Role description as a Data Engineering, you bring Software Engineering Best Practices to production and maintenance of analytics code and bring an engineering mindset to considerations on how data is modeled from its source to its use in the Data Warehouse as business data and Reporting Data.
More Uses of the Data Warehouse Toolkit:
- Head: conduct full Data Lifecycle analysis; engaging thE Business in Requirements Gathering, performing analysis and collection of data, subsequently developing and implementing a solution.
- Drive integration of organization wide data into a centralized Data Warehouse and modeled to support Data Analysis requirements from all functional groups.
- Adhere to Data Strategy, policies, controls, and programs to ensure the Enterprise Data is accurate, complete, secure, and reliable.
- Ensure your organization supports the definition and elicitation of Data Warehouse strategy as an active participant in the Enterprise Analytics Governance Process.
- Determine database structural requirements by working with internal Business Stakeholders, and identifying optimal database specifications.
- Manage work on extract, transform, and load (ETL) processes/projects, individually or as part of or in conjunction with a database/Data Warehouse team.
- Ensure all employees share the responsibility for maintaining a Workplace Culture of dignity, respect, understanding and appreciation of individual and group differences.
- Manage work with BI development and the office of Information Technology to support Complex Data models and a robust semantic layer that produces easily understood data sets for functional users.
- Create and maintain Data Governance discipline across your organization to ensure a consistent view of data across your organization.
- Be certain that your group leads or facilitates the analysis of industry, technology and Market Trends to determine potential impacts on the enterprises Data Warehouse strategy and architecture requirements.
- Manage work with various customer groups to develop thE Business Data Collection and access layer across various Business Intelligence products.
- Create a Real Time Data capability that enables systems and Customer Support teams to act instantly on consumer and third party generated data.
- Manage work with Data Architects to build models that conform to Data Modeling and design standards, tools, Best Practices, and related development for enterprise Data Models.
- Evaluate: design/architect/ implement/deploy scalable and fault tolerant Enterprise Solutions for Data Platforms, integration and analytics.
- Ensure your design leads the effort to change, primarily by championing the change to elicit support, evolving the process of Data Warehouse Architecture so that it delivers value.
- Evaluate and implement Emerging Technology as Cloud Data Warehouse appliances, real time streaming, predictive/prescriptive/diagnostic and Descriptive Analytics, Data Visualization, and Cloud based Big Data.
- Methodize: monitor and project Data Storage requirements and costs, and put in place mitigating factors to Reduce Costs without adversely affecting warehouse performance.
- Lead: work closely with the engineering and Development Teams to identify non Functional Requirements, build out Data Visualizations and Data Access capabilities in support of Business Requirements.
- Secure that your team applies Data Warehouse Architecture principles using conceptual logical and physical modeling tools to provide access to data to the enterprise.
- Identify: Data Integration incorporate new business and system data into the chop Data Warehouse while maintaining enterprise Best Practices and adhering to Data Governance standards.
- Arrange that your enterprise develops Data Structures for Data Warehouses and Data Mart projects and initiatives; and supports data Analytics and Business Intelligence systems.
- Keep abreast of new Data Storage, delivery, analysis, visualization, reporting techniques and software to develop more powerful Data Infrastructure.
- Assure your enterprise complies; Solutions Support enterprise Information Management, master Data Management, Business Intelligence, Machine Learning, Data Science, and other business interests.
- Manage work with Application Developers and other stakeholders to determinE Business need and apply Industry Standards to all database solutions created.
- Develop and implement approaches, policies, and standards to ensure Data Quality and integrity is maintained and that any inaccurate data is uncovered and corrected.
- Make sure that your business has used at least one of your organization of the art Data Warehouse packages available in practical application of moderate difficulty.
- Arrange that your project complies; awareness of Data Governance practices, business and technology issues related to management of enterprise Information Assets and approaches related to Data Protection.
- Identify: design, development, Unit Testing, System Testing and Change Management for development, enhancements and fixes related to enterprise reports and processes.
- Establish that your design rolls out enterprise wide Data Governance framework, with focus on organization, policies, principles and standards, and Governance Metrics.
- Confirm your organization develops the Core Data Warehouse environment to ensure that the Data Warehouse Architecture outputs are used to bring about positive change through effective use of data.
Save time, empower your teams and effectively upgrade your processes with access to this practical Data Warehouse Toolkit and guide. Address common challenges with best-practice templates, step-by-step Work Plans and maturity diagnostics for any Data Warehouse 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 Warehouse specific requirements:
STEP 1: Get your bearings
- The latest quick edition of the Data Warehouse 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 Warehouse improvements can be made.
Examples; 10 of the 999 standard requirements:
- What are you attempting to measure/monitor?
- What sources do you use to gather information for a Data Warehouse study?
- To what extent does each concerned units Management Team recognize Data Warehouse as an effective investment?
- Who do you think the world wants your organization to be?
- Is there an established Change Management process?
- Scope of sensitive information?
- How can you improve performance?
- Does the goal represent a desired result that can be measured?
- Have changes been properly/adequately analyzed for effect?
- Why is Data Warehouse important for you now?
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 Warehouse book in PDF containing 994 requirements, which criteria correspond to the criteria in...
Your Data Warehouse 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 Warehouse Self-Assessment and Scorecard you will develop a clear picture of which Data Warehouse 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 Warehouse 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 Warehouse projects with the 62 implementation resources:
- 62 step-by-step Data Warehouse Project Management Form Templates covering over 1500 Data Warehouse 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 Warehouse project issues be unconditionally tracked through the Issue Resolution process?
- Closing Process Group: Did the Data Warehouse Project Team have enough people to execute the Data Warehouse 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 Warehouse 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 Warehouse Project Management Forms and Templates including check box criteria and templates.
1.0 Initiating Process Group:
- 1.1 Data Warehouse project Charter
- 1.2 Stakeholder Register
- 1.3 Stakeholder Analysis Matrix
2.0 Planning Process Group:
- 2.1 Data Warehouse 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 Warehouse 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 Warehouse 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 Warehouse 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 Warehouse 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 Warehouse project with this in-depth Data Warehouse Toolkit.
In using the Toolkit you will be better able to:
- Diagnose Data Warehouse 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 Warehouse 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 Warehouse investments work better.
This Data Warehouse 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.