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.
![No alt text provided for this image](https://cdn.prod.website-files.com/62d80a87294cc0d49739df0e/631fd159c242571240407c2f_1653603370026.png)
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:
![No alt text provided for this image](https://cdn.prod.website-files.com/62d80a87294cc0d49739df0e/631fd159a7b0aba701f88771_1653603548853.png)