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Analyzing Time-series without the Llama Drama
Summarize and analyze this article with:
Key Take Aways
Time-series analysis gets complicated fast when datasets involve rolling periods, fiscal calendars, rankings, and repeated time-based calculations.
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Savant’s Time Series Rollups automate these transformations, converting raw records into useful summaries such as rolling monthly metrics, quarterly totals, and rankings.
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The article uses a humorous llama-petting dataset to demonstrate the concept, but the underlying problem is very real: analysts repeatedly need the same time-based transformations across business data.
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The payoff is a reusable workflow instead of manually rebuilding calculations each time.
Analyzing Time-series Data
Some argue that time is a flat circle. Most analysts, however, can agree that working with time-series data is tough.
Processing large volumes of transactional records, building rolling period aggregations, and implementing fiscal calendars are tedious. Don’t even get me started on time-zone transformations.
Savant Time Series Rollups
The pain is near and dear to our hearts at Savant, which is why we built a tool to greatly simplify time-series operations.
Let’s say we had a data set that tracks how many llamas each Savant employee pets on a given day.
Now, we’re a bit competitive at Savant, so we want to be able to track who pet the most llamas every quarter, as well as who is improving in their llama petting on a rolling month-to-month basis.
The Savant time series tool easily takes our raw data and creates the roll-ups needed for these calculations.
See how it works in this short video:
With just a few more steps in Savant, I’m able to automate a competition tracker that updates our llama scores on a daily basis:
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