Big Data Analytics Toolkit

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Be accountable for ongoing projects focus on text understanding, machine reasoning, deep generative models, robust representation learning, few shot/zero shot learning, interpretable models, Data Visualization, Deep Learning systems, and deep Reinforcement Learning, among others.

More Uses of the Big Data Analytics Toolkit:

  • Develop enterprise level asset intelligence BI reporting analytics environments to support Business Intelligence and Big Data Analytics.

  • Provide input on design and testing of various forecasting methodologies as it relates to loyalty points balance, Customer Behavior, and propensity to buy.

  • Identify recurring problems and bottlenecks that might be improved through upgrades to your software product, new technologies in the analytics team infrastructure, or further research into statistical methodology.

  • Promote technical readiness and capability of database and analytics services by driving organizational initiatives across multiple geographies to develop and share Best Practices.

  • Manage It Security and Data Governance to ensure that your organizations Data Analytics and integration products are effectively secured and that risks are mitigated.

  • Be accountable for ensuring highly available, secure, and compliant infrastructure to cost effectively support all your business critical needs, whether in on premise, cloud/multi cloud, or hybrid deployments.

  • Warrant that your group serves as a resource to advise management and business stakeholders on use of quality Business Analytics, tools, and methods to improve efficiency, accuracy, and interpretation of various business metrics.

  • 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.

  • Ensure you introduce; lead Cloud Architecture, design and development that supports diagnostic instruments, with a focus on Data Architecture, Big Data Analytics, microservices, and database services.

  • Ensure you train; lead development of custom predictive and prescriptive algorithms interfacing with large data sets, based on principles from statistics, machinE Learning, and Operations Research.

  • Make sure that your enterprise provides support by mining data to identify behavior patterns, predict trends, and forecast outcomes to support Data Driven decisions to drive change in your customer interactions and Risk Management.

  • Manage: from Big Data Analytics, to cognitive digital twins and Data Driven strategy consulting and startup acceleration work to make your customers even more successful.

  • Develop, maintain, and continuously improve media mix modeling, mass media attribution, multi touch attribution, and other models to support the optimization of marketing spend.

  • Develop, maintain, and continuously improve customer churn, customer acquisition, and customer value models to inform go to market strategy and drive improved profitability.

  • Manage work with large structured / Unstructured Data sets, various rest/wms data services, multiple database programs and collection systems, in a modeling and analytical environment, solving hard intelligence problems and issues.

  • Drive successful end to end project execution from post Sales Engagement, staffing plans, Requirements Gathering, design, development, deployment and support.

  • Make sure that your enterprise finds and recommends new uses for existing data sources; designs modify, and builds new data processes; and builds large, complex data sets.

  • Perform Data Analysis, data model design, data linking, implementation, testing, debugging, documenting, and maintenance of several applications.

  • Head: architecture, design, configure, automate, and manage reliable, scalable, and secure Cloud Infrastructure for IoT services, Big Data Analytics, and cloud based applications.

  • Develop productive relationships with Business Unit leaders across your organization to influence how Data Integration technology solutions can enable new sources of value.

  • Become a consumer lending data expertise, utilizing the Data Warehouse to inform modeling approaches, understand Customer Behavior, research outliers, and prepare data for usage by the quantitative modeling team.

  • Communicate highly technical results and methods clearly to clients, consider how to incorporate information into processes, and achieve high client satisfaction.

  • Manage work with Application Management team, and where necessary, other members of the analytics team to efficiently execute larger scale analytic deliverables and operationalize the results.

  • Consult with executives to develop and implement an enterprise wide strategy that maximizes the value by your offerings in alignment with Customers objective.

  • Take on specific ETL projects to assimilate data from multiple new structured and Unstructured Data sources in batch or real time, as appropriate.

  • Be accountable for publishing is an integral part of your activities as a means for calibrating the quality of the research and to ensure staying at the forefront of technology.

  • Recognize and drive opportunities to lead technical considerations in designing Data Lakes, Data Warehouses, IT Operations analytics based on MachinE Learning methodologies, and similar large scale Data products.

  • Be certain that your corporation complies; address aspects as Data Privacy and security, data ingestion and processing, Data Storage and compute, analytical and operational consumption, Data Modeling, Data Virtualization, self service data preparation and analytics, AI enablement, and API integrations.

  • Be accountable for working closely with the various teams Data Science, database, network, BI and application teams to make sure that all the Big Data applications are highly available and performing as expected.

  • Be accountable for ensuring that the technologies, processes, and culture transform data into an activE Business asset that helps drive the strategy of your organization forward.

 

Save time, empower your teams and effectively upgrade your processes with access to this practical Big Data Analytics Toolkit and guide. Address common challenges with best-practice templates, step-by-step Work Plans and maturity diagnostics for any Big 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 Big Data Analytics specific requirements:


STEP 1: Get your bearings

Start with...

  • The latest quick edition of the Big 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 Big Data Analytics improvements can be made.

Examples; 10 of the 999 standard requirements:

  1. What is your theory of human motivation, and how does your compensation plan fit with that view?

  2. What are your personal philosophies regarding Big Data Analytics and how do they influence your work?

  3. Scope of sensitive information?

  4. What are the timeframes required to resolve each of the issues/problems?

  5. What methods do you use to gather Big Data Analytics data?

  6. What information do you gather?

  7. Are you relevant? Will you be relevant five years from now? Ten?

  8. How will the data be checked for quality?

  9. What are the essentials of internal Big Data Analytics management?

  10. Which measures and indicators matter?


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 Big Data Analytics book in PDF containing 994 requirements, which criteria correspond to the criteria in...

Your Big 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 Big Data Analytics Self-Assessment and Scorecard you will develop a clear picture of which Big 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 Big 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 Big Data Analytics projects with the 62 implementation resources:

Examples; 10 of the check box criteria:

  1. Cost Management Plan: Eac -estimate at completion, what is the total job expected to cost?

  2. Activity Cost Estimates: In which phase of the Acquisition Process cycle does source qualifications reside?

  3. Project Scope Statement: Will all Big Data Analytics project issues be unconditionally tracked through the Issue Resolution process?

  4. Closing Process Group: Did the Big Data Analytics Project Team have enough people to execute the Big Data Analytics project plan?

  5. Source Selection Criteria: What are the guidelines regarding award without considerations?

  6. Scope Management Plan: Are Corrective Actions taken when actual results are substantially different from detailed Big Data Analytics project plan (variances)?

  7. Initiating Process Group: During which stage of Risk planning are risks prioritized based on probability and impact?

  8. Cost Management Plan: Is your organization certified as a supplier, wholesaler, regular dealer, or manufacturer of corresponding products/supplies?

  9. Procurement Audit: Was a formal review of tenders received undertaken?

  10. Activity Cost Estimates: What procedures are put in place regarding bidding and cost comparisons, if any?

 
Step-by-step and complete Big Data Analytics Project Management Forms and Templates including check box criteria and templates.

1.0 Initiating Process Group:


2.0 Planning Process Group:


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 Big 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 Big Data Analytics 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 Big Data Analytics project with this in-depth Big Data Analytics Toolkit.

In using the Toolkit you will be better able to:

  • Diagnose Big 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 Big 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 Big Data Analytics investments work better.

This Big 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.