BUSACT702 · Accounting Information Systems
Data Analytics with Power BI
The final chapter of University of Auckland BUSACT 702 turns accounting data into insight with Microsoft Power BI: the analytics workflow, connecting and modelling data, and building visualisations for decisions. It closes the loop with the earlier chapters — the data model you learned to draw as an ER diagram is what you connect and relate in Power BI — and it complements the AIS by making its data useful while its controls keep that data trustworthy.
What this chapter covers
- 01The analytics workflow: connect -> model (relate tables) -> build measures -> visualise -> share for decisions
- 02Connecting data: importing from the accounting data sources into Power BI
- 03Modelling: relating tables (the ER model from the databases chapter) so measures compute correctly across entities
- 04Visualising for decisions: choosing charts and dashboards that answer a business question, not just decorate
- 05Analytics in the AIS: how data analytics complements the transaction cycles and their controls
- 06Data quality and controls: reliable analytics depends on a sound, controlled data model — garbage in, garbage out
- 07The Power BI tool guides (provided on Canvas) as the practical reference for the data-analytics coursework
Walking a question through the analytics workflow
- +1Connect and model. Import the accounts-payable, supplier and payment tables and relate them (supplier -> invoices -> payments), reusing the ER relationships so a supplier links to its invoices and payments correctly.
- +1Build the measures. Create measures for total payables by supplier and average days-to-pay (payment date minus invoice date), so the dashboard can rank exposure and flag lateness rather than just list rows.
- +1Visualise for the decision. Show a ranked bar chart of exposure by supplier and a visual of days-to-pay against terms, with a filter for overdue items — a layout that answers the two questions directly and supports a decision (e.g. renegotiate or prioritise a supplier).
Key terms
- Analytics workflow
- The end-to-end path from data to decision in Power BI: connect to the data, model (relate tables), build measures, visualise, and share for decisions.
- Data model (in Power BI)
- The related set of tables you build so measures compute correctly across entities — the ER relationships from the databases chapter, realised in the tool.
- Measure
- A calculation defined over the model (for example average days-to-pay or total payables by supplier) that a visual displays and that responds to filters.
- Visualisation
- A chart, table or dashboard chosen to answer a specific business question and support a decision, rather than to decorate a report.
- Data quality
- The accuracy, completeness and consistency of the underlying data; because analytics inherits it, sound controls over the AIS data are a prerequisite for trustworthy analytics.
- Power BI
- Microsoft's data-analytics tool used in the course to connect, model and visualise accounting data; a set of tool guides is provided on Canvas for the coursework.
Data Analytics with Power BI FAQ
What is the Power BI analytics workflow?
Connect to the data, model it by relating the tables, build measures, visualise for the business question, and share for decisions. Following the workflow keeps the analysis structured and reliable.
How does data modelling connect to Power BI?
The ER relationships you learned to read and draw are exactly what you build in Power BI so measures aggregate correctly across entities. A wrong relationship produces a confident but incorrect number.
Why does the course pair analytics with controls?
Because analytics inherits the quality of its data. If the AIS controls don't keep the underlying data accurate and complete, even a well-built dashboard misleads — good analytics presupposes good controls.
Can Sia help me plan a Power BI analysis?
Sia can help you structure the workflow — what to connect, how to relate tables, which measures answer the question, and which visual serves the decision — as a study aid. It does not complete graded coursework for you; confirm the assessment details on Canvas.
Exam move
Practise thinking in the workflow: for any question, decide what to connect, how to relate the tables, which measures answer it, and which visual serves the decision. Do the hands-on Power BI work in the computer-lab tutorials while support is available, using the tool guides on Canvas, and reuse the ER-modelling skills from the databases chapter to get relationships right. Always connect a visual back to the decision it informs, and remember that trustworthy analytics depends on controlled, good-quality data. Confirm the data-analytics assessment format and weight on Canvas.
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