Data model: Discovering entities, attributes, and relationships conceptual, logical, and physical data models – what is normalization to us?

Save time, empower your teams and effectively upgrade your processes with access to this practical Data model Toolkit and guide. Address common challenges with best-practice templates, step-by-step work plans and maturity diagnostics for any Data model related project.

Download the Toolkit and in Three Steps you will be guided from idea to implementation results.

 

https://store.theartofservice.com/Data-model-toolkit-best-practice-templates-step-by-step-work-plans-and-maturity-diagnostics/

 

The Toolkit contains the following practical and powerful enablers with new and updated Data model specific requirements:

STEP 1: Get your bearings

Start with…

  • The latest quick edition of the Data model 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 668 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 model improvements can be made.

Examples; 10 of the 668 standard requirements:

  1. Is it possible to implement a traditional structured data models using an environment which has been designed for unstructured and semi-structured data(NoSQL environments)?

  2. How much importance needs to be given to metadata modeling during data warehouse development and how can you standardize the metadata model in data warehousing?

  3. Discovering entities, attributes, and relationships conceptual, logical, and physical data models – what is normalization to us?

  4. Has the logical data model been thoroughly examined to ensure that all of the required business functionality can be achieved?

  5. Should the person who enters the metadata be the creator herself, or should this be taken care of by the organisation?

  6. What are the data model, data definitions, structure, and hosting options of purchased applications (COTS)?

  7. What is the physical data model definition (derived from logical data models) used to design the database?

  8. What are the data model, data definitions, structure, and hosting options of purchased applications (COTS)?

  9. What is the physical data model definition (derived from logical data models) used to design the database?

  10. Common Business Data Model: Should the services be exposed in the form of some common business data model?

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 model book in PDF containing 668 requirements, which criteria correspond to the criteria in…

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

  • 62 step-by-step Data model Project Management Form Templates covering over 6000 Data model project requirements and success criteria:

Examples; 10 of the check box criteria:

  1. Human Resource Management Plan: Quality of people required to meet the forecast needs of the department?
  2. Project Portfolio management: Governance. How does the organization ensure that Data model project and program benefits and risks are being managed to optimize the overall value creation from the portfolio?
  3. Cost Management Plan: Have the key elements of a coherent Data model project management strategy been established?
  4. Lessons Learned: What was the methodology behind successful learning experiences, and how might they be applied to the broader challenge of the organizations knowledge management?
  5. Procurement Audit: Did the contracting authority draw up a comprehensive written report about progress and outcome of the procurement process?
  6. Schedule Management Plan: Are the schedule estimates reasonable given the Data model project?
  7. Team Member Performance Assessment: Does statute or regulation require the job responsibility?
  8. Schedule Management Plan: Are the processes for status updates and maintenance defined?
  9. Stakeholder Management Plan: Is the current scope of the Data model project substantially different than that originally defined?
  10. Project Performance Report: To what degree is there centralized control of information sharing?

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

1.0 Initiating Process Group:

  • 1.1 Data model project Charter
  • 1.2 Stakeholder Register
  • 1.3 Stakeholder Analysis Matrix

2.0 Planning Process Group:

  • 2.1 Data model 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 model 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 model 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 model 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 model 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 model project with this in-depth Data model Toolkit.

In using the Toolkit you will be better able to:

  • Diagnose Data model 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 model 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 model investments work better.

This Data model All-Inclusive Toolkit enables You to be that person:

 

https://store.theartofservice.com/Data-model-toolkit-best-practice-templates-step-by-step-work-plans-and-maturity-diagnostics/

 

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.