Business Analytics Course — fundamentals, data and visualization

Course overview

Description generated based on course syllabus and open data.

In this course you will learn the essentials of business analytics, manage and visualize data, and align teams around evidence to support decisions.

Who the business analytics course suits and when business analysis is not appropriate

Suitable for

• Beginners in business analysis who need a structured requirements and process framework.
• Product/Project managers aligning stakeholders and roadmaps.
• Marketing and finance professionals applying data analytics to business.
• Small business owners formalizing metrics and indicators.
• Data practitioners transitioning into BA and stakeholder work.

Not suitable for

• Those expecting deep programming or machine-learning–centric data science.
• Those seeking purely theoretical content without practical BA artifacts.
• Cases where only tool training (Excel/SQL/BI) is required without BA process.

Business problems and business analytics outcomes

Typical problems → expected outcomes

• Fragmented goals and metrics → aligned goal map, KPIs, and indicators.
• Ambiguous requirements → structured specifications (BRD, user stories, acceptance criteria).
• Manual processes → AS-IS/TO-BE models, bottleneck identification, prioritized changes.
• Low data visibility → dashboards and visualizations for transparent metrics.

Comparison with alternatives to learning business analysis

Self-study

• Pros: flexibility, low entry cost.
• Limits: fragmentation, challenging quality control of BA artifacts.

MBA, project/product vs business analysis

• MBA/PM/PO emphasize strategy and management, while business analysis details requirements and processes.

Tool-focused courses (Excel, SQL, BI) vs business analysis process

• Tools cover data handling; business analysis defines what to build, why, for whom, and how success is measured.

Results of completing a business analysis course

Competencies

• Formulating goals, hypotheses, and metrics; stakeholder engagement.
• Requirements elicitation, refinement, prioritization; process modeling.

Tools and artifacts

• BRD, user stories, backlog, acceptance criteria, RACI, roadmap.
• Basic data work and visualization (tables, charts, dashboards).