Data Modelling Toolkit

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

STEP 1: Get your bearings

Start with...


• The latest quick edition of the Data Modelling 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 995 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 Modelling improvements can be made.

Examples; 10 of the 995 standard requirements:


1. Does the use of a concept map as a first step in data modeling help learners to learn conceptual data modeling easier than the traditional method of learning?
   
   

2. What are the available licensing models for a complete metadata management solution, including ongoing costs as licensing or maintenance and support?
   
   

3. Are there any data partners that expect the provider to enable the entire data wrangling effort on premises / locally in the infrastructure?
   
   

4. How can a database containing hundreds or thousands of tables be modelled or displayed so as to give an accurate picture of the database?
   
   

5. How would that knowledge impact the business processes and applications your organization relies on to remain competitive?
   
   

6. What is your organizations overall methodology and approach to metadata management of structured and unstructured data?
   
   

7. Is it expected that all data from contributing organizations will be final, or do you anticipate multiple transfers?
   
   

8. Does the software solution have customizable role based access to the metadata and the management of metadata?
   
   

9. Are there basic differences between 2D and 3D which make 3D better or worse for particular domains or tasks?
   
   

10. Does the software solution provide a search feature that searches all metadata within the metadata registry?
    
    


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 Modelling book in PDF containing 995 requirements, which criteria correspond to the criteria in...


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


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


Examples; 10 of the check box criteria:


1. Risk Audit: Does your organization have any policies or procedures to guide its decision-making (code of conduct for the board, conflict of interest policy, etc.)?
   
   

2. Responsibility Assignment Matrix: Competencies and craftsmanship – what competencies are necessary and what level?
   
   

3. Planning Process Group: What is the critical path for this Data Modelling project, and what is the duration of the critical path?
   
   

4. Procurement Audit: If information was withheld, was there reasonable justification for this decision?
   
   

5. Executing Process Group: Contingency planning. if a risk event occurs, what will you do?
   
   

6. Activity Duration Estimates: Is a Data Modelling project charter created once a Data Modelling project is formally recognized?
   
   

7. Quality Audit: How does your organization know that its relationships with industry and employers are appropriately effective and constructive?
   
   

8. Closing Process Group: How well defined and documented were the Data Modelling project management processes you chose to use?
   
   

9. Human Resource Management Plan: Is a stakeholder management plan in place that covers topics?
   
   

10. Lessons Learned: How well defined were the acceptance criteria for Data Modelling project deliverables?


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

1.0 Initiating Process Group:


• 1.1 Data Modelling project Charter

• 1.2 Stakeholder Register

• 1.3 Stakeholder Analysis Matrix


2.0 Planning Process Group:


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

In using the Toolkit you will be better able to:


• Diagnose Data Modelling 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 Modelling 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 Modelling investments work better.

This Data Modelling 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.