Partner with Product Management, Product Design and Product Engineering to apply your expertise in Quantitative Analysis, Data Mining, and Statistical Modeling to see beyond the numbers and understand how your users interact with your consumer products to help drive product and business decisions.
More Uses of the Data Mining Toolkit:
- Be accountable for developing Standard Operating Procedures (SOP) for compute infrastructure, storage area network (SAN) hardware/software and related enterprise Backup and Recovery infrastructure.
- Ensure you are skilled in areas of Digital Marketing, decision management, inbound and real time marketing, Predictive Analytics and Data Mining or Campaign Management.
- Manage work with people across a range of disciplines to discover insights and identify opportunities using statistical, algorithmic, Data Mining, and Data Visualization methodologies.
- Apply techniques from Statistical Analysis and modeling, Business Intelligence, Data Mining, and other practices to highlight business opportunities found through analyzing client data.
- Apply your expertise in Quantitative Analysis, Data Mining, and the visualization of data in developing data informed strategies for growing and improving your product offerings and Customer Satisfaction.
- Pilot: Software Development.perience with scripting languages and software platforms related to advanced statistics, optimization, Data Mining and/or Machine Learning and visualization.
- Assure your operation deploys solutions utilizing Business Intelligence concepts; as, Data Mining, Predictive Analytics and Trend Analysis to provide management with insight into business.
- Confirm your operation ensures program metrics are aligned with business goals and objectives at all times, and maintains primary accountability for ensuring Quality Assurance standards are achieved consistently by front line team members in all Yield Management Contact Center locations.
- Ensure you boost; build production grade models on large scale datasets to optimize marketing performance by utilizing advanced Statistical Modeling, Machine Learning, or Data Mining techniques and marketing science research.
- Organize: research key business data using Statistical Analysis and Data Mining to understand historical patterns that can be utilized to improve business performance.
- Establish deterministic and probabilistic linkages between data sources and develop ways to extract and summarize the sought information in the data using a wide variety of statistical, Data Mining and Machine Learning techniques.
- Be certain that your corporation complies; is proactive in calling attention to Service Delivery deficiencies or opportunities and offers concrete suggestions for improving Processes And Systems that affect quality of care and productivity.
- Be accountable for working closely with Network Operations, Systems Operations, Product, Sales And Marketing teams to understand business problems and develop suitable predictive models.
- Develop: general understanding and wide application of advanced principles, theories, concepts, tools, and techniques in integrating, analyzing, and designing and reporting on large and diverse data sets; Data Mining; analytics, and statistics.
- Drive: influence stakeholders to make product/service improvements that yield customer/business value by effectively making compelling cases through storytelling, visualizations, and other influencing tools.
- Assure your organization understands and facilitates the integration of Business Processes, people, and relevant technology to identify, configure, and communicate useful information.
- Be certain that your planning provides tactical and Strategic Direction in the areas of Business Intelligence analytics, Data Mining and visualization and assessment of Data Quality and consistency across platforms, products and business areas.
- Evaluate: Data Mining platform incidents that have occurred during the week and creating dashboards, graphs, charts, etc highlighting critical trends and patterns to Key Stakeholders throughout your organization.
- Be certain that your operation develops predictive and prescriptive models to address complex problems, discover insights, and identify opportunities using Machine Learning, Statistical Techniques, and Data Mining.
- Quantify relationships between internal and external factors on business outcomes, identify and profile market and customer segments, and predict employee and customer behaviors.
- Drive: after spending considerable time exploring the need for better alignment models across diverse organizations, you have developed a framework and methodology based on insights from extensive research.
- Be accountable for learning how to evaluate, cleanse, design, and implement Data Models using Data Mining techniques; understand Business Intelligence and relational database concepts.
- Establish that your organization demonstrates full commitment to Quality Improvement initiatives by taking an active role, being a positive model and by encouraging others to be equally committed and accountable.
- Initiate: conduct requirements (business and functional) analysis, requirements traceability, Data Mining, Data Profiling, data/information research, cleansing, identify data anomalies, post load data/load quality checks.
- Manage: on going analysis of the maintenance (preventative and repair) process to identify opportunities for process and system improvements, efficiency gains, and Cost Reduction through the use of various Supply Chain applications and Data Mining tools.
- Enable more meaningful reporting for management and operational use that is aligned with organization objects and easily updated to reflect evolving Business Needs.
- Manage work with Data Analytics partners to use Data Mining and Statistical Techniques to validate or identify operational inefficiencies, exceptions, and fault/event correlation.
- Be accountable for utilizing multiple quantitative and qualitative datasets from a variety of sources and interpreting results using various techniques, ranging from simple data aggregation to Statistical Analysis to complex Data Mining.
- Secure that your design recommends and justifies Strategic Sourcing initiatives by using Data Mining tools to conduct Spend Analysis, prepare supporting reports/spreadsheets and comparisons.
- Automate common development, testing, Data Mining, and Data Manipulation tasks using DevOps tools, macros, scripts, and advanced MetaData Analysis techniques.
Save time, empower your teams and effectively upgrade your processes with access to this practical Data Mining Toolkit and guide. Address common challenges with best-practice templates, step-by-step Work Plans and maturity diagnostics for any Data Mining 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 Mining specific requirements:
STEP 1: Get your bearings
- The latest quick edition of the Data Mining 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 Mining improvements can be made.
Examples; 10 of the 999 standard requirements:
- Are decisions made in a timely manner?
- How do you provide a safe environment -physically and emotionally?
- How do you measure risk?
- How can the phases of Data Mining development be identified?
- Why do you expend time and effort to implement measurement, for whom?
- Where is the data coming from to measure compliance?
- Are pertinent alerts monitored, analyzed and distributed to appropriate personnel?
- Are supply costs steady or fluctuating?
- What evidence is there and what is measured?
- What is the extent or complexity of the Data Mining problem?
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 Mining book in PDF containing 994 requirements, which criteria correspond to the criteria in...
Your Data Mining 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 Mining Self-Assessment and Scorecard you will develop a clear picture of which Data Mining 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 Mining 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 Mining projects with the 62 implementation resources:
- 62 step-by-step Data Mining Project Management Form Templates covering over 1500 Data Mining 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 Mining project issues be unconditionally tracked through the Issue Resolution process?
- Closing Process Group: Did the Data Mining project team have enough people to execute the Data Mining 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 Mining 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 Mining Project Management Forms and Templates including check box criteria and templates.
1.0 Initiating Process Group:
- 1.1 Data Mining project Charter
- 1.2 Stakeholder Register
- 1.3 Stakeholder Analysis Matrix
2.0 Planning Process Group:
- 2.1 Data Mining 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 Mining 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 Mining 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 Mining 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 Mining 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 Mining project with this in-depth Data Mining Toolkit.
In using the Toolkit you will be better able to:
- Diagnose Data Mining 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 Mining 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 Mining investments work better.
This Data Mining 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.