High Frequency Data

Overview

The explosive growth in the field of IoT, the rapid development of cloud computing and the renewed interest in the use of Artificial Intelligence to process the massive volumes of data being produced by hundreds of thousands of sensors, coupled with the long downturn cycles in the O&G industry, has managed to elevate the value of data to the highest of levels.  Organizations are increasingly turning to data to optimize operations and reduce cost of doing business in the face of vanishing margins.  Automation at various levels of operation is gaining credence as the means of attaining efficiencies.

Glossary of terms

Stationary process

In mathematics and statistics, a stationary process (or a strict/strictly stationary process or strong/strongly stationary process) is a stochastic process whose unconditional joint probability distribution does not change when shifted in time. (Gagniuc, 2017).  In other words, the process exhibits periodicity and repeatability.  These are processes whose statistical characteristics do not change over time.  The data inside a constant sized time window has the same distribution.

Non-stationary process

In contrast to a stationary process defined above, a non-stationary process has a variable variance.  The data representing a non-stationary process, therefore, does not show a tendency of mean reversion.