#Sigma computing functions driver

Below, we list six challenges around interactive cloud data analysis systems. In a positive feedback loop, these trends amplify each other’s effects, and we expect them to continue doing so. Another reason for the expanding user base is the second trend above, which makes the data relevant to an even larger number of business users. For instance, a 5-column table with one million rows would quickly push the limits of many spreadsheet applications. An undercurrent to this trend is that spreadsheet applications, which business users have traditionally used, have become inadequate for data analysis as spreadsheets do not facilitate the analysis of live, large-scale, or unstructured data.

This boosts the demand for easy-to-use cloud data analysis systems (often simplified as self-service tools). Third, the number of business users who would like direct access to cloud data is also rapidly growing. Another aspect of this trend is the nature of the new data, which is increasingly semi-structured or unstructured, primarily text, including logs, but also, for example, sensor, audio, imaging, and video data. For example, even a small-size company can have several marketing applications regularly pushing new data into the enterprise’s data warehouse. Second, the size and diversity of data available to enterprises increase faster than ever as a growing number of data sources (typically SaaS applications) feed into enterprises’ data stores.

#Sigma computing functions driver

The decreasing cost of keeping data in the public cloud has been the primary driver of this trend. Three major correlated forces act on enterprise data analysis today.įirst, more and more enterprise data is stored in the cloud. Data analysis is imperative for enterprises to leverage the signals from data to improve their business outcomes.