SpotIQ Analyze best practices

Learn the best practices for custom SpotIQ analysis.

The SpotIQ Analyze feature works without you having to do anything but push a button. However, like any other feature, there are things you can do to optimize the feature. This page contains some best practices you can use to make SpotIQ more effective when you use it.

When to invoke SpotIQ Analyze

A good time to run SpotIQ Analyze is right after you upload data. SpotIQ Analyze can very quickly help you find insights in your data.

Start from a Search. Enter a single measure in the bar; one you want to explore, of course! Then, select the More menu more menu icon > SpotIQ analyze. Choosing the single measure focuses SpotIQ.

Customize your analysis to focus or tweak the SpotIQ results. While you are tempted to keep all the columns, eliminating some can also result in a better analysis.

Do your data modeling

Increase SpotIQ’s effectiveness by ensuring you are practicing good data modeling. This is true if you are a user uploading the occasional data file or a data management professional. Modeling data requires that you can:

  1. Select Data to get to the data management listing.

  2. Select a data source you own or can edit.

    This brings up the Columns screen, where you can make your modeling settings.

  3. Modify one or more column settings.

  4. Save your changes.

Make sure you set the INDEX PRIORITY for columns in your data source. Use a value between 8-10 for important columns to improve their search ranking. Use 1-3 for low priority columns. INDEX PRIORITY impacts user-based ranking which helps SpotIQ focus its analysis.

SpotIQ Analyze uses measures for correlations. For trendlines and outliers, if SpotIQ Analyze has a measure, it then drills by attributes in turn.

Image comparing attributes and measures. Attributes are text or dates that you can’t sum. Measures are values that you can do math on with a meaningful result.

You should also set AGGREGATION on your columns. SpotIQ Analyze applies the default aggregations from your data when it pulls measures for analysis.

Situations to avoid

There are some use cases SpotIQ is not yet designed to handle.

  • If your data contains a measure that uses a MOVING_* or GROUP_* formula, SpotIQ may return results that simply aren’t meaningful.

  • When doing a correlation analysis, SpotIQ may not find meaningful data if you have a measure with anything other than SUM.

Set SpotIQ preferences

To set preferences for SpotIQ, click SpotIQ in the top bar, and then select Default preferences. These preferences allow you to control how you receive analysis notifications. They also allow you to exclude nulls or zero value measures from analysis.

The exclusions impact each SpotIQ analysis. It eliminates points with such values during statistical calculations for example, for mean, standard deviation SpotIQ excludes values from any equation and uses only the remaining points.

For more information, refer to SpotIQ preferences.

Prioritizing analyses types

You can prioritize highlighting changes in data over time instead of other changes, such as outliers or anomalies.


When you trigger a SpotIQ analysis on an Answer, you can select alternate data columns. To trigger more time-related insights, pick more date-time columns.


In the advanced tab of the SpotIQ dialog, increase the maximum number of trend and correlation insights, and reduce the number of anomaly insights.

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