Moving window calculations

Moving-window calculations help you see what’s really happening over time instead of being misled by one noisy day or week. By looking at a fixed slice of recent data (the “window”) and sliding it forward, they smooth bumps, handle seasonality, and keep comparisons fair—this 4 weeks vs the previous 4, not this week vs a random old week.

• A moving calculation shows the smoothed level (like a 13-week average).

• A running total shows how much you’ve accumulated so far.

• The moving % and absolute change tell you whether momentum is up or down and by how much.

These four table-level calculations turn any metric into a clear rolling or cumulative signal—directly in Vizpads, without extra formulas or duplicate Business Views. Pick the option that matches your question, set the window and time order, and Tellius does the rest (even when data has gaps).

You can set up table calculations whenever the chart or table involves a valid date column.

Which calculation should you use?

Moving Calculation (windowed value, e.g., 13-week average) Use when you want to smooth noise and see the level of a metric over a rolling window (e.g., rolling average revenue). Great for baseline trend, seasonality smoothing, KPI dashboards. Avoid when you need directional change (up/down vs last window).

Running Total (cumulative to date) Use when you track progress toward a target over time (e.g., YTD sales, MTD signups). Great for target tracking, quota attainment, fundraising, backlog burn-down. Avoid when comparing equal windows (it keeps growing; not a rate-of-change signal).

Moving Percentage Change (% change current window vs previous) Use when you need a rate-of-change that’s easy to compare across segments with different scales (e.g., +8% in Region A vs +2% in Region B). Great for campaign impact, product adoption velocity, MoM/YoY momentum, anomaly detection. Avoid when previous window can be zero/near-zero (percent can explode—use Absolute Change instead).

Moving Absolute Change (difference current window vs previous) Use when you care about the magnitude of change in original units (e.g., +1,250 orders vs last 4 weeks). Great for staffing and capacity planning, inventory deltas, ticket volume swings, revenue +/- in currency. Avoid when comparing segments with very different scales (percent is more comparable across uneven bases).

Example use cases:

• 13-week moving sum of Revenue and % change vs prior 13 weeks → spot momentum by category and region.

• 3-month moving average of Active Users + MoM % change → detect adoption accelerations or slowdowns.

• 4-week moving average of MTTR + absolute change → trigger staffing/incident reviews on spikes.

• 12-month moving sum of Profit + % change → smooth seasonality and quantify YoY trend.