UCOVI Stage 4: Visualise


Business Strategy & People Management: ★★★☆☆ Technical Work: ★★★☆☆ Analytical/Scientific: ★★★★☆

Business Strategy & People Management: ★★★☆☆
Technical Work: ★★★☆☆
Analytical/Scientific: ★★★★☆



Discipline Overview

Building and nurturing a suite of reports and dashboards that call out important business KPIs (with appropriate alert statuses when significant deviations from expectation occur), and encourage investigative, self-service drilldown analysis from users.

Reporting the outcomes of investigations with data and analysis projects clearly, including commentary to contextualise numerical findings within any certainty limitations from data quality or sample size.

Handling exploratory analysis differently from confirmatory analysis, so that potential findings and avenues for investigation aren't buried in caveats and statistical jargon, but the significance and confidence of discoveries are accurately reported to those who will base decisions on them.

Remember that sometimes Microsoft Word is your ideal BI tool; sophisticated diagnostic analytics lends itself as much to clear written explanation of the subtle but key messages in the graph rather than the aesthetics and interactivity of the graph itself.

Questions and Considerations

How can we make this report page less cluttered? What level should we conditionally format low data points to show red?

People and Teams to Involve

Business stakeholders, data analysts, in-house design teams.

Discipline Overview

Building engaging reports that combine impartiality and business-relevance in the presentation of data.

Common situations faced

Testing DAX measures, tidying up dimension values on axes, optimising complex, detailed reports for consumption on mobiles.

Technologies to learn and specialisms to hone

Tableau, Qlik, Power BI, Looker. Establishing a report structure around key KPIs as an opening state with the ability for the user to drill down into more detail. Designing reports that anticipate follow-up questions from users. Using outlier detection and average reporting that suits the distribution of the data.



Next Stage: Interpret