Dashboards & Reports

Dashboards, reports and other visualizations:

• Standard reports:

  Standard reports are often used to provide information to a large group of users. Characteristic of standard reports is that the creation of the reports is often done by the role of an "editor" who controls or creates both the data and the presentation of the data on the report. This can ensure high data quality and consistency, not always without losing agility. The goal is to provide curated information, often in a fixed format (PDF, Excel) or using filters and controllable by the user.

• Dashboards:

  The modern alternative: instead of actively distributing (rigid) information, it is presented to a larger group of users in a modern web interface. Interactions with the data are possible within predefined limits, either by a developer/editor or by the tool used. Dashboards are often visually appealing, but sometimes have weaknesses in printing. The big advantage is that the combination of a modern, interactive interface and a suitable data model can cover many more information requests than many standard reports.

• Ad-Hoc Reports/Analyses:

  While reports and dashboards satisfy the basic need for information distribution in the company, special, specific evaluations are initially left out. Ad-hoc reports or analyses close the gap. Targeted analyses are created that examine specific business processes and lay the foundation for new decisions. Flexibility and agility characterize the requirements for this type of information provision. Depending on the preparation of the data, the analysis can be created by a trained business user using simple tools, or the data must first be prepared and the methodology and visualization determined. These activities can be performed by well-trained data analysts or – if very complicated – by a team of data engineers and data analysts (sometimes also data scientists).

• "Visual Analytics", "Exploration":

  This is a special case or an extension of ad-hoc analyses. Special tools support the analyst in his or her work by independently searching the data stock for anomalies, deviations or, for example, correlations. In this way, correlations in the data may be detected that would otherwise have remained hidden.

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Marc Bastien

Software Architect TIMETOACT Software & Consulting GmbH

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