Data Analysis Toolkit

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


STEP 1: Get your bearings

Start with...

  • The latest quick edition of the Data Analysis 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 992 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 Analysis improvements can be made.

Examples; 10 of the 992 standard requirements:

  1. Do you add modules as inventory, finance and marketing to expand the systems capabilities and include more areas of the business in data analysis?

  2. Is it obvious what their project is about, which part of the process is causing the issue, that the solutions come from the data analysis?

  3. Does the curve slope up, does it slope down, and is there a definite change in the direction or the magnitude of the slope over time?

  4. How does recordkeeping and data analysis help you identify problems, develop solutions and manage the compensation process?

  5. Can a few simple operators on a familiar and minimal representation provide much of the power of exploratory data analysis?

  6. How do engineering education researchers interpret and report the meaning and use of mixed methods research designs?

  7. What data sources or challenges are driving, or would drive, your organizations interest in using big data analysis?

  8. What other issues are engineering education researchers facing when interpreting and reporting mixed methods data?

  9. What is the justification for analysing qualitative data in a systematic manner and according to strict rules?

  10. What is the amount of non personnel costs associated with the anonymization of sensitive data in the project?


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 Analysis book in PDF containing 992 requirements, which criteria correspond to the criteria in...

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

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

Examples; 10 of the check box criteria:

  1. Cost Management Plan: Does the business case include how the Data Analysis project aligns with your organizations strategic goals & objectives?

  2. Quality Management Plan: How does your organization recruit, hire, and retain new employees?

  3. Human Resource Management Plan: Is Data Analysis project work proceeding in accordance with the original Data Analysis project schedule?

  4. Variance Analysis: Is work properly classified as measured effort, LOE, or apportioned effort and appropriately separated?

  5. Planning Process Group: How well did the chosen processes fit the needs of the Data Analysis project?

  6. Procurement Audit: Are goods generally ordered and received in time to be used in the programs for which they were ordered?

  7. Procurement Management Plan: Have stakeholder accountabilities & responsibilities been clearly defined?

  8. Procurement Audit: Did the conditions of contract comply with the detail provided in the procurement documents and with the outcome of the procurement procedure followed?

  9. Risk Management Plan: Management -what contingency plans do you have if the risk becomes a reality?

  10. Quality Audit: How does your organization know that its teaching activities (and staff learning) are effectively and constructively enhanced by its activities?

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

1.0 Initiating Process Group:

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


2.0 Planning Process Group:

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

In using the Toolkit you will be better able to:

  • Diagnose Data Analysis 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 Analysis 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 Analysis investments work better.

This Data Analysis 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.