Save time, empower your teams and effectively upgrade your processes with access to this practical DataOps Toolkit and guide. Address common challenges with best-practice templates, step-by-step work plans and maturity diagnostics for any DataOps 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 DataOps specific requirements:
STEP 1: Get your bearings
Start with...
- The latest quick edition of the DataOps 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 989 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which DataOps improvements can be made.
Examples; 10 of the 989 standard requirements:
- How can data lineage and provenance be used to support data storytelling and business intelligence, and what are the implications of not having a clear understanding of data origins and transformations on business decision-making?
- How can data lineage and provenance be used to support data mesh and data fabric architectures, and what are the implications of not having a clear understanding of data origins and transformations on distributed data management?
- How can data lineage and provenance be used to support data marketplaces and data exchanges, and what are the implications of not having a clear understanding of data origins and transformations on data sharing and collaboration?
- What are the key data analytics and machine learning algorithms that we can use in DataOps to analyze and optimize our supply chain and logistics operations, such as regression analysis, clustering analysis, and neural networks?
- How can data lineage and provenance be used to support data cataloging and data discovery, and what are the implications of not having a clear understanding of data origins and transformations on data exploration and analysis?
- How do you ensure that change management and version control are properly implemented and managed throughout the DataOps pipeline, particularly in industries where system changes can have significant regulatory implications?
- How can data lineage and provenance be used to support data security and access controls, and what are the implications of not having a clear understanding of data origins and transformations on data protection and privacy?
- How do we ensure that our security and compliance posture is scalable and adaptable to changing business requirements and new technologies, and what are the implications of security and compliance on our business agility?
- How can data lineage and provenance be used to support DevOps and Agile development practices, and what are the implications of not having a clear understanding of data origins and transformations on software development?
- How can data lineage and provenance be used to support AI and machine learning model development, and what are the implications of not having a clear understanding of data origins and transformations on model accuracy?
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 DataOps book in PDF containing 989 requirements, which criteria correspond to the criteria in...
Your DataOps 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 DataOps Self-Assessment and Scorecard you will develop a clear picture of which DataOps 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 DataOps 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 DataOps projects with the 62 implementation resources:
- 62 step-by-step DataOps Project Management Form Templates covering over 1500 DataOps project requirements and success criteria:
Examples; 10 of the check box criteria:
- Scope Management Plan: What are the risks that could significantly affect the communication on the DataOps project?
- Probability and Impact Assessment: Would avoiding any of corresponding impact the DataOps projects chance of success?
- Executing Process Group: Just how important is your work to the overall success of the DataOps project?
- Responsibility Assignment Matrix: Is work properly classified as measured effort, LOE, or apportioned effort and appropriately separated?
- Team Performance Assessment: To what degree are corresponding categories of skills either actually or potentially represented across the membership?
- Procurement Audit: Proper and complete records of transactions and events are maintained?
- Activity Duration Estimates: Will the new application negatively affect the current IT infrastructure?
- Resource Breakdown Structure: Goals for the DataOps project. What is each stakeholders desired outcome for the DataOps project?
- Risk Audit: Have all involved been advised of any obligations they have to sponsors?
- Risk Audit: Do industry specialists and business risk auditors enhance audit reporting accuracy?
Step-by-step and complete DataOps Project Management Forms and Templates including check box criteria and templates.
1.0 Initiating Process Group:
- 1.1 DataOps project Charter
- 1.2 Stakeholder Register
- 1.3 Stakeholder Analysis Matrix
2.0 Planning Process Group:
- 2.1 DataOps project Management Plan
- 2.2 Scope Management Plan
- 2.3 Requirements Management Plan
- 2.4 Requirements Documentation
- 2.5 Requirements Traceability Matrix
- 2.6 DataOps 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 DataOps 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 DataOps 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 DataOps 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 DataOps project with this in-depth DataOps Toolkit.
In using the Toolkit you will be better able to:
- Diagnose DataOps 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 DataOps 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 DataOps investments work better.
This DataOps 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.
