Support a variety of revenue, productivity, cost and other impactful initiatives through Complex Data Modeling, sampling, and analysis projects that have applicability across geographical boundaries and Customer Segments.
More Uses of the Data Model Toolkit:
- Lead: design and drive the creation of new standards and Best Practices in the use of statistical Data Modeling, Big Data and optimization tools.
- Assure your corporation develops and recommends Architecture Framework based on the logical Data Model for operational stores, Data Marts, and Content Management stores.
- Initiate: constantly be testing new ideas, obtaining measurable results that can be used to make business decisions, and partner with the data teams on strategies involving Data Models and machinE Learning solutions.
- Perform Data Management, as Master Data, Metadata, Data Architecture, Data Governance, Data Quality, and Data Modeling while utilizing technologies.
- Standardize: design, build, and launch collections of sophisticated Data Models and visualizations that support multiple Use Cases across different products or domains.
- Identify and promote Best Practices and patterns for Data Modeling and provide oversight for all activities related to Data Cleansing, Data Quality and Data Consolidation using standard Data Modeling methodologies.
- Be accountable for reviewing and approving Data Designs for compliance with enterprise Best Practice guidelines and standards for data, Metadata, Data Modeling, and management.
- Develop Data Models and visualizations that efficiently translate business data into digestible information to the different stakeholders.
- Establish that your design applies Data Analysis and Data Modeling techniques to establish, modify, and maintain Data Structure and associated components.
- Provide architectural and Data Model oversight for processes which perform Data Extraction, transformation, Workflow Management and Data Quality check.
- Provide activity and Data Modeling, developing modern business methods, identifying Best Practices and creating and assessing performance measurements.
- Develop algorithms, Data Modeling framework, and approaches that support the Digital Intelligence features on your roadmap.
- Supervise: Data Modeling, coding, analytical modeling, Root Cause Analysis, investigation, debugging, testing and collaboration with the Business Partners, Product Managers, architects and Engineering teams.
- Utilize a combination of Data Modeling, Information Engineering, and sampling to ensure efficient and comprehensive designs.
- Be certain that your project establishes and applies Data Modeling practices and Data Architecture options; provides guidance and support to stakeholders.
- Manage advanced knowledge and expertise with Data Modelling, Data Aggregation, standardization, linking, Quality Check mechanisms and reporting.
- Be accountable for managing of consulting engagements pertaining to Data Architecture, Data Models design and implementation, and Agile Data Modeling techniques.
- Be accountable for designing of finance technology architectures, finance Data Models that are part of Technology Modernization initiatives and benchmarking/standard industry practices.
- Ensure you advance; build the enterprise conceptual and logical Data Models for analytics, operational and Data Mart structures in accordance to industry Best Practices models.
- Pilot: partner with IT Resources to enable appropriate Data Flow/Data Model, development using appropriate tools/technology, Rapid Prototyping and informs the design of analytical products.
- Steer: design logical and Physical Data Model using relevant Business Intelligence Tools to standardize data sources for visualization and reporting.
- Be involved in different stages of the lifecycle (Data Model design, Query Tuning and Optimization, Operational Management and troubleshooting).
- Head: partner with enterprise IT Team to ensure governance of Project Management tool (wave) and expand reporting capabilities.
- Develop Technical Architecture designs which support a robust solution that considers User Requirements, Technical Requirements, Data Models, architectures, etc.
- Be accountable for developing and maintaining Data Models through analysis and Solution Design, detailed Data Design, Data Model and Design Quality management and data implementation.
- Provide input to and execute development of logical and physical enterprise Data Models; Enterprise Master Data and reference Data Models; MetaData Models; and Data Catalogs.
- Provide search engine optimization, Data Modeling, and integration Best Practices and optimization guidance throughout engagements to drive customer ROI.
- Steer: partner with product owners, Data Engineers and Business Systems analysts to identify data mappings and generate Enterprise Analytics Data Models.
- Drive: implement Data Strategies, build Data Flows and develop and maintain conceptual, logical, and physical Data Models to established standards.
- Oversee: partner closely with a team of people analysts, Business Intelligence analysts, and engineers to evolve your Talent Acquisition Data Model and design consumable, high impact dashboards and visualizations.
Save time, empower your teams and effectively upgrade your processes with access to this practical Data Model Toolkit and guide. Address common challenges with best-practice templates, step-by-step Work Plans and maturity diagnostics for any Data Model 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 Model specific requirements:
STEP 1: Get your bearings
- The latest quick edition of the Data Model 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 Model improvements can be made.
Examples; 10 of the 999 standard requirements:
- What is the scope of the Data Model effort?
- Does the Data Model task fit the client's priorities?
- How has the Data Model data been gathered?
- Identify an operational issue in your organization, for example, could a particular task be done more quickly or more efficiently by Data Model?
- What are evaluation criteria for the output?
- How is data used for Program Management and improvement?
- Act/Adjust: What Do you Need to Do Differently?
- What is the Big Data Model idea?
- How will you know that you have improved?
- How do you measure progress and evaluate training 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 Model book in PDF containing 994 requirements, which criteria correspond to the criteria in...
Your Data Model 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 Model Self-Assessment and Scorecard you will develop a clear picture of which Data Model 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 Model 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 Model projects with the 62 implementation resources:
- 62 step-by-step Data Model Project Management Form Templates covering over 1500 Data Model project requirements and success criteria:
Examples; 10 of the check box criteria:
- Cost Management Plan: Eac -estimate at completion, what is the total job expected to cost?
- Activity Cost Estimates: In which phase of the Acquisition Process cycle does source qualifications reside?
- Project Scope Statement: Will all Data Model project issues be unconditionally tracked through the Issue Resolution process?
- Closing Process Group: Did the Data Model Project Team have enough people to execute the Data Model Project Plan?
- Source Selection Criteria: What are the guidelines regarding award without considerations?
- Scope Management Plan: Are Corrective Actions taken when actual results are substantially different from detailed Data Model Project Plan (variances)?
- Initiating Process Group: During which stage of Risk planning are risks prioritized based on probability and impact?
- Cost Management Plan: Is your organization certified as a supplier, wholesaler, regular dealer, or manufacturer of corresponding products/supplies?
- Procurement Audit: Was a formal review of tenders received undertaken?
- Activity Cost Estimates: What procedures are put in place regarding bidding and cost comparisons, if any?
Step-by-step and complete Data Model Project Management Forms and Templates including check box criteria and templates.
1.0 Initiating Process Group:
- 1.1 Data Model project Charter
- 1.2 Stakeholder Register
- 1.3 Stakeholder Analysis Matrix
2.0 Planning Process Group:
- 2.1 Data Model 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 Model 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 Model 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 Model 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 Model project or Phase Close-Out
- 5.4 Lessons Learned
With this Three Step process you will have all the tools you need for any Data Model project with this in-depth Data Model Toolkit.
In using the Toolkit you will be better able to:
- Diagnose Data Model 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 Model 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 Model investments work better.
This Data Model 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.