PMGT5887 Chap.9 Project Reports, Business Intelligence and Power BI
Project Reports, Business Intelligence and Power BI
Week 8 turns project data into decisions, and this chapter follows the path from raw files to a dashboard. It explains what project reports are for and the four kinds the slides name, status, risk, financial and milestone, what makes a report clear, relevant and actionable, and what each stakeholder wants to read.
It sets out the business intelligence process from a data warehouse fed by extract, transform and load, through text and statistical analysis and the four questions of descriptive, diagnostic, predictive and prescriptive analysis, to reporting, and the lifecycle version of the same flow.
It then introduces Power BI: what it is, its three views, the get, transform, chart and theme sequence, and the goals, visualisations and data that a dashboard is built from. A worked steering-committee dashboard and a budget-against-actual combo chart show how one page can answer the reader's question, and the chapter lists the six families of project data a dashboard can draw on.
A budget chart shows how one visual can answer an executive's first question.
What this chapter covers
- 01
Purpose and types of project reports
- 02
Stakeholders and their reporting needs
- 03
The business intelligence process
- 04
Four kinds of analysis
- 05
Power BI and its three views
- 06
Dashboard building blocks
- 07
Six families of project data
Worked example · free
Reading a budget-against-actual chart for an executive
- +1Monthly differences, actual minus budget: -2, +2, +8, +1, so spending first exceeds budget in the second month.
- +1Cumulative overspend: -2 + 2 + 8 + 1 = $9k after four months, driven mainly by the third month.
- +1Action: ask whether to approve $9k of contingency or to reduce scope, and investigate the third-month spike (diagnostic analysis).
Key terms
- Business Intelligence
- The processes and tools that turn data from many sources into reports and insight for decisions.
- Data Warehouse
- A central repository holding integrated data drawn from various sources.
- ETL
- Extract, transform and load: collecting data, cleaning it and loading it into a warehouse.
- Diagnostic Analysis
- Analysis that asks why something happened, using the data behind a result.
- Power Query Editor
- The Power BI tool used to transform and clean data before it is modelled and charted.
- Slicer
- An on-page filter in Power BI that lets a reader narrow every visual by a category or date.
Project Reports, Business Intelligence and Power BI FAQ
What makes a project report good?
Clear visuals and structure, KPIs and metrics that matter to the reader, and insights that lead to action. A report that records progress but asks for no decision misses its purpose.
What are the three views in Power BI Desktop?
Report, where you build and arrange the visuals; Data, where you inspect the tables you have loaded; and Model, where you define how those tables relate to each other before charting.
Which analysis answers what will happen next?
Predictive analysis forecasts what will happen. Descriptive analysis summarises what already happened, diagnostic analysis explains why it happened, and prescriptive analysis asks how to make a desired result happen.
What data can a project dashboard use?
Task data such as dates and dependencies, financial data such as budget and spend, resource data, risk and issue logs, progress metrics such as percentage complete, and time tracking from timesheets and work logs.
What are the building blocks of a dashboard?
Goals first, such as improving productivity or reducing cost; then the visualisations that show progress toward them; then the data and where it will come from. Starting from the data usually produces a page with no clear message.
Assessment move
Memorise the four analysis questions as a ladder from what happened to how to make it happen, and practise classifying ten manager questions onto it. Sketch one dashboard on paper for an executive and one for a team member using the same data, and note what changes. In Power BI Desktop, import a small spreadsheet, clean one column in Power Query and add a slicer, so that the menu sequence is familiar.
For the discussion task, choose one public Power BI data story and answer the four workshop questions in writing: who it is for, what it shows, what it supports deciding and what you would change. The same four questions make a reliable structure for any short answer about a report.
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