SiSense Style Guide

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On this page

• Overall Look and Feel
  • KPI Charts
  • Filterable Reports
  • Choosing the Right Chart
• Colors, Labels, and Data Values
  • Standard Color Pallete
  • Rounding
  • Currency
  • Data and Time
  • Recorded and Calculated Data
    • Presentation
• Custom Python Modules

Overall Look and Feel

KPI Charts

under construction

Filterable Reports

under construction

Choosing the Right Chart

under construction

Colors, Labels, and Data Values

Standard Color Pallete

SiSense charts use the standard GitLab color pallete.

Rounding

To round or not to round? Know your audience. Present numbers suitable for your target audience and analysis use cases.

• Executive-level charts do not normally require multiple digits of precision and rounding to the nearest ten, hundred, or thousand is sufficient.
• Depending on the chart, 1 or 2 significant digits on percentages may be required for totals to equal 100%.
• In general except for currency, numbers should be displayed in their full form.

Currency

• All currency is presented in USD.
• At $10,000 and above, each 000 is replaced with a k; example $10k instead of $10,000.
• At $1,000,000 and above, each 000,000 is replaced with a m; example $10m instead of $10,000,000.

Data and Time

Fiscal Dates should be extracted from the DIM_DATE dimension table.

Date formats must adhere to the GitLab Writing Style Guidelines:

• Dates are yyyy-mm-dd
• Time is presented as a 24 hour clock using UTC
• Fiscal Quarter is Qn, example Q1
• Fiscal Year is FYyy, example FY21
• Fiscal Year and Quarter is FYyy-Qn, example FY21-Q2

Recorded and Calculated Data

Data is prepared for presentation, or reporting, for a specific target audience and use case. Recorded Data is the basis for all Calculated Data.

• Recorded Data - "Factual" data which originates from a verifiable source and observable events. To aid in verification, recorded data commonly includes audit metadata such as the name of data creator/source, the date and time of data capture, and the location where the event occurred.
• Estimated Data - calculated data based on Recorded data plus an Estimation Factor. The Estimation Factor is typically based on historical data trends over a meaningful and relevant period of time. Estimation is widely used across all industries and domains.
• Forecasted Data - calculated data based on historical Recorded data plus assessments based on "most-likely" future scenarios. Forecasting is commonly used in Financial Planning.
• Predicted Data - calculated data based on historical Recorded data plus assessments based on "what-if" future scenarios.

Presentation

Recorded data does not require special labeling, but Calculated data does. Calculated data should always be:

• clearly labeled, such as in the chart title and legend (E.g. use "Estimated Seats" instead of "Seats")
• clearly identified in the chart elements (E.g. use different line styles when mixing Calculation types on the same chart)

Custom Python Modules

Python modules help with maintaining reusable, quality and clean code in a single place.

To start / modify a custom python module start a MR in the periscope/master branch of the Sisense project. You can see the available custom modules in Sisense at any point at the left side menu of the Create Chart page.

Official documentation on Custom Modules can be found HERE.