Professional Certificate 10 Modules 150 Lessons

Business Analytics and Data Visualization (Power BI and Tableau)

Description

Program summary

This online program develops analytic thinking and visualization skills for decision support. Beyond tool usage, you will learn KPI design, dashboard structure, and data storytelling to create clear, action-oriented reporting. The emphasis is on linking business questions to meaningful metrics and designing visualizations that reduce misinterpretation risk.
Format: Delivered online. If a specific program includes live sessions, an on-campus visit, or any in-person component, this will be clearly stated on the program page.
What you will gain:
• Design consistent KPI frameworks and metric dictionaries
• Build dashboard structures aligned with business questions
• Communicate insights clearly through data storytelling
• Reduce misinterpretation risks with visualization best practices
Who should attend:
Analysts, reporting teams, business stakeholders, product/growth teams, and managers who rely on dashboards.
Course outline
1. Analytics workflow: question → metric → data → insight → action
2. KPI design: metric dictionary, targets, thresholds
3. Dashboard principles: layout, hierarchy, filtering, usability
4. Power BI & Tableau: modeling concepts and visual selection
5. Data storytelling: executive-ready narratives and context
6. Applied practice: dashboard wireframes and critique

Modules

10

What is included

Lessons

150

Review the module structure and lesson flow before enrollment.

Content sections

4

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Course Curriculum

Module roadmap

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Module 1

Foundations of Business Analytics

15 Lessons

Module 2

Data Preparation and Transformation

16 Lessons

Module 3

Power BI: Core Skills and Interface

16 Lessons
Business Analytics and Data Visualization (Power BI and Tableau)

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What is included

Course Curriculum

Review the module structure and lesson flow before enrollment.

10 Modules 150 Lessons
1

What Is Business Analytics: Types, Applications and Value

2

The Analytics Landscape: Descriptive, Diagnostic, Predictive and Prescriptive

3

Data Thinking: Asking the Right Business Questions

4

Understanding Data Types: Structured, Unstructured and Semi-Structured

5

Data Sources in Business: Databases, APIs, Files and Streams

6

The Analytics Workflow: From Raw Data to Business Decision

7

Key Metrics and KPIs: Designing Meaningful Measures

8

Data Quality: Completeness, Accuracy, Consistency and Timeliness

9

Introduction to Statistics for Business Analysts

10

Probability and Distributions: What Every Analyst Must Know

11

Correlation, Causation and the Dangers of Spurious Relationships

12

Sampling and Estimation: Drawing Conclusions from Partial Data

13

Hypothesis Testing: Making Evidence-Based Decisions

14

Communicating Analytical Findings to Non-Technical Stakeholders

15

Ethics and Bias in Business Analytics

1

Data Collection and Integration: Connecting to Multiple Sources

2

Data Cleaning: Handling Missing Values, Duplicates and Errors

3

Data Transformation: Reshaping, Pivoting and Aggregating Data

4

Working with Dates and Times in Analytics

5

Text Data Preparation: Parsing, Splitting and Standardising

6

Data Normalisation and Standardisation for Analysis

7

Joining and Merging Data from Multiple Tables

8

Introduction to SQL for Business Analysts

9

Advanced SQL: Window Functions, CTEs and Subqueries

10

Excel for Data Preparation: Power Query and Data Transformation

11

Data Profiling: Understanding Your Dataset Before You Analyse It

12

Building Reusable Data Preparation Workflows

13

Data Governance and Documentation for Analytics Teams

14

Introduction to Python for Data Preparation

15

Introduction to R for Business Analytics

16

Data Wrangling with Python Pandas: Practical Techniques for Analysts

1

Power BI Ecosystem: Desktop, Service, Mobile and Embedded

2

Power BI Interface: Navigating Reports, Data and Model Views

3

Connecting to Data Sources in Power BI Desktop

4

Power Query in Power BI: Transforming Data Before It Loads

5

Building Your First Power BI Report: Fields, Visuals and Pages

6

The Power BI Data Model: Tables, Relationships and Cardinality

7

Introduction to DAX: Calculated Columns and Measures

8

DAX Fundamentals: CALCULATE, FILTER, ALL and Context

9

Time Intelligence in DAX: YTD, MTD, Rolling Averages and Growth

10

Advanced DAX: Variables, SWITCH, RANKX and Iterators

11

Row-Level Security in Power BI

12

Power BI Service: Publishing, Workspaces and Sharing

13

Scheduling Data Refresh and Gateway Configuration

14

Power BI Apps and Deployment Pipelines

15

Performance Optimisation in Power BI: Data Models and Visuals

16

Power BI Dataflows and Reusable Data Preparation at Scale

1

Custom Visuals in Power BI: AppSource and Building Your Own

2

Drill-Through, Drill-Down and Cross-Report Navigation

3

Bookmarks, Buttons and Conditional Formatting

4

Dynamic Titles, Tooltips and Report Personalisation

5

What-If Parameters and Scenario Analysis in Power BI

6

AI Visuals: Key Influencers, Decomposition Tree and Q&A

7

Power BI and Excel Integration: Analyse in Excel and Live Connections

8

Paginated Reports in Power BI: Pixel-Perfect Reporting

9

Power BI Embedded: Integrating Analytics into Applications

10

Power BI Administration: Tenant Settings, Capacity and Governance

11

Microsoft Fabric and the Future of Power BI

12

Real-Time Dashboards and Streaming Datasets in Power BI

13

Power BI for Finance: P&L, Balance Sheet and Cash Flow Reports

14

Power BI for Sales and Marketing Analytics

15

Power BI for Operations and Supply Chain Reporting

1

Tableau Ecosystem: Desktop, Server, Online and Public

2

Tableau Interface: Shelves, Cards, Marks and the Data Pane

3

Connecting to Data Sources in Tableau

4

Dimensions, Measures, Discrete and Continuous Fields

5

Building Your First Tableau Visualisation: Rows, Columns and Marks

6

Tableau Data Relationships, Joins and Blends

7

Calculated Fields in Tableau: Formulas, Logic and String Functions

8

Table Calculations: Running Total, Percent of Total and Rank

9

Level of Detail Expressions: FIXED, INCLUDE and EXCLUDE

10

Filters in Tableau: Extract, Data Source, Context and View Filters

11

Parameters and Dynamic Controls in Tableau

12

Sets and Groups: Segmenting Your Data for Analysis

13

Tableau Prep: Data Cleaning and Shaping for Tableau

14

Publishing to Tableau Server and Tableau Online

15

Tableau Data Extracts and Incremental Refresh Strategies

1

Dashboard Design in Tableau: Layout, Actions and Interactivity

2

Advanced Chart Types in Tableau: Bump Charts, Slope Charts and Sparklines

3

Mapping in Tableau: Geographic Visualisations and Spatial Analysis

4

Statistical Analysis in Tableau: Reference Lines, Bands and Box Plots

5

Forecasting and Trend Lines in Tableau

6

Cluster Analysis and Tableau's Built-In Analytics

7

Tableau Extensions and JavaScript API

8

Tableau Embedding and Integration with Web Applications

9

Performance Optimisation in Tableau: Extracts, Queries and Dashboards

10

Tableau Server Administration: Sites, Permissions and Content Management

11

Tableau for HR and People Analytics

12

Tableau for Operations and Supply Chain Analytics

13

Tableau vs Power BI: When to Use Which Tool

14

Storytelling with Data in Tableau: Storypoints and Narrative Flow

15

Tableau Pulse and AI-Powered Insights in Tableau Cloud

1

The Principles of Effective Data Visualisation

2

Choosing the Right Chart Type for Your Data and Message

3

Visual Perception: How the Brain Reads Charts and Graphs

4

Colour Theory for Data Visualisation: Scales, Palettes and Accessibility

5

Typography and Layout in Dashboard Design

6

Avoiding Common Visualisation Mistakes and Misleading Charts

7

Designing for Accessibility: Colour-Blindness, Screen Readers and Contrast

8

Mobile-First Dashboard Design: Responsive Layouts and Touch Interaction

9

Executive Dashboards vs Operational Dashboards: Design Principles

10

Self-Service Analytics: Designing Reports for Non-Technical Users

11

Data Storytelling: Structure, Narrative and Insight Communication

12

Annotating Charts and Guiding the Reader's Eye

13

Advanced Dashboard UX: Navigation, Filtering and User Experience

14

Benchmark and Comparison Visualisations: Before and After, Target vs Actual

15

Small Multiples and Faceted Charts for Multi-Dimensional Comparison

1

Exploratory Data Analysis: Finding Patterns Before You Build Reports

2

Cohort Analysis: Understanding Customer Behaviour Over Time

3

Funnel Analysis: Conversion, Drop-Off and Optimisation

4

RFM Analysis: Segmenting Customers by Recency, Frequency and Monetary Value

5

Pareto Analysis and the 80/20 Rule in Business Analytics

6

A/B Testing and Experimentation: Design, Analysis and Interpretation

7

Regression Analysis for Business: Predicting Outcomes from Data

8

Forecasting Methods: Moving Averages, Exponential Smoothing and ARIMA

9

Clustering and Segmentation: Grouping Customers and Products

10

Decision Trees and Classification for Business Problems

11

Natural Language Processing Basics for Analysts: Sentiment and Text Analysis

12

Anomaly Detection: Identifying Outliers and Unusual Patterns

13

Network Analysis and Relationship Mapping for Business

14

Monte Carlo Simulation for Business Risk Analysis

1

Data Warehouses and Data Marts: Architecture and Design Principles

2

Data Lakes and Lakehouses: Modern Data Storage for Analytics

3

ETL and ELT Pipelines: Moving and Transforming Data at Scale

4

Star Schema and Snowflake Schema: Dimensional Modelling for BI

5

Cloud Analytics Platforms: Azure Synapse, Google BigQuery and AWS Redshift

6

Data Mesh and Federated Analytics: Decentralised Data Ownership

7

Building a Data Catalogue and Metadata Management

8

Master Data Management: Consistency Across Systems and Reports

9

Analytics Maturity Model: Assessing and Improving Your Organisation

10

Data Strategy: Building an Analytics-Driven Organisation

11

BI Tool Selection and the Business Case for Analytics Investment

12

Managing the Analytics Team: Roles, Skills and Structures

13

Agile Analytics: Iterative Development for BI Projects

1

Financial Reporting Dashboard: P&L, Variance Analysis and Forecasting

2

Sales Performance Dashboard: Pipeline, Revenue and Team Analytics

3

Marketing Analytics Dashboard: Campaign, Channel and Funnel Analysis

4

HR and People Analytics Dashboard: Headcount, Turnover and Diversity

5

Supply Chain and Operations Dashboard: Inventory, Lead Time and Quality

6

Customer Analytics Dashboard: Churn, Lifetime Value and Segmentation

7

Healthcare Analytics Dashboard: Patient Outcomes and Operational KPIs

8

Retail Analytics Dashboard: Store Performance, Basket Analysis and Forecasting

9

Real Estate Analytics Dashboard: Portfolio, Valuation and Market Trends

10

End-to-End Analytics Project: From Business Question to Deployed Dashboard

11

Presenting Your Analytics Work: Building a Portfolio and Case Studies

12

Certification Pathways: PL-300 Power BI, Tableau Desktop Specialist and Beyond

13

Freelance and Consulting in Business Analytics: Getting Started

14

The Future of Business Analytics: AI Copilots, Augmented Analytics and Trends

15

AI and Generative Analytics: Copilot, NotebookLM and the Analyst of Tomorrow

16

Course Conclusion: Your Analytics Career Starts Here

Program details

Content sections

Review the sections below and open only the one you need. The summary panel on the side keeps the long explanation separate and readable.

Click the Add to Cart button. Complete the purchase process by filling in the required information. Once your payment has been confirmed, your login credentials and access details will be sent to the email address you provided during registration. Use the information sent via email to log in to the learning platform and start the course immediately.
The programs are open to: University students, Recent graduates, Public and private sector employees, Engineers, technicians, and specialists, Managers and management candidates, Professionals seeking to advance their careers, Individuals looking to enhance their digital skills, Anyone interested in gaining competencies in a new field.
Participants who successfully complete the program will: Gain up-to-date knowledge and skills relevant to their field; Develop professional competencies in line with international standards; Adapt to digital transformation and the evolving requirements of the future workforce; Acquire new skills that support career development and professional growth; Receive a verifiable digital certificate documenting their learning achievements; Strengthen their commitment to lifelong learning and continuous professional development. Certificates are issued in digital format and can be verified online through the certificate verification system.
The training programs are offered in Turkish and English and are delivered entirely online. Participants who successfully complete the program will receive a digital certificate. No physical certificate or printed document will be issued or delivered. Upon completion of the application and registration process, access information and login credentials for the training platform will be sent to the email address provided during registration. Participants may access the platform using the credentials provided and follow all training activities online throughout the program.