
Systems Analysis, Data Analytics, and Management Accounting Course
Master the three disciplines that drive modern business performance: systems analysis, data analytics, and management accounting. This course equips you with the tools to diagnose organisational problems, build predictive models, and produce financial reports that inform strategic decisions. From requirements elicitation to capital investment appraisal, every skill is grounded in real business application.
What you'll learn:
Model organisational systems, define requirements, and assess technical and operational feasibility.
Apply descriptive, diagnostic, and predictive analytics techniques to real business datasets.
Construct budgets, perform variance analysis, and evaluate product costs using multiple costing methods.
Build interactive dashboards and management reports that combine financial and operational insights.
Use regression, clustering, and time-series forecasting to support data-driven planning and control.
Evaluate capital investments, pricing strategies, and divisional performance using integrated analytical frameworks.
How you study in practice Systems Analysis, Data Analytics, and Management Accounting Course
How you practise Systems Analysis, Data Analytics, and Management Accounting Course
For businesses looking to train their team
With Dedika for businesses, the course includes exercises and examples tailored to your own business and the way your company needs.
Course content
8 Chapters • 37 LessonsDuration between 4 and 360 hours (you decide)
Chapter 1HideHide detailsSee detailsFoundations of Systems Thinking
Foundations of Systems Thinking
Lesson 1 • Introduction to Process Modelling
Introduces flowcharts and basic process diagrams as tools for visualising system behaviour. Prepares students for more advanced modelling techniques in later chapters.
Lesson 2 • Core Concepts of Systems Theory
Introduces open vs. closed systems, entropy, and emergence as applied to organisations. Establishes vocabulary used throughout all subsequent chapters.
Lesson 3 • Problem Identification and Scoping
Teaches structured techniques for defining business problems before analysis begins. Prevents scope creep by establishing clear problem boundaries early.
Lesson 4 • Organisational Systems and Structures
Maps how departments, processes, and data flows form an organisational system. Connects structural design to information needs and decision-making.
Chapter 2HideHide detailsSee detailsSystems Analysis Methods and Tools
Systems Analysis Methods and Tools
Lesson 1 • Data Flow and Entity Modelling
Introduces data flow diagrams and entity-relationship models as complementary analysis tools. Links data structures to business processes identified in Chapter 1.
Lesson 2 • Functional and Non-Functional Requirements
Distinguishes between what a system must do and how well it must perform. Teaches writing precise, testable requirement statements.
Lesson 3 • Use Case and User Story Development
Teaches use case diagrams and agile user stories as user-centred specification tools. Bridges traditional and agile analysis approaches.
Lesson 4 • Requirements Elicitation Techniques
Covers interviews, workshops, surveys, and observation as methods for gathering system requirements. Emphasises selecting the right technique for each stakeholder context.
Lesson 5 • Feasibility and Impact Assessment
Evaluates technical, operational, and financial feasibility of proposed system changes. Produces a structured feasibility report as a deliverable.
Chapter 3HideHide detailsSee detailsData Foundations for Analytics
Data Foundations for Analytics
Lesson 1 • Database Structures and Data Storage
Explains relational database design, normalisation, and the role of data warehouses. Connects storage architecture to retrieval efficiency for analytics.
Lesson 2 • Data Types and Measurement Scales
Classifies data as nominal, ordinal, interval, or ratio and explains analytical implications of each. Grounds subsequent statistical and visualisation work in correct data handling.
Lesson 3 • Data Quality Assessment and Cleansing
Identifies common data quality issues including missing values, duplicates, and inconsistencies. Applies systematic cleansing procedures to produce analysis-ready datasets.
Lesson 4 • Data Governance and Ethics
Covers data ownership, access controls, privacy principles, and ethical use of personal data. Establishes responsible data practices required in all analytics work.
Chapter 4HideHide detailsSee detailsDescriptive and Diagnostic Analytics
Descriptive and Diagnostic Analytics
Lesson 1 • Root Cause Diagnostic Techniques
Applies Pareto analysis, fishbone diagrams, and drill-down techniques to identify performance drivers. Bridges descriptive findings to actionable management insights.
Lesson 2 • Descriptive Statistics for Business
Covers measures of central tendency, dispersion, and distribution shape applied to business datasets. Provides the statistical foundation for all subsequent analytical techniques.
Lesson 3 • Correlation and Trend Analysis
Introduces correlation coefficients, scatter plots, and time-series trend identification. Connects pattern recognition to diagnostic questions about business performance.
Lesson 4 • Data Visualisation Principles
Teaches chart selection, design principles, and visual encoding for accurate communication. Prevents common visualisation errors that mislead decision-makers.
Lesson 5 • Reporting and Analytical Storytelling
Structures analytical findings into coherent narratives for non-technical audiences. Teaches the pyramid principle and executive summary writing for business reports.
Chapter 5HideHide detailsSee detailsPredictive Analytics and Forecasting
Predictive Analytics and Forecasting
Lesson 1 • Classification and Segmentation Methods
Introduces logistic regression, decision trees, and cluster analysis for categorising business entities. Connects segmentation outputs to targeted management decisions.
Lesson 2 • Model Evaluation and Selection
Teaches cross-validation, overfitting detection, and model comparison metrics. Ensures students select the most appropriate model for each business context.
Lesson 3 • Regression Analysis for Prediction
Covers simple and multiple linear regression, model assumptions, and interpretation of outputs. Applies regression to cost estimation and revenue forecasting scenarios.
Lesson 4 • Time-Series Forecasting Methods
Applies exponential smoothing, ARIMA concepts, and decomposition to business time-series data. Produces demand and revenue forecasts with quantified uncertainty ranges.
Chapter 6HideHide detailsSee detailsManagement Accounting Fundamentals
Management Accounting Fundamentals
Lesson 1 • Cost Classification and Behaviour
Distinguishes fixed, variable, semi-variable, and step costs and explains their behaviour across output levels. Establishes cost vocabulary essential for all subsequent accounting topics.
Lesson 2 • Cost-Volume-Profit Analysis
Applies CVP relationships to calculate break-even points, margin of safety, and profit targets. Connects cost behaviour to pricing and volume decisions.
Lesson 3 • Performance Measurement Frameworks
Introduces responsibility accounting, divisional performance metrics, and the balanced scorecard. Aligns financial and non-financial measures to strategic objectives.
Lesson 4 • Budgeting and Variance Analysis
Covers master budget construction, flexible budgeting, and variance calculation for materials, labour, and overhead. Links budget deviations to corrective management actions.
Lesson 5 • Costing Methods and Systems
Compares absorption costing, marginal costing, and activity-based costing for product cost determination. Evaluates the managerial implications of each costing approach.
Chapter 7HideHide detailsSee detailsIntegrating Analytics with Management Accounting
Integrating Analytics with Management Accounting
Lesson 1 • Analytical Budgeting and Forecasting
Replaces static budget assumptions with data-driven forecasts using time-series and regression models. Produces rolling forecasts that adapt to changing business conditions.
Lesson 2 • Working Capital and Cash Flow Analytics
Uses analytical tools to monitor receivables, payables, and stock cycles. Connects operational efficiency metrics to cash flow forecasting.
Lesson 3 • Profitability and Segment Analysis
Applies contribution analysis and customer profitability techniques using transactional data. Identifies high-value and loss-making segments for strategic resource allocation.
Lesson 4 • Integrated Management Reporting
Designs management reports that combine financial results with operational and analytical insights. Applies storytelling principles from Chapter 4 to accounting report design.
Lesson 5 • Data-Driven Cost Analysis
Applies regression and clustering to cost data to identify cost drivers and anomalies. Enhances traditional cost analysis with statistical rigour.
Chapter 8HideHide detailsSee detailsStrategic Decision-Making and Advanced Applications
Strategic Decision-Making and Advanced Applications
Lesson 1 • Capstone Integration Project
Synthesises all course competencies in a comprehensive case study requiring systems analysis, data analytics, and management accounting outputs. Develops professional-grade deliverables for portfolio use.
Lesson 2 • Pricing Strategy and Decision Analysis
Evaluates pricing approaches including cost-plus, target costing, and value-based pricing using analytical data. Applies decision trees and expected value to pricing under uncertainty.
Lesson 3 • Capital Investment Appraisal
Applies net present value, internal rate of return, and payback methods to evaluate long-term investments. Incorporates risk analysis and sensitivity testing into investment decisions.
Lesson 4 • Strategic Performance and Value Creation
Connects management accounting and analytics outputs to long-term value creation and competitive strategy. Evaluates organisational performance using economic value added and strategic scorecards.
Lesson 5 • Transfer Pricing and Divisional Decisions
Analyses transfer pricing methods and their impact on divisional performance and goal congruence. Evaluates make-or-buy and outsourcing decisions using relevant cost analysis.
Your valid completion certificate
This course is for you:
Finance professionals: ready to add data modelling skills to their accounting toolkit.
Business analysts: seeking formal grounding in both systems thinking and financial reporting.
Operations managers: wanting to turn process data into measurable performance outcomes.
Career changers: moving into analytics or accounting from a non-technical background.
Recent graduates: building a competitive, cross-disciplinary skill set for business roles.
Accounting technicians: looking to expand their scope into data-driven planning and analysis.
What our students say
Your lessons are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of interest without needing to change platforms... I'm grateful for everything you do, I've already recommended you to other people...

I like how the lessons are straight to the point and how I can change chapters and skip content I don't need.

I like the content and the way videos are presented and transcribed, which speeds up the process!

The platform is fast and simple to use. The diversity of content and complementary videos really help with learning.

Top upskilling courses
FAQ
Who is Dedika?
Is the certificate valid in Australia?
Are the courses free?
What is the course workload?
What are the courses like?
How do the courses work?
What is the duration of the courses?
What is the cost or price of the courses?
What is an EAD or online course and how does it work?
PDF Course




















