Data Farming Toolkit


• Ensure you involve; lead with knowledge and expertise in selling Cloud Technologies, with focus on Azure cloud data and Bi Platforms.
  
  

• Evaluate quality monitoring data to ensure standards are being met.
  
  

• Secure that your business maintains, archives, and distributes geospatial data while assuring its effectiveness by keeping the associated Metadata current and accurate.
  
  

• Arrange that your organization develops operational controls for the monitoring and detection of Data Quality issues and develops Continuous Data Quality Improvement processes.
  
  

• Develop self generated leads through networking, Data Mining (from existing client records), and referral generation from previous clients.
  
  

• Collect and organize technical data from equipment manufacturers, equipment users, and engineering personnel.
  
  

• Provide insight on and champion Process Improvement opportunities and the elimination of non value added work.
  
  

• Identify Data Quality issues and support the Data Governance initiative by participating in necessary activities.
  
  

• Make sure that your group determines long term organization wide information needs and develops overall strategy for Data Management and interfacing.
  
  

• Collect and analyze key market data and competitive information to assess Addressable Market size and trend.
  
  

• Oversee database planning, configuration, installation, data conversion, database migration, Performance Tuning, Capacity Planning, database migrations to cloud Backup and Recovery.
  
  

• Arrange that your project serves as the primary point of contact for vendors for SaaS and on premise applications for Problem Resolution, upgrades, Performance Tuning and reoccurring Data Processing.
  
  

• Manage work with systems and Data Governance teams to ensure Internal Controls are implemented and Data integrity is maintained post conversion.
  
  

• Arrange that your team provides purchasing, planning, and control information by collecting, analyzing, and summarizing data and trends.
  
  

• Be accountable for using data indicators, intuition, and/or other resources, identifies system, safety and quality problems, suggests solutions, and provides information that leads to change in department and on teams.
  
  

• Provide expertise, coaching and training to brands on how to effectively gather Quantitative Data and identify relevant Customer Insights.
  
  

• Create and maintain essential Metadata (data models, Data Dictionaries, and Data Flow diagrams).
  
  

• Ensure you amplify; build data mappings to provide the means of System Integration by considering security, compliance the target and the source System Requirements.
  
  

• Be accountable for ensuring that the technologies, processes, and culture transform data into an activE Business asset that helps drive the strategy of your organization forward.
  
  


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

STEP 1: Get your bearings

Start with...


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

Examples; 10 of the 999 standard requirements:


1. Who is involved with workflow mapping?
   
   

2. How do you build the right business case?
   
   

3. What Data Farming data do you gather or use now?
   
   

4. Is it possible to estimate the impact of unanticipated complexity such as wrong or failed assumptions, feedback, etc. on proposed reforms?
   
   

5. Are required metrics defined, what are they?
   
   

6. What else needs to be measured?
   
   

7. What scope to assess?
   
   

8. Is the scope clearly documented?
   
   

9. How do you reduce costs?
   
   

10. Which models, tools and techniques are necessary?
    
    


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


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


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

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

1.0 Initiating Process Group:


• 1.1 Data Farming project Charter

• 1.2 Stakeholder Register

• 1.3 Stakeholder Analysis Matrix


2.0 Planning Process Group:


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

In using the Toolkit you will be better able to:


• Diagnose Data Farming 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 Farming 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 Farming investments work better.

This Data Farming 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.