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Power BI & Excel Dashboards for Maintenance & Reliability Training Course

Turns maintenance system data into clear Excel and Power BI dashboards that support decisions on availability, reliability, workload, cost and spare parts.

MAI · Maintenance EngineeringAll Levels#2335ClassroomEnglish , Arabic
Duration
5 Days
Download BrochureView Upcoming Dates

Free substitution at any time · 30+ days' notice: full refund minus 10%. Cancellation policy

Course Overview

The Maintenance & Reliability Dashboards with Excel & Power BI Training Course equips maintenance, reliability, and asset management professionals with the practical skills to turn maintenance system data into clear, reliable dashboards that support better decisions on availability, reliability, workload, cost, and spare parts. In oil and gas, petrochemicals, power, water and utilities, manufacturing, mining, transport, facilities management, and government asset-owning organizations, computerized maintenance management systems hold large amounts of work order, failure, cost, and inventory data, yet this data is often underused because it is incomplete, difficult to extract, or presented in long tables that do not highlight problems or priorities. The course combines maintenance and reliability performance concepts with hands-on Excel and Power BI skills. Participants learn to select meaningful maintenance and reliability KPIs based on recognized industry metrics, including availability, mean time between failures, mean time to repair, overall equipment effectiveness, preventive maintenance and schedule compliance, backlog, planned and reactive work, maintenance cost, and spare parts performance. The program covers extracting and cleaning data from maintenance systems, improving data quality, building analyses and dashboards in Excel using Power Query, pivot tables, and charts, and building interactive dashboards in Power BI using data models, DAX measures, drill-down, and bad actor and Pareto analysis. Participants also learn dashboard design for technicians, planners, engineers, and managers, publishing and refreshing reports, and establishing dashboard governance. The course is delivered through intensive hands-on exercises using realistic maintenance datasets. Participants leave with a maintenance and reliability KPI definition library, a data quality checklist, working Excel and Power BI dashboards, a DAX measure library for maintenance KPIs, and a dashboard design and governance guide. This course builds practical dashboard skills and is not an official Microsoft certification program.

Learning Objectives

  • Analyze the role of dashboards and data-driven decision making in maintenance and reliability management on Day 1.
  • Select maintenance and reliability KPIs informed by recognized industry metrics and aligned with organizational objectives.
  • Define KPIs consistently, including formulas, data sources, frequency, targets, and ownership.
  • Extract maintenance data from computerized maintenance management and enterprise asset management systems.
  • Assess and improve maintenance data quality, including work order coding, failure data, and cost allocation.
  • Clean, transform, and combine maintenance data using Excel Power Query.
  • Analyze maintenance performance using Excel formulas, pivot tables, and charts and build Excel dashboards.
  • Build Power BI data models for maintenance and reliability data.
  • Develop DAX measures for availability, mean time between failures, mean time to repair, compliance, backlog, and cost KPIs.
  • Apply reliability analysis techniques, including bad actor identification and Pareto analysis, within dashboards.
  • Design dashboards tailored to technicians, planners, reliability engineers, and managers using effective visualization principles.
  • Publish, share, and refresh dashboards and establish dashboard governance and continuous improvement practices by the end of Day 5.

Who Should Attend

This course is designed for maintenance engineers, reliability engineers, maintenance planners and schedulers, maintenance supervisors and managers, and asset management professionals who analyze or report maintenance performance. It is also relevant for CMMS administrators, maintenance data analysts, performance and excellence professionals, and business intelligence specialists supporting maintenance functions. It is particularly valuable for professionals in oil and gas, petrochemical, refining, power, water, and utility organizations; in manufacturing, mining, and industrial facilities; in transport, airports, ports, and rail operators; in facilities management providers; and in ministries, municipalities, and government entities managing public assets. Participants should be comfortable using Excel; no prior Power BI experience is required.

Learning Outcomes

  • Explain how dashboards improve maintenance and reliability decisions.
  • Choose a focused set of meaningful maintenance and reliability KPIs.
  • Define KPIs clearly so they are calculated consistently.
  • Extract and prepare data from maintenance systems.
  • Identify and correct common maintenance data quality problems.
  • Clean and combine data efficiently with Power Query.
  • Build practical maintenance dashboards in Excel.
  • Build interactive maintenance and reliability dashboards in Power BI.
  • Write DAX measures for key maintenance KPIs.
  • Identify bad actors and priority failures using Pareto analysis.
  • Design dashboards that meet the needs of different users.
  • Publish, maintain, and improve dashboards over time.

Course Outline

Day 1

Maintenance and Reliability KPIs and Data Foundations

  • The role of dashboards in maintenance and reliability management
  • Maintenance and reliability KPIs informed by recognized industry metrics
  • Defining KPIs: formulas, data sources, frequency, targets, and ownership
  • Maintenance data sources and common data quality issues
  • Practical application: participants select and define KPIs for a case study maintenance organization and assess data quality
Day 2

Data Preparation and Excel Analysis

  • Extracting data from maintenance management systems
  • Cleaning, transforming, and combining data with Power Query
  • Calculating KPIs with Excel formulas and pivot tables
  • Charting maintenance performance trends
  • Practical application: participants prepare maintenance data and calculate key KPIs in Excel
Day 3

Building Excel Dashboards and Reliability Analysis

  • Excel dashboard layout and design
  • Interactive elements: slicers, timelines, and dynamic charts
  • Bad actor identification and Pareto analysis
  • Backlog, compliance, and cost analysis
  • Practical application: participants build an Excel maintenance and reliability dashboard
Day 4

Power BI for Maintenance and Reliability

  • Power BI data models for maintenance data
  • DAX measures for availability, mean time between failures, mean time to repair, compliance, backlog, and cost
  • Interactive visuals, drill-down, and filters
  • Asset hierarchy and time-based analysis
  • Practical application: participants build a Power BI maintenance and reliability dashboard
Day 5

Dashboard Design, Publishing, and Governance

  • Designing dashboards for technicians, planners, engineers, and managers
  • Visualization principles and data storytelling
  • Publishing, sharing, and refreshing dashboards
  • Dashboard governance, data ownership, and continuous improvement
  • Final workshop: participants finalize and present a complete maintenance and reliability dashboard with key insights and recommended actions

Upcoming Dates

CityDatesPrice per ParticipantEarly Bird
AmsterdamScheduled
9 – 13 Nov 2026€6,000—
BangkokScheduled
16 – 20 Nov 2026€6,700—
BakuScheduled
16 – 20 Nov 2026€5,300—
BarcelonaScheduled
23 – 27 Nov 2026€6,000€5,400until 2 Nov
BerlinScheduled
30 Nov – 4 Dec 2026€6,300€5,670until 9 Nov
CairoScheduled
7 – 11 Dec 2026€3,800€3,420until 16 Nov
CasablancaConfirmed
14 – 18 Dec 2026€4,700€4,230until 23 Nov
DammamScheduled
21 – 25 Dec 2026€4,800€4,320until 30 Nov
DohaScheduled
28 Dec 2026 – 1 Jan 2027€4,700€4,230until 7 Dec
DubaiScheduled
3 – 7 Jan 2027€4,700€4,230until 14 Dec
FrankfurtScheduled
4 – 8 Jan 2027€6,200€5,580until 14 Dec
GenevaScheduled
11 – 15 Jan 2027€7,300€6,570until 21 Dec
IstanbulScheduled
18 – 22 Jan 2027€5,300€4,770until 28 Dec
Kuala LumpurScheduled
25 – 29 Jan 2027€4,700€4,230until 4 Jan
LisbonScheduled
1 – 5 Feb 2027€6,000€5,400until 11 Jan
LondonScheduled
8 – 12 Feb 2027€5,800€5,220until 18 Jan
MadridScheduled
15 – 19 Feb 2027€6,000€5,400until 25 Jan
MadinahScheduled
15 – 19 Feb 2027€4,800€4,320until 25 Jan
MakkahConfirmed
22 – 26 Feb 2027€4,800€4,320until 1 Feb
ManamaScheduled
1 – 5 Mar 2027€5,300€4,770until 8 Feb
MarrakeshScheduled
8 – 12 Mar 2027€4,700€4,230until 15 Feb
MilanScheduled
15 – 19 Mar 2027€7,000€6,300until 22 Feb
MunichScheduled
22 – 26 Mar 2027€6,000€5,400until 1 Mar
MuscatScheduled
29 Mar – 2 Apr 2027€6,300€5,670until 8 Mar
OnlineScheduled
4 – 8 Apr 2027€2,700€2,430until 15 Mar
ParisScheduled
5 – 9 Apr 2027€6,700€6,030until 15 Mar
RiyadhScheduled
12 – 16 Apr 2027€4,800€4,320until 22 Mar
RomeScheduled
19 – 23 Apr 2027€7,000€6,300until 29 Mar
SingaporeScheduled
19 – 23 Apr 2027€9,100€8,190until 29 Mar
ViennaScheduled
26 – 30 Apr 2027€6,400€5,760until 5 Apr

Available in: Istanbul · Dubai · London · Riyadh · Doha · Amsterdam

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