Pilot Data Life Cycle: design, architecture and develop solutions for Application Integration and work with application architects for successful integration with Enterprise Applications involving complex/critical security models, visualization delivery and APIs.

More Uses of the Data Life Cycle Toolkit:


• Standardize Data Life Cycle: design Data Flow and engineering Data Life Cycle to determine how data is originated, enriched, stored, and disposed to meets compliance and Business Requirements.
  
  

• Manage Data Life Cycle: confidence using data to highlight challenges and roadblocks during recruiting life cycle.
  
  

• Provide leadership responsibility to embrace digital innovation to drive Continuous Improvement through Data Analytics to Reduce Risk and with a rigorous focus on leading indicators.
  
  

• Blend methodologies from Machine Learning, applied statistics, and Operations Research in order to distill complex and disparate data sources into value added information streams accessible by non technical staff.
  
  

• Formulate Data Life Cycle: fuel Communication Skills to effectively convey business implications of complex data relationships and results of statistical models to multiplE Business partners.
  
  

• Drive efforts to document Data Flow architectures between Enterprise Systems for critical data assets as Customers, Vendors, Products, Price, Cost, etc.
  
  

• Transform and improve performance long running queries on large datasets with more efficient queries, Data Virtualization.
  
  

• Provide Thought Leadership in areas as Data Retention, Business Continuity, Disaster Recovery Planning/testing, and information Risk Management.
  
  

• Warrant that your group performs Data Analysis, trending, and prepares hourly, daily and monthly Call Center Performance Reports and or Dashboards.
  
  

• Roll out an enterprise wide Data Governance framework, with a focus on improvement of Data Quality and the protection of sensitive data through modifications to organization behavior Policies And Standards, principles, Governance Metrics, processes, related tools and Data Architecture.
  
  

• Perform large scale Data Analysis to extract useful business insights.
  
  

• Ensure you helm; lead research, strategy creation and development of new data products or services to expand markets, monetize data (directly and indirectly) and grow revenue as allowed by regulation and policy.
  
  

• Arrange that your organization assess, modify, enhance and develop the enterprise strategy for information Security And Compliance in partnership with peers and business leaders, creating short and long term initiatives that support Business Objectives that mitigate organization risk and protect Data Security.
  
  

• Secure that your organization coordinates the management of the Data Loss Protection application with organizations Managed Security Service Provider.
  
  

• Analyze subscription kpis and data to make informed business decisions on auto replenishment strategy, up sells and cross sells.
  
  

• Be accountable for entering and maintaining data in the internal Customer Management system.
  
  

• Ensure you classify; build and deliver high quality Data Architecture and pipelines to support Business Analysis, Data Scientists, and customer reporting needs.
  
  

• Audit Data Life Cycle: research and understand external Best Practices and Emerging Technologies for possible incorporation into organizational identity and Data Security practices.
  
  

• Steer Data Life Cycle: on various metrics to promote Data Governance and to improve overall performance and insight.
  
  

• Develop and/or modify Data Models and/or simulations to capture the attributes of adversarial and non adversarial threats targeting critical systems.
  
  

• Coordinate and facilitate Data Gathering and other activities between Retail Business Office and Auto Lending Technology leadership team.
  
  

• Organize Data Life Cycle: design, build and launch efficient and reliable Data Pipelines for ingesting and transforming data from internal and cloud applications.
  
  

• Establish that your organization maintains the enterprise Identity Management infrastructure and performs considerable work in the development and implementation of workflows and Data Integration/transformations in an Identity Management System.
  
  

• Be accountable for supporting manufacturing goals to increase equipment up time, Statistical Process Control, and use of Data Analysis to understand area issues.
  
  

• Manage and coordinate teams to deploy Data Analytics projects using innovative solutions and to provide analytics driven insights.
  
  

• Contribute to functional and technical software Application Design (requirement gathering/analysis, mapping/gapping, Solution Design, application setup and design, testing and post implementation support); authoring/management (workflow mapping, data dictionary).
  
  

• Identify, research and resolve data discrepancies in order to provide a single source of truth in all Data Reporting.
  
  

• Ensure you helm; lead data Intelligence Analysis.
  
  

• Identify opportunities resulting from situational changes as new regulation, data insights, new business situations to shape new improvements in MDM Business Processes and data.
  
  

• Manage relationships between thE Business and technology and effectively support the needs of thE Business and drive change through the use of Data Analytics, automation and Digital Transformation.
  
  

• Advise the Program Management (pm) throughout the program life cycle on cost, schedule, risk and performance issues.
  
  

• Identify Data Life Cycle: through collaboration with team members, develop and implement Data Collection systems and other strategies that optimize statistical efficiency and Data Quality.
  
  


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

STEP 1: Get your bearings

Start with...


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

Examples; 10 of the 999 standard requirements:


1. What do you want to improve?
   
   

2. Does the problem have ethical dimensions?
   
   

3. What are your key Data Life Cycle organizational Performance Measures, including key short and longer-term financial measures?
   
   

4. How do mission and objectives affect the Data Life Cycle processes of your organization?
   
   

5. What Data Life Cycle Data will be collected?
   
   

6. Do the viable solutions scale to future needs?
   
   

7. How do you track customer value, profitability or financial return, organizational success, and sustainability?
   
   

8. Where is training needed?
   
   

9. Do you recognize Data Life Cycle achievements?
   
   

10. How will you measure your Data Life Cycle effectiveness?
    
    


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


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


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

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

1.0 Initiating Process Group:


• 1.1 Data Life Cycle project Charter

• 1.2 Stakeholder Register

• 1.3 Stakeholder Analysis Matrix


2.0 Planning Process Group:


• 2.1 Data Life Cycle 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 Life Cycle 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 Life Cycle 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 Life Cycle 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 Life Cycle 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 Life Cycle project with this in-depth Data Life Cycle Toolkit.

In using the Toolkit you will be better able to:


• Diagnose Data Life Cycle 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 Life Cycle 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 Life Cycle investments work better.

This Data Life Cycle 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.