I'm Sachin Yoganandham
Turning complex metrics into clear stories
Hover a red pulse for details
Live data: USGS, wheretheiss.at, Open-Meteo · borders from Natural Earth · drag to spin
HOW I APPROACH DATA
A metric is only useful if someone can act on it.
My toolkit at a glance
how I work
From raw data to a clear decision
Source
Pull data from the systems the business actually runs on.
Model
Clean, join and shape it into something people can trust.
Visualize
Turn it into dashboards that people actually open.
Decide
Forecast, automate and hand over a clear next step.
data story
How a forecast is built
A worked example on a classic public dataset: separate the trend, find the seasonality, then project forward with an honest uncertainty range. It is the same approach I use when forecasting business metrics.
Monthly airline passengers, 1949–1960: demand grew about 4× in twelve years.
Data: Box, Jenkins & Reinsel, monthly international airline passengers. Trend, seasonality and forecast computed in your browser.
Tech Stack
MySQL
Python
Dynamics 365
Power Automate