Data Analytics Toolkit

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


STEP 1: Get your bearings

Start with...

  • The latest quick edition of the Data Analytics 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 990 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 Analytics improvements can be made.

Examples; 10 of the 990 standard requirements:

  1. How does the already automated manufacturing industry harness AI and the real time data analytics capabilities to make more real time decisions that increase productivity and improve competitiveness?

  2. How will the blending of technologies, as data analytics, social connectivity, cloud computing, autonomous technology, and instantaneous communication, alter current business models?

  3. How is your organization identifying areas where AI or data analytics approaches are applicable or have the potential for the greatest positive impact?

  4. Are you taking full advantage of available channels, digital capabilities, data analytics, and artificial intelligence tools to boost service sales?

  5. How do you deliver the clean and structured data that AI and machine learning solutions must have to solve challenging data analytics use cases?

  6. Have you evaluated the positive impact modern data analytics and reporting platforms could have on your and regulatory reporting requirements?

  7. Can the audit department afford to have one or more people dedicated to data analytics, particularly if its a small internal audit function?

  8. Will you perform advanced malware analysis, threat hunting, data analytics, forensics, and incident response as part of your core service?

  9. What additional audit tests does your organization perform over audit areas/processes where internal audit uses data analytics?

  10. What role does data, data analytics and predictive analytics play in identifying, closing and anticipating capability gaps?


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 Analytics book in PDF containing 990 requirements, which criteria correspond to the criteria in...

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

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

Examples; 10 of the check box criteria:

  1. Assumption and Constraint Log: Have Data Analytics project management standards and procedures been established and documented?

  2. Planning Process Group: When developing the estimates for Data Analytics project phases, you choose to add the individual estimates for the activities that comprise each phase. What type of estimation method are you using?

  3. Procurement Audit: Did additional works amount to no more than 50% of the initial contract?

  4. Procurement Management Plan: Were Data Analytics project team members involved in the development of activity & task decomposition?

  5. Procurement Audit: What is the process cost of the procurement function?

  6. Lessons Learned: What things surprised you on the Data Analytics project that were not in the plan?

  7. Activity Duration Estimates: Calculate the expected duration for an activity that has a most likely time of 3, a pessimistic time of 10, and a optimiztic time of 2?

  8. Activity Duration Estimates: Based on , if you need to shorten the duration of the Data Analytics project, what activity would you try to shorten?

  9. Roles and Responsibilities: Are your budgets supportive of a culture of quality data?

  10. Risk Register: What further options might be available for responding to the risk?

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

1.0 Initiating Process Group:

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


2.0 Planning Process Group:

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

In using the Toolkit you will be better able to:

  • Diagnose Data Analytics 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 Analytics 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 Analytics investments work better.

This Data Analytics 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.