Provide technology agnostic technical leadership, drive technology stack selection and ensure the project team is setup for success on any number of Open Source, commercial, on premise and/or cloud based Data Engineering technologies.
More Uses of the Data Analytics Toolkit:
- Manage to clearly communicate instructions and sensitive information down the line for Data Analytics and Data Warehousing personnel to effectively execute duties.
- Collaborate with numerous departments across the business, advocating the proper use of Data Analytics, ensuring the delivery of desired operational results.
- Ensure you are likely to balance your time between engagement planning with other Data Analytics team members and actively analyzing complex data.
- Be accountable for developing Data Analytics frameworks, policies, and processes that comply with your organizations Architecture and Data Governance best practices.
- Evaluate and refine Data Analytics processes, methods, and tools to enhance understanding, performance, and efficiency in projects development and delivery.
- Develop and implement databases, Data Collections systems, Data Analytics and other strategies that optimize statistical efficiency and quality.
- Drive successful end to end project execution from post Sales Engagement, staffing plans, Requirements Gathering, design, development, deployment and support.
- Formulate: partner closely with business stakeholders and Data Stewards to identify and unlock opportunities and Data Quality issues identify relevant data sets needed for Data Analytics.
- Be accountable for preventing and detecting fraud is all about identifying potential risks using existing trends and emerging technology to accelerate intelligent Decision Making and build more efficient finance functions.
- Communicate highly technical results and methods clearly to clients, consider how to incorporate information into processes, and achieve high client satisfaction.
- Manage relationships between the business and technology and effectively support the needs of the business and drive change through the use of Data Analytics, automation and Digital Transformation.
- Supervise: leverage Data Analytics, workforce models and new innovation/automation to inform, advise, problem solve and influence decisions and outcomes that align the strategic priorities.
- Be accountable for assessing and prioritizing Data Analytics requirements in line with organization strategy, and recommending investment where appropriate.
- Create production tracking spreadsheets, historical trending reports and perform Data Analytics and provide feedback to management on conclusions.
- Make sure that your operation assess client Business Processes, Information Systems and Internal Controls, and perform advanced Data Analytics using technology based audit techniques.
- Assure your group assess and prioritize Data Analytics requirements in line with organization strategy, and recommending investment where appropriate.
- Provide leadership responsibility to embrace digital innovation to drive Continuous Improvement through Data Analytics to Reduce Risk and with a rigorous focus on leading indicators.
- Be accountable for creating and maintaining appropriate Data Analytics solution (in collaboration with ETL, Data Architecture, and business requirements) to support Enterprise Data Warehouse and BI capabilities.
- Establish that your enterprise leads the Data Analytics and Data Warehousing efforts in research, development, and implementation of appropriate data systems that lead to improved business performance and achievement of overall business goals.
- Coordinate: architecture technical direction for the development, design, and systems integration across multiple teams to drive the implementation of innovative Data Analytics solutions.
- Establish Software Development standards and processes along with best practices for the delivery of scalable and high quality software.
- Ensure you organize; lead the creation of new Data Driven approaches for the purpose of generating business insights through Data Analytics, information visualization, and addressing unanswered business issues in a proactive manner.
- Manage: data modernization helps customers make predictive, Data Driven decisions that accelerate innovation and increase ROI leveraging modern Data Analytics.
- Advise on exploratory, descriptive and predictive Data Analytics to a variety of projects and shape delivery of solutions that drive business value.
- Provide input on design and testing of various forecasting methodologies as it relates to loyalty points balance, customer behavior, and propensity to buy.
- Consult with executives to develop and implement an enterprise wide strategy that maximizes the value by your offerings in alignment with Customers objective.
- Ensure you are an expert in Big Data Analysis and know how to apply Machine Learning techniques to solve challenging data driving problems.
- Manage: work closely with other IT areas (IT Operations, PMO, applications, Data Analytics, and training) to implement new technology in accordance with Change Management best practices.
- Identify Data Analytics opportunities for the business for the business and ensure data/information compliance with business policy, legal, and compliance.
- Ensure you enhance; understand Customer Requirements and existing environments, and translate into configurations in AWS that meet performance, scalability, and availability needs.
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
- 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 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 Analytics improvements can be made.
Examples; 10 of the 999 standard requirements:
- What is in scope?
- How do you gather Data Analytics requirements?
- How do you stay flexible and focused to recognize larger Data Analytics results?
- What, related to, Data Analytics processes does your organization outsource?
- What information should you gather?
- Was a Data Analytics charter developed?
- What is Data Analytics risk?
- What creative shifts do you need to take?
- Will the controls trigger any other risks?
- Do the benefits outweigh the costs?
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 994 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:
- 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 Analytics project issues be unconditionally tracked through the Issue Resolution process?
- Closing Process Group: Did the Data Analytics project team have enough people to execute the Data Analytics 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 Analytics 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 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
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.