Global Learning for Operational Leaders
Course IMCS-003
Power BI: Data Mining and Big Data Analytics (IT Management and Cyber Security)
Classroom
14 sessions
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Online / Live
14 sessions
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Introduction
Course overview
Training Course Overview
As businesses increasingly generate vast amounts of data, the ability to transform this information into actionable insights has become a key competitive advantage.
Data mining and big data analytics offer organizations the ability to uncover hidden patterns, forecast future trends, and make informed decisions that drive growth and operational efficiency.
The Power BI: Data Mining and Big Data Analytics training course is designed to equip professionals with the skills needed to leverage the full potential of big data using Microsoft Power BI, one of the most powerful and intuitive tools for business intelligence and data analysis. This Course covers everything from importing and processing large datasets to applying advanced data mining techniques within Power BI. Participants will learn how to model and visualize complex data, identify significant patterns and relationships, and integrate predictive analytics using AI features. With a strong emphasis on practical application, the course is ideal for data analysts, business intelligence professionals, and decision-makers looking to extract valuable insights from big data and apply them to real-world challenges.
By the end of the course, attendees will have the expertise to tackle big data challenges, utilize advanced DAX functions for customized analytics, and design visually compelling dashboards that provide clear insights for strategic decision-making.
This training enables participants to not only analyze large datasets but also to drive data-driven initiatives within their organizations, turning data into a valuable competitive asset.
This training course will feature:
Overview of data mining and big data analytics in today’s data-centric world
Understanding the role of Power BI in analyzing large datasets
Key objectives of the course and expected outcomes for participants
What you will achieve
Learning objectives
- Equip participants with skills to process, visualize, and analyze large datasets using Power BI
- Understand data mining techniques and how they can be applied in Power BI
- Teach best practices for handling big data, from importing to transforming and visualizing
- Enable participants to use advanced analytics features, including predictive analytics and clustering
- Develop the ability to identify patterns, trends, and insights from large datasets
Who should attend
Target audience
- This training course is suitable to a wide range of professionals but will greatly benefit:
- Data analysts, business intelligence professionals, and IT specialists interested in big data analysis
- Business managers and decision-makers seeking to leverage big data insights for strategic planning
- Professionals in marketing, finance, operations, and research fields aiming to apply data mining techniques
- Learning Methods
- This training course will utilise a variety of proven adult learning techniques to ensure maximum understanding, comprehension and retention of the information presented.
- This includes theoretical presentation of the concepts, but the emphasis will be on the exercises performed by the delegates with the guidance of the instructor.
- The delegates will be “learning by doing” as the training course is designed for them to use the software on the real problems and real data applying each of the techniques themselves.
Complete course outline
Five focused days of learning and application
The timings provided are estimates and may vary depending on the number of participants and the discussions taking place during the sessions. They are indicative only and do not constitute a binding commitment.
Day 1
Introduction to Big Data and Power BI Essentials
- Understanding big data and its applications in business
- Overview of Power BI and its relevance to big data analytics
- Connecting to large data sources and managing data ingestion (SQL, Hadoop, Azure, etc.)
- Coffee break
- Connecting to large data sources and managing data ingestion (SQL, Hadoop, Azure, etc.) (continued)
- Introduction to Power Query for data transformation and cleansing
- Hands-on: Loading and preparing a large dataset in Power BI
Day 2
Data Modeling and Advanced Data Mining Techniques
- Building efficient data models to handle large datasets
- Introduction to data mining concepts: classification, clustering, and association
- Using DAX (Data Analysis Expressions) for calculated fields and complex measures
- Coffee break
- Using DAX (Data Analysis Expressions) for calculated fields and complex measures (continued)
- Applying data mining techniques with DAX in Power BI
- Hands-on: Creating data models and applying DAX for data mining
Day 3
Data Visualization and Identifying Patterns in Big Data
- Exploring visualizations optimized for big data in Power BI
- Using Power BI visuals to identify trends, patterns, and anomalies
- Interactive dashboards and drill-down features for big data insights
- Coffee break
- Interactive dashboards and drill-down features for big data insights (continued)
- Advanced visual techniques for clustering, classification, and segmentation
- Hands-on: Building a big data dashboard with advanced visualizations
Day 4
Advanced Analytics and AI Integration in Power BI
- Introduction to AI features in Power BI for predictive analysis and forecasting
- Leveraging the Key Influencers visual to detect trends and factors impacting outcomes
- Using Power BI’s Q&A and AI-driven clustering to enhance data mining
- Coffee break
- Using Power BI’s Q&A and AI-driven clustering to enhance data mining (continued)
- Applying machine learning models and integrating Azure Machine Learning with Power BI
- Hands-on: Implementing AI-powered analytics and predictive insights in Power BI
Day 5
Optimizing, Publishing, and Sharing Big Data Insights
- Optimizing big data reports and dashboards for performance and accessibility
- Publishing and securely sharing Power BI dashboards with stakeholders
- Integrating Power BI reports with Microsoft Teams and SharePoint for collaboration
- Case studies: Real-world applications of big data analytics using Power BI
- Coffee break
- Case studies: Real-world applications of big data analytics using Power BI (continued)
- Final Hands-on Project: Creating and presenting a comprehensive big data analytics dashboard
FAQ
Frequently asked questions
What does Power BI: Data Mining and Big Data Analytics (IT Management and Cyber Security) (IMCS-003) cover?
This course covers IT Management and Cyber Security through a structured five-day outline focused on practical application, discussion, and implementation planning.
When is the next available session?
The next scheduled session starts on 16 - 20 November 2026. See the course schedules section for the available dates and delivery formats.
Who should attend this course?
This training course is suitable to a wide range of professionals but will greatly benefit:, Data analysts, business intelligence professionals, and IT specialists interested in big data analysis, Business managers and decision-makers seeking to leverage big data insights for strategic planning
Is bilingual course delivery available?
Yes. All course materials and presentations are provided in English, while bilingual explanation and discussion support may be available depending on the selected location and trainer availability. For example, when attending a course in Istanbul, you may request a Turkish-speaking trainer to explain the English course content in Turkish. Arabic explanation support may also be requested at this location. Other languages are available in selected cities. You can choose your preferred language support as an optional preference during registration.
How can I register for a session?
Use any Register button next to the available course dates to open the participant registration page and submit your booking request for the selected session.
Is this course available online as well as classroom-based?
Check the course schedules section for currently published classroom and Online / Live sessions.
Where are classroom sessions delivered?
Current classroom venues include Barcelona, Dubai, Cape Town, Amsterdam, London, Istanbul, Munich, Paris, Frankfurt, Kuala lumpur, Rome, Vienna, Geneva, Madrid.
How long is the training programme?
The programme runs for five days, with up to five training hours per day, from 9:00 AM to 2:00 PM. Each programme includes a total of 25 training hours.
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