Decision Support, regulatory and Financial Reporting, and Compliance Monitoring, in coordination with Business Architects by Data Domain and Data Stewards.

More Uses of the Data Domain Toolkit:

  • Assure your design applies Data Domain knowledge to your organization, channel, and application and process to satisfy regulatory and internal requirements related to Information Governance and Data Management.

  • Be accountable for Data Domain architecture decisions and Technology Investments, managing the overall Data Domain Technology Roadmap to support the overall Data Strategy, in alignment with enterprise guidance and vision.

  • Provide leadership, direction, and accountability for strategic architecture plans, System Design, and implementation standards for the Data Domain.

  • Direct: partner with Data Architects and business SMEs to create and maintain your organization Data Model (bdm) for each Data Domain that is aligned across the enterprise.

  • Support the cleansing, transformation, conversion, and remediation of data efforts across key business and Master Data Domains.

  • Establish single sources of truth for investment Data Domains, immediate focus on holdings, transactions and account domains.

  • Participate as a member of Architectural Review Boards that ensures Data Domain is appropriately represented and data related decisions are properly vetted.

  • Direct: enterprise wide awareness of the business and Data Domains in relation to core Business Processes and capabilities, and enabling Technology Platforms.

  • Collaborate with Process Owners/data owners to monitor Data Usage and foster trust in data by driving Data Quality by making sure procedures and rules adapt as Data Domains/sets expand or Business Requirements change.

  • Supervise: leverage enterprise standards for Data Domains and data solutions, focusing on simplified integration and streamlined operational and analytical uses.

  • Drive the development and implementation of Data Quality and Data Protection standards across relevant Data Domains.

  • Ensure your venture supports and contributes to Information Governance guidelines, principles, policies and standard implementations across Data Domain, teams, and Key Stakeholders.

  • Capture launch the Client (Buyer) and Intermediary (Producer) Data Domains team establishes client and producer Data Strategies through an Enterprise lens and ensures roadmap delivery for all enterprise client and producer Data Domain initiatives.

  • Ensure you coach; correspond develop a common language for Enterprise Data managed through a standard process and a platform to organize and maintain Metadata around Data Domains/data taxonomy.

  • Drive data Management And Governance process to grow together disparate Data Assets, curate key Data Domains into sources of truth and help create a Data Backbone supporting analytics and reporting.

  • Enable the client (buyer) and intermediary (producer) Data Domains team establishes client and producer Data Strategies through an enterprise lens and ensures roadmap delivery for all enterprise client and producer Data Domain initiatives.

  • Support the development, maintenance and implementation of common language for Enterprise Data managed through a standardized Data Governance platform to organize and maintain Data Domains and data taxonomy.

  • Serve as a resource for Data Management implementations on other Technology Teams and collaborate with Data Domain owners, business owners, and leaders.

  • Obtain proceed develop a common language for Enterprise Data managed through a standard process and a platform to organize and maintain Metadata around Data Domains/data taxonomy.

  • Confirm your organization leads and mentors other Solution Architects and SMEs across Data Domain in the management of Data Architecture deliverables, incorporating industry Best Practices/standards.

  • Ensure you convey; lead the Business Case requirements for an MDM Platform to enable source system cleansing and Data Quality measuring and monitoring at scale across all the Data Domains.

  • Warrant that your organization leads the requirements analyzing team in building the process Value Chain, functional and Data Domains, conceptual Data Models etc.

  • Lead Business Requirements gathering, and understand Process Design and capabilities across your analytics communities and Data Domains.

  • Systematize: enterprise level awareness of the business, systems, processes and Data Domains in relation to core Business Processes, capabilities, and enabling Technology Platforms.

  • Manage advanced ability in designing a people Data Strategy with particular emphasis on expertise in the Human Capital Data Domain.

  • Make sure that your enterprise leads the Master Data Governance Team for supplier, customer, material, financial and other Data Domains of enterprise impact.

 

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


STEP 1: Get your bearings

Start with...

  • The latest quick edition of the Data Domain 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 Data Domain improvements can be made.

Examples; 10 of the 999 standard requirements:

  1. When are costs are incurred?

  2. For estimation problems, how do you develop an estimation statement?

  3. Are the Data Domain standards challenging?

  4. To whom do you add value?

  5. Is scope creep really all bad news?

  6. Who will gather what data?

  7. What is the complexity of the output produced?

  8. How do you cross-sell and up-sell your Data Domain success?

  9. What are the costs?

  10. Who is involved with workflow mapping?


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

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

  • 62 step-by-step Data Domain Project Management Form Templates covering over 1500 Data Domain 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 Data Domain project issues be unconditionally tracked through the Issue Resolution process?

  4. Closing Process Group: Did the Data Domain Project Team have enough people to execute the Data Domain 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 Data Domain 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 Data Domain 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 Data Domain 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 Domain project or Phase Close-Out
  • 5.4 Lessons Learned

 

Results

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

In using the Toolkit you will be better able to:

  • Diagnose Data Domain 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 Domain 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 Domain investments work better.

This Data Domain 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.