Power BI: Advanced Data Analysis Techniques
المقدمة
اهداف البرنامج
محتوى البرنامج
الشهادات
This course examines “Power BI: Advanced Data Analysis Techniques” through data preparation, exploratory analysis, visualization, reliable metrics and evidence-based reporting. Participants review practical workflows, assess assumptions and risks, and develop evidence-based improvement actions relevant to the stated subject and professional context.
الحصول على الكتيب
للحصول على كتيب بكامل محتويات الدورة برجاء ملء النموذج التالي ببياناتك الصحيحة
مارس
، 2027
الإنجليزية
براغ
$4,900.00
Programme Framework
Power BI: Advanced Data Analysis Techniques
Programme overview
This course examines “Power BI: Advanced Data Analysis Techniques” through data preparation, exploratory analysis, visualization, reliable metrics and evidence-based reporting. Participants review practical workflows, assess assumptions and risks, and develop evidence-based improvement actions relevant to the stated subject and professional context.
Learning outcomes
- ✓Frame a clear analytical question in the context of Power Data Analysis Techniques.
- ✓Check data quality and assumptions using a case involving Power Data Analysis Techniques.
- ✓Build meaningful indicators and charts when evaluating Power Data Analysis Techniques.
- ✓Communicate results and limitations with supporting evidence from Power Data Analysis Techniques.
- ✓Develop an applied assessment of Power BI: Data Analysis Techniques, with evidence, constraints and measurable improvements
- ✓Apply the subject framework to a documented professional scenario in the context of Power Data Analysis Techniques.
Who should attend
- Engineers and technical supervisors
- Maintenance and reliability professionals
- Technical project and quality specialists
Detailed programme outline
01Data sources and metric definitions
- Explain the key variables and assumptions in data sources and metric definitions in a professional case involving Power Data Analysis Techniques.
- Connect the topic to a measurable professional decision in the context of Power Data Analysis Techniques.
- Compare workable approaches to data sources and metric definitions against constraints in a professional case involving Power Data Analysis Techniques.
02Cleaning and quality checks
- Identify appropriate evidence and evaluation criteria for cleaning and quality checks when comparing alternatives for Power Data Analysis Techniques.
- Compare plausible methods against stated criteria when analysing applications of Power Data Analysis Techniques.
- Review implementation risks and traceability for cleaning and quality checks when comparing alternatives for Power Data Analysis Techniques.
- Define the concept and distinguish neighbouring technical terms when analysing applications of Power Data Analysis Techniques.
03Descriptive analysis and comparison
- Compare workable approaches to descriptive analysis and comparison against constraints in the context of Power Data Analysis Techniques.
- Identify the relevant inputs, assumptions and boundaries in a professional case involving Power Data Analysis Techniques.
- Document decision implications and limitations of descriptive analysis and comparison in the context of Power Data Analysis Techniques.
- Document limitations, responsible roles and follow-up actions in a professional case involving Power Data Analysis Techniques.
- Explain the key variables and assumptions in descriptive analysis and comparison in the context of Power Data Analysis Techniques.
04Visualization and reporting
- Review implementation risks and traceability for visualization and reporting when analysing applications of Power Data Analysis Techniques.
- Assess measurable performance criteria for visualization and reporting when comparing alternatives for Power Data Analysis Techniques.
- Document the data limitations and decisions for visualization and reporting when analysing applications of Power Data Analysis Techniques.
05Interpretation and action planning
- Document decision implications and limitations of interpretation and action planning in a professional case involving Power Data Analysis Techniques.
- Identify appropriate evidence and evaluation criteria for interpretation and action planning in the context of Power Data Analysis Techniques.
06Applied study: Power BI: Advanced Data Analysis Techniques
- Explain the key variables and assumptions in applied study: power bi: advanced data analysis techniques.
- Specify evidence that would confirm the intended outcome when analysing applications of Power Data Analysis Techniques.
- Compare workable approaches to applied study: power bi: advanced data analysis techniques against constraints.
07Engineering measurements and data
- Determine appropriate instruments and calibration needs in the context of Power Data Analysis Techniques.
- Assess uncertainty, repeatability and missing data in a professional case involving Power Data Analysis Techniques.
08Equipment and material selection
- Compare technical properties, operating envelopes and reliability when analysing applications of Power Data Analysis Techniques.
- Assess maintainability and total life-cycle implications when comparing alternatives for Power Data Analysis Techniques.
- Document reasons for component or process selection when analysing applications of Power Data Analysis Techniques.
- Evaluate applicability to a case involving Power BI: Advanced Data Analysis Techniques and document evidence limits.
- Define an outcome measure and review criteria for equipment and material selection when analysing applications of Power Data Analysis Techniques.
09Operations and maintenance
- Compare preventive and condition-based maintenance approaches in a professional case involving Power Data Analysis Techniques.
- Use trend data to distinguish degradation from noise in the context of Power Data Analysis Techniques.
10Instrumentation and process control
- Map sensors, control signals and operating constraints when comparing alternatives for Power Data Analysis Techniques.
- Interpret alarms, interlocks and diagnostic records when analysing applications of Power Data Analysis Techniques.
11Applied technical case
- Evaluate an anonymised technical data set in the context of Power Data Analysis Techniques.
- Develop and test competing engineering explanations in a professional case involving Power Data Analysis Techniques.
- Submit a structured recommendation with acceptance tests in the context of Power Data Analysis Techniques.
Training methodology
Evidence-based technical mini-lectures and guided discussion
Worked examples using anonymised or simulated professional data
Scenario analysis, calculations or design exercises as appropriate
Feedback against explicit, measurable assessment criteria
Practical deliverable
Practical deliverable
An applied portfolio for Power BI: Advanced Data Analysis Techniques, including an evidence-based case analysis, a documented decision or process design, and a verification plan.
Suggested assessment
An initial diagnostic, evidence-based practice exercises, and a final applied case assessed against explicit criteria for reasoning, technical accuracy, limitations and follow-up.
Educational outline only. Scope of practical activities and assessment is subject to the centre’s confirmed delivery plan.