Time-Series has been the fastest growing database category, rated by DBEngines, for over 2 years; yet, less than 15% of organisations store their time-series data in a time-series database. Do you?
One could, accurately, say that time-series data is as old as the universe; but it wasn’t until the mid-19th century that the first article was published on the concept: A Comparison of the Fluctuations in the Price of Wheat and in the Cotton and Silk Imports into Great Britain by J. H. Poynting (March 1884).
Time-Series data is so natural and common that you actually consume, evaluate, and utilise it everyday; when you’re:
Paying for your morning coffee Sighing at the “Delayed” notice on your commute Ploughing through your email inbox In this talk we will look at the different types of time-series data and how to use that to drive observations, understanding, and automation.
Most data is best understood in the dimension of time, lets see why.