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Postgraduate Diploma in Operational Dashboards and Real-Time Analytics

800-hour online Postgraduate Diploma in Operational Dashboards and Real-Time Analytics. 8 modules covering ISO 22400-2, ISA-101.01 and Grafana. Assigned tutor and open enrolment.

Duration800 h
ModeOnline
AwardSEIUM Institute diploma
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Run a real engineering trade-off from this programme. Move the sliders, watch the model react in real time and beat the challenge.

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Learning outcomes

What you will be able to do

01

Design real-time operational data architectures.

02

Process data streams using windows and aggregations.

03

Apply visual design principles to operational dashboards.

04

Use industrial visualisation tools.

05

Detect anomalies and trends in real time.

06

Define and visualise key operational indicators.

07

Deploy and govern dashboard solutions on the shop floor.

Profile

Who it's for

  • Industrial data engineer seeking to specialise in Operational Dashboards and Real-Time Analytics.
  • Dashboard developer seeking to specialise in Operational Dashboards and Real-Time Analytics.
  • Operations analyst seeking to specialise in Operational Dashboards and Real-Time Analytics.
  • MES systems engineer seeking to specialise in Operational Dashboards and Real-Time Analytics.
  • Real-time data architect seeking to specialise in Operational Dashboards and Real-Time Analytics.
  • Continuous improvement manager seeking to specialise in Operational Dashboards and Real-Time Analytics.
  • Engineering or science graduates seeking to enter discrete manufacturing.
Standards & tools

What you'll work with

  • ISO 22400-2
  • ISA-101.01
  • ISA-95
  • IEC 62541
  • ISO 9241-11
  • IEC 62443-3-3
Syllabus

8 modules · 800 h

  1. 1.1Plant data sources
  2. 1.2Latency and update frequency
  3. 1.3Streaming architectures
  4. 1.4MQTT and Kafka message queues
  5. 1.5Time-series databases
  6. 1.6Asset data models
  7. 1.7Real-time data quality
  8. 1.8Unified Namespace (UNS) architecture
  9. 1.9Data contextualisation with metadata
  10. 1.10Practical: data flow from MQTT to a time-series database
  1. 2.1Event-driven processing
  2. 2.2Sliding and tumbling time windows
  3. 2.3Streaming aggregations
  4. 2.4Apache Kafka Streams
  5. 2.5Processing with Apache Flink
  6. 2.6Complex pattern detection
  7. 2.7Edge processing
  8. 2.8Fault tolerance in streaming
  9. 2.9Integrating streaming with databases
  10. 2.10Laboratory: window aggregation with Kafka
  1. 3.1Target audience and needs
  2. 3.2Visual design principles
  3. 3.3Information hierarchy
  4. 3.4Chart selection
  5. 3.5Use of colour
  6. 3.6Design for shop-floor displays
  7. 3.7Accessibility and panel legibility
  8. 3.8Usability testing
  9. 3.9Interaction and filtering in dashboards
  10. 3.10Workshop: production line dashboard prototype
  1. 4.1Grafana for operations
  2. 4.2Power BI in real time
  3. 4.3Panels with Node-RED Dashboard
  4. 4.4Visualisation with Ignition Perspective
  5. 4.5Web visualisation with JavaScript
  6. 4.6SCADA integration
  7. 4.7Alerts and notifications
  8. 4.8Access security
  9. 4.9Templates and panel reuse
  10. 4.10Practical: Grafana dashboard with alerts
  1. 5.1Online statistics
  2. 5.2Anomaly detection in streaming
  3. 5.3Real-time statistical process control
  4. 5.4Short-term forecasting
  5. 5.5Online learning models
  6. 5.6Event correlation
  7. 5.7Real-time root cause analysis
  8. 5.8Alert explanation
  9. 5.9Dynamic alert thresholds
  10. 5.10Laboratory: anomaly detection in streaming
  1. 6.1Real-time OEE
  2. 6.2Energy performance indicators
  3. 6.3Online quality indicators
  4. 6.4Maintenance indicators
  5. 6.5Production tracking by shift
  6. 6.6Comparison with targets
  7. 6.7Trend indicators
  8. 6.8Gamification and motivation
  9. 6.9Workplace safety indicators on the shop floor
  10. 6.10Case study: real-time OEE dashboard
  1. 7.1Scalable visualisation architectures
  2. 7.2Container deployment
  3. 7.3Data security
  4. 7.4Dashboard governance
  5. 7.5Version control
  6. 7.6User training
  7. 7.7Adoption measurement
  8. 7.8Continuous improvement of panels
  9. 7.9Performance and panel loading times
  10. 7.10Case study: multi-site dashboard deployment
  1. 8.1Definition of needs
  2. 8.2Data architecture
  3. 8.3Streaming pipeline
  4. 8.4Dashboard design
  5. 8.5Real-time analytics
  6. 8.6Selection of operational indicators
  7. 8.7User testing
  8. 8.8Analysis of results
  9. 8.9Report and presentation
  10. 8.10Final review with the tutor
Methodology, software & labs

How you'll learn

100% online training on the SEIUM Institute campus, with downloadable materials, recorded classes and an assigned technical tutor. There are no fixed timetables: students progress at their own pace within the intake, which makes it possible to combine the programme with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is Grafana, Apache Kafka, InfluxDB, Power BI, Ignition, in free, academic or evaluation versions. Tests are studied using real procedures for real-time OEE dashboards, anomaly detection in plant data streams and operational visualisation on workshop displays. Assessment is continuous across each module, plus the final integrating project.

Accredited laboratories(EN ISO/IEC 17025) with a rotor test rig, EMC/Lightning pre-compliance, HIL/SIL, vibration/acoustics.
Evidence-focused final project:safety case, test plan, compliance dossier and operational limits.
Industry mentorship:faculty with experience in training, , eVTOL/UAM and flight test.
Flexible format(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:a safety-by-design approach, with OT cybersecurity, DIH and compliance as its pillars.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Definition of needs

Design real-time operational data architectures.

Data architecture

Process data streams using windows and aggregations.

Streaming pipeline

Apply visual design principles to operational dashboards.

Dashboard design

Use industrial visualisation tools.

Real-time analytics

Detect anomalies and trends in real time.

Career opportunities

Where this takes you

Industrial data engineerDashboard developerOperations analystMES systems engineerReal-time data architectContinuous improvement manager
Admissions & scholarships

Requirements

  • Prior technical training or professional experience in the sector. No university degree is required.
  • Internet connection and a computer capable of running the programme's software.
  • Sufficient command of Spanish to follow technical standards documentation.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

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FAQ

Frequently asked questions

The programme totals 800 hours, spread over 6 to 8 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.

The programme uses Grafana, Apache Kafka, InfluxDB, Power BI and Ignition. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.

An own diploma from SEIUM Institute upon passing the continuous assessment and the integrating project. This is in-house training, not an official qualification from the Ministry.

Yes. Modules passed in a course or diploma in the same area can be credited towards the advanced programme. Please check the credit transfer policy when you enrol.

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