Cursusdetails
Advanced Excel: Power Query & Power Pivots
Cursustaal: EN Cursusbeschrijving, lesmateriaal en uitvoering blijven in het Engels.
Cursusdetails
Cursustaal: EN Cursusbeschrijving, lesmateriaal en uitvoering blijven in het Engels.
Seminarinhoud
Microsoft Excel remains one of the most widely used tools for financial analysis, operational reporting, business intelligence, and management decision-making. However, traditional spreadsheet techniques can become inefficient when professionals work with large datasets, multiple data sources, repetitive reporting processes, and complex analytical requirements.
Power Query and Power Pivot extend Excel's analytical capabilities by enabling users to automate data preparation, combine information from different systems, establish relationships between datasets, and develop advanced calculations using Data Analysis Expressions (DAX). These tools help transform fragmented spreadsheets into structured, refreshable data models that support reliable reporting and more efficient analysis.
The Advanced Excel: Power Query & Power Pivots course provides participants with practical skills in data extraction, transformation, modelling, analysis, and interactive reporting. Participants learn how to connect Excel to external data sources, clean and reshape datasets, automate repetitive transformations, create relational data models, and develop powerful analytical measures.
The programme also explores advanced DAX calculations, time intelligence, PivotTables, PivotCharts, data model optimisation, and dashboard development. Through hands-on exercises, participants build an integrated Excel reporting solution that reduces manual work, improves data consistency, and supports faster, evidence-based business decisions.
Time-consuming manual data preparation: Automating repetitive data cleaning, formatting, consolidation, and transformation tasks through Power Query.
Fragmented information across multiple sources: Combining data from Excel workbooks, CSV files, databases, and other supported sources into consistent analytical datasets.
Spreadsheet errors and inconsistent reporting: Establishing repeatable transformation procedures, structured data models, and validation controls to improve reporting reliability.
Difficulty analysing large or complex datasets: Using Power Pivot and the Excel Data Model to analyse related tables without relying on extensive worksheet formulas.
Limited analytical capabilities in traditional PivotTables: Developing DAX measures for financial ratios, performance indicators, comparisons, and time-based analysis.
Inefficient recurring management reports: Creating refreshable reporting models that reduce manual consolidation and support consistent reporting cycles.
Poor visibility of business performance: Building interactive dashboards that present trends, variances, operational indicators, and management insights.
The programme is delivered through instructor-led demonstrations, practical Excel exercises, guided data modelling workshops, business reporting case studies, and hands-on analytical projects.
Participants work with realistic datasets covering financial transactions, sales performance, procurement expenditure, operational activities, and budget information. Exercises progress from data extraction and transformation to relational modelling, DAX calculations, PivotTable analysis, and interactive dashboard development.
The training emphasises practical application using Microsoft Excel with Power Query and Power Pivot functionality. Participants develop reusable data preparation workflows and reporting models that can be adapted to their organisational requirements.
By the end of this course, participants will be able to:
Understand the roles of Power Query, Power Pivot, and the Excel Data Model in business analysis
Connect Excel to multiple internal and external data sources
Clean, transform, combine, and restructure datasets using Power Query
Automate repetitive data preparation and consolidation activities
Apply basic Power Query M language concepts to customise transformations
Design relational data models using Power Pivot
Establish table relationships and apply appropriate data modelling principles
Develop calculated columns and measures using DAX
Apply advanced DAX functions for business and financial analysis
Perform time intelligence calculations and comparative performance analysis
Create interactive PivotTables, PivotCharts, and management dashboards
Optimise, validate, refresh, and maintain Excel-based analytical solutions
This course is suitable for:
Financial analysts and management accountants
Financial planning and analysis professionals
Business intelligence analysts
Data analysts and reporting specialists
Finance managers and financial controllers
Procurement and supply chain analysts
Operations and performance management professionals
Sales and commercial analysts
Internal auditors and compliance reporting professionals
Advanced Excel users responsible for data consolidation and management reporting
Participants will develop competencies in:
Advanced Excel data management
Power Query data extraction and transformation
Data cleaning and preparation automation
Multi-source data consolidation
Power Pivot relational data modelling
DAX formula development
Advanced financial and business analytics
Time intelligence and performance analysis
Interactive dashboard development
Data model optimisation and reporting automation
Voordelen
Methodiek
Doelgroep
Seminardetails
Understanding the Excel business intelligence environment and the relationships between Power Query, Power Pivot, PivotTables, and the Excel Data Model
Navigating the Power Query Editor and understanding queries, applied steps, data types, previews, and refresh behaviour
Connecting to Excel workbooks, CSV files, folders, and supported database sources using appropriate connection settings
Cleaning and standardising datasets through filtering, replacing values, removing duplicates, handling errors, and managing missing information
Transforming data structures using split columns, merged columns, conditional columns, grouping, pivoting, and unpivoting
Practical workshop: Importing and transforming a collection of financial and operational datasets into a consistent, analysis-ready structure
Combining multiple datasets using append queries and merge queries with appropriate join types and matching keys
Automating recurring file consolidation through folder-based imports, reusable transformations, and refreshable queries
Working with parameters, custom columns, conditional logic, and basic Power Query M expressions
Applying advanced transformations involving dates, text, numbers, nested data, and grouped calculations
Improving query reliability and performance through efficient transformation sequences, data validation, and appropriate loading options
Practical exercise: Developing an automated monthly reporting workflow that consolidates multiple source files and produces a validated analytical dataset
Understanding Power Pivot architecture, columnar data storage, and the advantages of relational data modelling over traditional spreadsheet lookups
Designing fact tables and dimension tables using star schema principles and appropriate data granularity
Creating and managing relationships between tables, including one-to-many relationships, unique keys, and filter direction
Distinguishing calculated columns, explicit measures, and implicit aggregations within the Excel Data Model
Developing foundational DAX measures using SUM, COUNTROWS, DISTINCTCOUNT, DIVIDE, CALCULATE, and related functions
Hands-on workshop: Building a relational Power Pivot model and developing core financial and operational performance measures
Understanding DAX evaluation context, including row context, filter context, and context modification using CALCULATE
Developing advanced analytical measures using FILTER, ALL, REMOVEFILTERS, SUMX, and other relevant DAX functions
Creating a dedicated date table and applying time intelligence calculations for year-to-date, quarter-to-date, and prior-period analysis
Building measures for growth rates, percentage contribution, running totals, budget variances, and actual-versus-target comparisons
Troubleshooting DAX calculations and improving analytical accuracy through measure validation and relationship analysis
Practical workshop: Creating an advanced performance analysis model with dynamic financial KPIs, period comparisons, and management reporting measures
Creating advanced PivotTables and PivotCharts connected to Power Pivot measures and relational data models
Designing interactive reporting interfaces using slicers, timelines, conditional formatting, and coordinated dashboard elements
Applying dashboard design principles to communicate trends, financial variances, operational performance, and key management insights
Optimising Power Query workflows and Power Pivot models through appropriate data types, reduced model complexity, efficient calculations, and controlled refresh processes
Establishing data validation, refresh procedures, documentation, access considerations, and maintenance practices for reusable Excel reporting solutions
Capstone exercise: Developing and presenting an Integrated Excel Business Intelligence Dashboard using Power Query for automated data preparation, Power Pivot for relational modelling, DAX for advanced calculations, and interactive visualisations for management decision-making
Data en locaties
Cursuscertificaat
Iedere deelnemer die dit seminar afrondt, ontvangt een professioneel cursuscertificaat van INFORAMTECH.
Informatie over
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