This view is powered by the Historical Skill Trends by Occupation API, as well as three related APIs:
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Trending Skills by Occupation
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Emerging Skills by Occupation
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Declining Skills by Occupation
The chart lets you compare historical trend lines of specific skills that are:
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Frequently mentioned in job ads
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Newly emerging and gaining traction
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Losing prominence over time
What this chart shows
Each line on the chart represents one skill and shows how often it was mentioned in job ads for a selected occupation across a rolling 12-month window.
The y-axis reflects the number of mentions across one million job postings, giving you a normalized view for easier comparison across roles and markets.
The x-axis shows the timeline — usually 12 months — so you can see trends and inflection points.
🔎 Example: If "Data Visualization" is a trending skill for Data Analysts, the chart may show a steady upward line, indicating growing demand over the past year.
Why it matters
This historical chart can help you:
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Validate whether a trend is consistent or just a spike
Is this skill steadily rising, or is it a one-off month? -
Plan learning and recruitment strategies proactively
Catch rising trends early and future-proof your workforce. -
Spot skills that are losing traction
These might indicate areas to de-prioritize in training or org design. -
Compare multiple skills over time
Overlay skills to assess relative growth (coming soon).
How to read the values
When reading the chart, you’ll notice two types of values based on where you’re looking:
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Tooltip (on hover): shows a 1-year rolling average of skill mentions.
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Chart legend: reflects a monthly rolling value — typically representing that individual month's data.
What does “rolling” mean?
A rolling value calculates the average (or count) over a moving time window. As time progresses, the window shifts forward — offering a smoothed, ongoing view.
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A 1-year rolling average means each point shows the average mentions from the 12 months leading up to that month.
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A monthly rolling view shows only that month’s mentions, but may still be smoothed to reduce noise.
Why both are useful
| Metric | What it tells you | Best for |
|---|---|---|
| 1-year rolling avg (tooltip) | Smoothed view of long-term trend | Spotting sustained increases or declines |
| Monthly rolling (chart legend) | Recent spikes or dips — more volatile and sensitive | Reacting to short-term market signals |
By comparing them, you can distinguish between:
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A sudden spike that may be temporary
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A steady upward trend that reflects genuine long-term demand
This combination gives a more complete view of skill dynamics — perfect for informed decision-making across workforce and learning initiatives.