Percept Research is thrilled to announce that we have transitioned our report production process to Power BI in 2023 for the Executive MBA Council Membership Program Benchmarking Survey.
This is an important evolution aimed at delivering high-quality reports more efficiently and with superior accuracy. This move will enable our firm to generate reports more swiftly, improving the timeliness of the insights for driving informed decisions for EMBAC members. Power BI's robust data processing capabilities allow us to minimize errors and inconsistencies substantially.
This change does come with adjustments to how the data are displayed. Power BI has certain limitations compared to our previous platform. Consequently, members may notice differences in the way data are presented within the reports. However, we assure you that these changes do not compromise the quality of the information being conveyed.
These are some of the adjustments to the data displayed in these reports with the use of Power BI:
1. Some charts will not display values to one decimal point for several reasons:
Default rounding behavior: By default, Power BI might not display values with decimal points for certain visuals if the system determines that decimals are not significant. For instance, when dealing with large values, the rounding settings may lead to values being displayed as whole numbers.
Aggregations and calculations: Certain aggregations and calculations performed within Power BI can lead to decimal approximations or truncation. This can result in a loss of decimal precision, causing some charts to display values without decimal points.
Data source limitations: In some cases, data sources might return data values without decimal points or with less precision. This can propagate to the visualizations and result in the absence of one decimal point for some charts.
Type of visual: Depending on the visualization used, different rounding logics may be applied, causing the absence of one decimal point for some charts. Some visuals make more sense with whole numbers (e.g., bar charts) while others are more suited for precise decimal values (e.g., line charts).
2. Some bar charts will not display data labels for small values for readability and comparative importance. When dealing with bar charts, especially with many bars or a mix of large and small frequencies, displaying labels for smaller frequency segments can make the chart cluttered and confusing. Power BI automatically avoids putting labels on small bars to maintain clarity. In some cases, small frequencies may carry less importance compared to larger ones in a given context. Omitting labels for small frequencies reduces unnecessary distraction and helps audiences focus on the more significant data.