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Data-Driven Project Management with BI Tools

Utilize Business Intelligence (BI) tools to enhance decision-making processes in project management by harnessing data insights effectively

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Certificate :

After Completion

Start Date :

10-Jan-2025

Duration :

30 Days

Course fee :

$150

COURSE DESCRIPTION:

  1. Utilize Business Intelligence (BI) tools to enhance decision-making processes in project management by harnessing data insights effectively. 

  2. This course emphasizes the integration of data analytics and visualization platforms, including Power BI, Tableau, and Excel, to improve various aspects of project management such as planning, monitoring, and reporting. 

  3. Gain proficiency in employing these tools to collect, analyze, and interpret project-related data, which will facilitate informed decision-making.

  4. Discover strategies to leverage data visualization techniques that can lead to clearer communication of project status and performance metrics.

  5. Enhance project outcomes by applying data-driven insights to optimize resource allocation, risk management, and overall project execution.

CERTIFICATION:

  1. Earn a Certified Data-Driven Project Manager credential, demonstrating your ability to utilize BI tools for data-driven project management.

LEARNING OUTCOMES:

By the conclusion of the course, participants will possess the skills to:

– Recognize the significance of Business Intelligence (BI) in contemporary project management practices, emphasizing its impact on decision-making and efficiency.
– Leverage BI applications such as Power BI, Tableau, and Excel to gather, visualize, and interpret project-related data effectively.
– Design dynamic dashboards that facilitate the monitoring of key performance indicators (KPIs), project milestones, and overall performance metrics.
– Employ data visualization strategies to transform intricate project data into clear, actionable insights for stakeholders, enhancing communication and understanding.
– Integrate diverse project data sources, including project management tools, financial applications, and time-tracking systems, to create a comprehensive view of project health and progress.

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Course Curriculum

Introduction to Data-Driven Project Management
  1. What is Data-Driven Project Management?
    • Definition and importance of data-driven decision-making in project management.
    • Benefits of using data and Business Intelligence (BI) tools in managing projects.
    • Overview of key project management metrics and KPIs that can be tracked through BI tools.
  2. Overview of BI Tools in Project Management
    • Introduction to Business Intelligence (BI) and its role in project management.
    • Common BI tools for project management: Microsoft Power BI, Tableau, Qlik, etc.
    • How BI tools help in tracking project performance, resources, costs, and risks.
Key Metrics and KPIs for Project Management
  1. Common Project Management Metrics
    • Project performance metrics: cost variance (CV), schedule variance (SV), and earned value management (EVM).
    • Resource utilization metrics: resource allocation, workload, and availability.
    • Quality metrics: defect rate, customer satisfaction, and quality control.
  2. Tracking Key Performance Indicators (KPIs)
    • Defining KPIs for project success: time, cost, scope, and quality.
    • How to identify and set KPIs relevant to different types of projects (e.g., IT projects, construction, etc.).
    • Visualizing KPIs with BI tools.
Data Collection and Integration for Project Management
  1. Types of Project Data
    • Quantitative vs qualitative data in project management.
    • Financial, resource, and schedule data collection.
    • Performance and risk data.
  2. Integrating Data from Multiple Sources
    • How to gather data from various project management tools (e.g., MS Project, Trello, Asana).
    • Integrating financial data from ERP systems (e.g., SAP, Oracle).
    • Using API integrations and connectors to pull data into BI tools for reporting and analysis.
  3. Data Quality and Consistency
    • Ensuring data accuracy, completeness, and consistency.
    • Best practices for maintaining clean and reliable project data.
Visualizing Project Data with BI Tools
  1. Introduction to BI Tool Dashboards
    • Key components of a BI dashboard: charts, tables, and filters.
    • How dashboards can provide real-time insights into project status and health.
    • Best practices for designing intuitive and effective dashboards for project management.
  2. Building Interactive Reports and Dashboards
    • Using Microsoft Power BI/Tableau to create interactive reports for project managers.
    • Customizing reports based on project needs (e.g., financial performance, schedule health).
    • Using slicers, filters, and drilldowns to enable deeper insights into project data.
  3. Advanced Visualizations
    • Creating Gantt charts, heatmaps, and scatter plots for visualizing project timelines and progress.
    • Using KPIs and progress bars in BI dashboards for quick assessments.
    • Visualizing project risks, resource usage, and stakeholder engagement.
Project Performance Analysis with BI Tools
  1. Tracking Project Progress and Timelines
    • Using BI tools to visualize project timelines, milestones, and dependencies.
    • Analyzing schedule performance using visualizations such as Gantt charts.
    • Comparing actual vs. planned timelines and forecasting project completion dates.
  2. Cost and Budget Tracking
    • Monitoring project budgets using financial data visualizations.
    • Using BI tools to track project cost overruns and provide early warnings.
    • Visualizing cost variance, earned value, and cost performance index (CPI).
  3. Risk Management and Reporting
    • Identifying and analyzing project risks using BI dashboards.
    • Building risk dashboards with KPIs like risk exposure, mitigation progress, and issue resolution.
    • Forecasting potential risks using historical data and predictive analytics in BI tools.
Predictive Analytics for Project Success
  1. Introduction to Predictive Analytics in Project Management
    • How predictive analytics can forecast project outcomes (e.g., delays, budget overruns).
    • The role of machine learning and AI in predictive project management.
    • Key techniques used in predictive analytics: regression analysis, time-series forecasting, and classification models.
  2. Using BI Tools for Predictive Insights
    • Leveraging Power BI or Tableau’s built-in predictive features for forecasting project trends.
    • Integrating machine learning models into BI dashboards for more advanced predictions.
    • Analyzing historical project data to predict future performance.
Project Reporting and Communication
  1. Automating Reports and Alerts
    • How to automate periodic reports and real-time alerts on project status using BI tools.
    • Setting up scheduled report generation and email notifications for stakeholders.
    • Benefits of automated reporting: saves time and ensures consistency.
  2. Effective Communication with Data
    • How to present data insights to project stakeholders effectively.
    • Tailoring reports and dashboards to different audiences: project managers, executives, and team members.
    • Storytelling with data: turning raw data into actionable insights.
  3.  
Capstone Project
  1. End-to-End Project Management with BI Tools
    • Create a comprehensive BI dashboard for a real-world project.
    • Collect and integrate data from various project management tools, financial systems, and risk management logs.
    • Track project progress, costs, and risks using visualizations and predictive analytics.
    • Present the dashboard to stakeholders with insights and recommendations for project success.

Training Features

Hands-On Practice

Build and customize BI dashboards for real-world project scenarios.

Real-Time Reporting

Learn how to automate project reports and set up real-time alerts for critical project milestones.

Interactive Learning

Participate in live sessions, quizzes, and group discussions to enhance BI and project management skills.

Industry-Relevant Tools

Use popular BI tools like Microsoft Power BI, Tableau, and Qlik for project tracking and analysis.

Expert Guidance

Regular feedback from instructors and experts on BI tool usage, project analysis, and reporting.

Certification

A globally recognized certificate validating your expertise in using BI tools for project management.

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