Training Course
Overview
Power BI Data Analytics for Managers is a practical,
management-focused training course designed to equip managers and business
professionals with the knowledge and skills required to transform
organizational data into meaningful insights and informed business decisions.
The course introduces Microsoft Power BI as a powerful business intelligence
and data analytics platform for connecting data sources, preparing information,
creating interactive dashboards, monitoring key performance indicators, and
communicating insights to stakeholders. Participants learn how managers can use
data analytics to improve operational performance, financial visibility,
customer service, workforce management, sales performance, and strategic
decision-making.
The course provides a structured introduction to the
Power BI environment, including Power BI Desktop, Power Query, data modeling,
relationships, calculated columns, measures, DAX fundamentals, visualizations,
dashboards, reports, filters, slicers, drill-downs, and interactive analytical
features. Participants work with practical business datasets and learn how to
import and clean data from Excel, CSV files, databases, and other common
sources. Emphasis is placed on understanding analytical concepts and
interpreting business information rather than advanced programming, enabling
managers to confidently work with Power BI and collaborate effectively with
data analysts and technical teams.
Power BI Data Analytics for Managers also covers advanced
managerial analytics, including KPI design, trend analysis, variance analysis,
profitability analysis, sales and customer analytics, operational performance
monitoring, forecasting concepts, and management reporting. Participants
explore how to build executive dashboards and analytical reports that provide
clear visibility into organizational performance. The course incorporates best
practices for data governance, visualization, accessibility, dashboard design,
data quality, security, and responsible use of business intelligence, while introducing
relevant concepts from data governance, business intelligence, and performance
management frameworks.
Through hands-on exercises, case studies, business
scenarios, and a practical capstone project, participants develop the ability
to translate raw organizational data into actionable management insights.
Participants learn how to identify important performance trends, investigate
business problems, communicate findings effectively, and support evidence-based
decision-making using Power BI. By the end of the course, managers will be able
to develop professional Power BI dashboards, interpret analytical results,
monitor organizational KPIs, identify performance opportunities, and establish
practical data-driven management reporting processes.
Course Duration
5 Days
Target Participants
·
Managers and senior managers
·
Department heads and team leaders
·
Business and operations managers
·
Finance and accounting managers
·
Sales and marketing managers
·
Human resource managers
·
Supply chain and procurement managers
·
Project and program managers
·
Business analysts and management analysts
·
Operations and performance improvement
professionals
·
Entrepreneurs and business owners
·
Professionals responsible for management
reporting and KPIs
·
Professionals seeking practical Power BI and
data analytics skills
Course Objectives
By the end of this Power BI Data Analytics for Managers
training course, participants will be able to:
·
Explain the principles of business intelligence
and data analytics for management.
·
Understand the Power BI ecosystem and its major
components.
·
Navigate Power BI Desktop and work with business
datasets.
·
Connect Power BI to Excel, CSV, databases, and
other common data sources.
·
Import, profile, clean, transform, and prepare
data using Power Query.
·
Understand data quality, data governance, and
data preparation principles.
·
Build effective data models and establish
relationships between tables.
·
Understand dimensions, facts, measures, and
basic star-schema concepts.
·
Create calculated columns and measures using
fundamental DAX.
·
Develop interactive charts, tables, cards, KPIs,
slicers, and dashboards.
·
Apply appropriate data visualization principles
for management reporting.
·
Analyze trends, variances, performance, and
business drivers.
·
Design management dashboards around strategic
and operational KPIs.
·
Apply Power BI to finance, sales, operations,
HR, supply chain, and customer analytics.
·
Use filters, drill-downs, drill-throughs,
bookmarks, and interactive reporting features.
·
Understand basic forecasting and time-based
analysis concepts.
·
Communicate data insights clearly to executives
and stakeholders.
·
Apply dashboard usability, accessibility, and
visualization best practices.
·
Understand Power BI security, sharing,
governance, and responsible data use.
·
Develop an integrated executive dashboard and
management analytics solution.
Course Content
Module 1: Power BI Data
Analytics for Managers
Day 1: Foundations of Power BI and Business Intelligence
1.
Introduction to Business Intelligence and Data
Analytics
o Definition
and purpose of business intelligence
o Descriptive,
diagnostic, predictive, and prescriptive analytics
o Role
of analytics in management decision-making
o Data-driven
versus intuition-based decision-making
2.
Power BI for Managers
o Overview
of the Microsoft Power BI platform
o Power
BI Desktop and Power BI Service
o Reports,
dashboards, semantic models, and datasets
o Managerial
applications of Power BI
3.
Navigating Power BI Desktop
o Power
BI interface
o Report,
data, and model views
o Fields,
visualizations, and filter panes
o Managing
report pages and workspaces
4.
Connecting to Business Data Sources
o Excel
workbooks
o CSV
and text files
o Databases
o Web
and cloud data sources
o Selecting
appropriate data sources
5.
Understanding Business Data Structures
o Rows,
columns, records, and fields
o Structured
and semi-structured data
o Dimensions
and measures
o Transactional
versus analytical data
6.
Data Quality Fundamentals
o Accuracy,
completeness, consistency, and timeliness
o Missing
and duplicate values
o Data
validation
o Common
data quality problems in management reporting
7.
Introduction to Power Query
o Power
Query environment
o Query
steps and transformations
o Data
type management
o Filtering
and sorting data
8.
Basic Data Transformation
o Removing
duplicates
o Handling
missing values
o Splitting
and merging columns
o Renaming
fields
o Standardizing
data formats
9.
Practical Exercise: Preparing a Management Dataset
o Import
a business dataset
o Identify
data quality issues
o Apply
basic transformations
o Prepare
the dataset for analysis
10. Case
Study: Replacing Manual Management Reporting
·
Analyze a manually prepared management report
·
Identify reporting inefficiencies
·
Determine opportunities for automation
·
Design an initial Power BI reporting approach
Day 2: Data Modeling, Power Query, and DAX Fundamentals
1.
Data Modeling Concepts
o Purpose
of data models
o Tables
and relationships
o Fact
and dimension tables
o Basic
star-schema principles
2.
Managing Relationships
o One-to-one
and one-to-many relationships
o Primary
and foreign keys
o Relationship
direction
o Identifying
relationship problems
3.
Building an Effective Power BI Model
o Model
organization
o Naming
conventions
o Date
tables
o Designing
models for management analysis
4.
Advanced Power Query Transformations
o Merging
queries
o Appending
queries
o Grouping
data
o Conditional
columns
o Custom
transformations
5.
Data Preparation Best Practices
o Query
organization
o Reusable
transformations
o Data
validation
o Refresh
considerations
o Maintaining
clean source data
6.
Introduction to DAX
o Purpose
of Data Analysis Expressions
o Measures
versus calculated columns
o Basic
DAX syntax
o Common
DAX functions
7.
Creating Basic Measures
o SUM
o AVERAGE
o COUNT
o DISTINCTCOUNT
o MIN
and MAX
o Practical
measure creation
8.
Calculated Columns and Business Logic
o When
to use calculated columns
o Creating
conditional calculations
o Categorizing
business records
o Comparing
calculated columns with measures
9.
Practical Exercise: Building a Management Data Model
o Transform
source datasets
o Create
relationships
o Develop
basic measures
o Validate
the analytical model
10. Case
Study: Integrating Multiple Business Data Sources
·
Combine sales, customer, and product data
·
Identify modeling challenges
·
Build an integrated data model
·
Prepare the model for management reporting
Day 3: Data Visualization, KPIs, and Management
Dashboards
1.
Principles of Effective Data Visualization
o Choosing
appropriate visualizations
o Matching
visuals to analytical questions
o Avoiding
misleading visualizations
o Visual
hierarchy and clarity
2.
Core Power BI Visualizations
o Bar
and column charts
o Line
charts
o Pie
and donut charts
o Tables
and matrices
o Cards
and KPI visuals
3.
Interactive Filters and Slicers
o Page-level
filters
o Report-level
filters
o Visual-level
filters
o Slicers
and selection controls
4.
Drill-Down and Drill-Through Analysis
o Hierarchical
analysis
o Drill-down
functionality
o Drill-through
pages
o Moving
from summary to detail
5.
Designing Management KPIs
o Key
Performance Indicators
o Leading
and lagging indicators
o Targets
and actual performance
o Variance
and threshold analysis
6.
Time-Based and Trend Analysis
o Date
hierarchies
o Monthly
and quarterly analysis
o Year-over-year
comparisons
o Trend
identification
7.
Dashboard Layout and User Experience
o Executive
dashboard design
o Information
hierarchy
o Visual
consistency
o Reducing
dashboard clutter
8.
Data Storytelling for Managers
o Identifying
the key message
o Highlighting
important trends
o Explaining
performance gaps
o Turning
analytics into actionable insights
9.
Practical Exercise: Building an Executive KPI Dashboard
o Select
management KPIs
o Create
interactive visuals
o Add
filters and drill-downs
o Develop
a management dashboard
10. Case
Study: Executive Performance Dashboard
·
Analyze organizational performance data
·
Identify important trends and exceptions
·
Design an executive dashboard
·
Present findings and management recommendations
Day 4: Advanced Managerial Analytics and Power BI
Applications
1.
Financial Analytics with Power BI
o Revenue
and expenditure analysis
o Profitability
analysis
o Budget
versus actual performance
o Cost
center reporting
o Financial
KPI dashboards
2.
Sales and Marketing Analytics
o Sales
performance
o Product
and customer analysis
o Sales
pipeline monitoring
o Conversion
and growth metrics
o Regional
and channel analysis
3.
Operations and Supply Chain Analytics
o Operational
KPIs
o Inventory
performance
o Procurement
analysis
o Supplier
performance
o Delivery
and fulfillment metrics
4.
Human Resources Analytics
o Workforce
analysis
o Headcount
trends
o Employee
turnover
o Absence
and attendance analysis
o Recruitment
performance
5.
Customer and Service Analytics
o Customer
segmentation
o Customer
satisfaction indicators
o Complaint
analysis
o Service
response times
o Retention
and churn analysis
6.
Advanced DAX for Managers
o CALCULATE
o FILTER
o IF
and SWITCH
o DIVIDE
o Basic
time-intelligence concepts
o Developing
reusable management measures
7.
Variance and Performance Analysis
o Actual
versus target
o Actual
versus budget
o Period-over-period
analysis
o Variance
percentages
o Identifying
performance drivers
8.
Forecasting and Predictive Analytics Concepts
o Forecasting
principles
o Trend-based
projections
o Scenario
analysis
o Predictive
analytics concepts
o Limitations
and responsible interpretation
9.
Practical Exercise: Cross-Functional Management
Analytics
o Analyze
finance, sales, operations, or HR data
o Develop
relevant KPIs
o Apply
DAX measures
o Identify
business insights and recommendations
10. Case
Study: Data-Driven Management Decision-Making
·
Analyze a business experiencing performance
challenges
·
Identify the most important performance drivers
·
Develop Power BI analysis
·
Present evidence-based management
recommendations
Day 5: Power BI Service, Governance, Best Practices, and
Capstone
1.
Introduction to Power BI Service
o Publishing
reports
o Workspaces
o Dashboards
and reports
o Sharing
and collaboration
o Managing
analytical content
2.
Report Refresh and Data Connectivity
o Data
refresh concepts
o Scheduled
refresh
o Data
source credentials
o Refresh
monitoring
o Managing
data dependencies
3.
Power BI Security and Access Management
o Data
access principles
o Workspace
roles
o Row-Level
Security concepts
o Protecting
sensitive business information
o Responsible
data sharing
4.
Data Governance and Management
o Data
ownership
o Data
quality controls
o Metadata
and documentation
o Governance
responsibilities
o Establishing
trusted reporting
5.
Power BI Dashboard Best Practices
o Consistent
design
o Appropriate
visual selection
o Clear
KPI definitions
o Accessibility
and readability
o Performance
considerations
6.
Business Intelligence Standards and Frameworks
o Data
governance principles
o Business
intelligence lifecycle
o Data
quality management
o Performance
management frameworks
o PDCA
and continuous improvement
7.
Management Reporting and Insight Communication
o Executive
reporting principles
o Communicating
analytical findings
o Distinguishing
facts, trends, and assumptions
o Developing
action-oriented recommendations
8.
Power BI Implementation and Change Management
o Identifying
reporting opportunities
o Stakeholder
requirements
o User
adoption
o Training
and support
o Measuring
reporting effectiveness
9.
Capstone Exercise: Building an Integrated Management
Dashboard
o Import
and transform a business dataset
o Build
a structured data model
o Create
DAX measures
o Develop
interactive KPI dashboards
o Analyze
trends and performance
o Present
actionable management insights
10. Final
Case Study, Assessment, and Analytics Roadmap
·
Analyze a comprehensive management analytics
scenario
·
Identify business questions and required KPIs
·
Develop and interpret Power BI reports
·
Present findings to a management audience
·
Complete a practical skills assessment
·
Develop a 90-day Power BI and data analytics
implementation roadmap