Reporting, Analytics, and Data Governance
From data to decisions
Reporting turns operational records into insight. Candidates must understand the main report families: utilization and capacity, project profitability and margin, backlog and pipeline, billing and unbilled aging, expense compliance, and revenue versus billing variance. Understand key metrics and how they are computed: margin percentage, realization rate (billed ÷ standard value), effective rate (revenue ÷ hours), backlog (contracted but undelivered value), and burn rate against budget.
Data governance fundamentals
Governance ensures the numbers are trustworthy. Know the concepts: master data (clients, projects, resources, rate cards), data ownership, validation rules, duplicate prevention, and audit trails. Understand the difference between a transactional record and a reporting snapshot, and why changing a rate card today should not silently rewrite last quarter's report. Understand security roles and row-level access so that project managers see their projects and finance sees the portfolio.
Traps
Frequent errors: comparing reports built on different date bases (transaction date versus accounting date versus project date); assuming a dashboard refresh is real time; treating a change to master data as a historical restatement; and confusing backlog with pipeline (backlog is sold, pipeline is not). Also watch for questions where the right answer is that a metric definition must be standardized before comparison.
Rule of thumb
Before trusting any comparison, confirm four things: same date basis, same currency, same metric definition, and same population filter. If any differs, the variance is likely definitional, not operational.