Lead Master Data Management (MDM) initiative for Continuous Improvement on processes for managing enterprise wide data throughout the Data Lifecycle from capture to processing to usage and provide the MDM framework to measure, track, improve, and communicate change.

More Uses of the Data Lifecycle Toolkit:


• Manage work with cross functional teams to enable data insights though Data Lifecycle.
  
  

• Ensure your organization understands and develops solutions to foster Data Lifecycle Management.
  
  

• Methodize: plan facilitate the development and implementation of Data Quality standards, Data Protection standards, Data Security, & maintenance of an end to end Data Lifecycle Management and adoption requirements across the enterprise.
  
  

• Be accountable for ensuring clear accountability for proper stewardship of consumer information throughout the Data Lifecycle.
  
  

• Transform facilitate the development and implementation of Data Quality standards, Data Protection standards, Data Security, and maintenance of an end to end Data Lifecycle Management and adoption requirements across the enterprise.
  
  

• Audit: work in collaboration with Key Stakeholders, as technology and analytics to lead the establishment of an enterprise wide Data Strategy for all aspects of the Data Lifecycle.
  
  

• Secure that your enterprise complies; interfaces with organization management and external Service Providers, on behalf of information analysis, processes and Data Lifecycle topics.
  
  

• Enforce your Data Retention policies, minimizing liability and cost while maximizing the effective Data Lifecycle.
  
  

• Strengthen accountability and alignment throughout the full Data Lifecycle through design and implementation of information policy, controls and guidance.
  
  

• Perform improve facilitate the development and implementation of Data Quality standards, Data Protection standards, Data Security, & maintenance of an end to end Data Lifecycle Management and adoption requirements across the enterprise.
  
  

• Evaluate: cause mature Data Governance efforts to organize and streamline the Data Lifecycle from origination through consumption.
  
  

• Ensure you propel; understand the Data Lifecycle and concepts as lineage, governance, privacy, retention, anonymity, etc.
  
  

• Develop standards for Data Governance, Data Lifecycle, Master Data Management and data cataloging.
  
  

• Be accountable for developing Data Management and Data Governance plans and working with Metadata and Data Lifecycle.
  
  

• Direct: management of Data Lifecycle, from creation to retention to deletion.
  
  

• Ensure you meet; lead Data Lifecycle Management strategy and maturation of archiving capabilities and services at Biogen, particularly with respect to Unstructured Data.
  
  

• Ensure best practices around ethics and equity are embedded at every stage of the Data Lifecycle from collection, storage, sharing, and use.
  
  

• Provide Quality Assurance and testing support for large scale Data Lifecycle initiatives.
  
  

• Establish that your team complies; monitors and provides Status Reports on Data Lifecycle and analytical workflow processes.
  
  

• Ensure you establish; understand and advise on the privacy requirements applicable to complex personal Data Flows across the Data Lifecycle.
  
  

• Supervise: act as a resource to the Machine Learning team with regards to Data Lifecycle Management.
  
  

• Support local teams in recognizing key business opportunities, engage customers to address aspects of the Data Lifecycle.
  
  

• Be accountable for leading annual efforts to execute the Data Lifecycle Management Review and completion with Business Process owners.
  
  

• Confirm your operation complies; sets technical direction for the overall MDM Solution Architecture, defines component architecture, review detailed designs for accuracy and overall compliance to defined architecture across the complete Data Lifecycle.
  
  

• Identify and communicate opportunities for improvement to aid in the overall enrichment of asset and MetaData Lifecycle.
  
  

• Secure that your team strengthens accountability and alignment throughout the full Data Lifecycle through design and implementation of information policy, controls and guidance.
  
  

• Manage the full Data Lifecycle from concept to delivery, connecting optimization metrics to the strategic intent of campaigns and underlying Business Objectives.
  
  

• Write and maintain functional Design Specifications for various Master Data Lifecycle scenarios based on business need.
  
  


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

STEP 1: Get your bearings

Start with...


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

Examples; 10 of the 999 standard requirements:


1. How do you establish and deploy modified action plans if circumstances require a shift in plans and rapid execution of new plans?
   
   

2. Has the Data Lifecycle value of standards been quantified?
   
   

3. What are hidden Data Lifecycle quality costs?
   
   

4. What are your most important goals for the strategic Data Lifecycle objectives?
   
   

5. What can you control?
   
   

6. Do you have the authority to produce the output?
   
   

7. What extra resources will you need?
   
   

8. How is implementation research currently incorporated into each of your goals?
   
   

9. Which models, tools and techniques are necessary?
   
   

10. What are current Data Lifecycle paradigms?
    
    


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


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


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

4. Closing Process Group: Did the Data Lifecycle project team have enough people to execute the Data Lifecycle 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 Lifecycle 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 Lifecycle Project Management Forms and Templates including check box criteria and templates.

1.0 Initiating Process Group:


• 1.1 Data Lifecycle project Charter

• 1.2 Stakeholder Register

• 1.3 Stakeholder Analysis Matrix


2.0 Planning Process Group:


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

In using the Toolkit you will be better able to:


• Diagnose Data Lifecycle 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 Lifecycle 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 Lifecycle investments work better.

This Data Lifecycle 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.