Descriptive analysis is the analysis of historical data to determine what is, what has changed, and what patterns can be identified.
Considered the most basic type of analysis, descriptive analysis involves breaking down big data into small pieces of usable information, so that companies can understand what is happening in a given business, process or set of operations. Descriptive analytics can provide insight into current customer behaviors and business trends to support decisions about resource allocations, process improvements, and overall performance management. Most industry observers believe that descriptive analysis represents a large part of the logical analysis used by companies today.
Cluster analysis or clustering is a statistical classification technique or activity that involves grouping a set of objects or data in such a way that those contained in the same group (cluster) are similar to each other but different from those in the other group.
Data management is the implementation of policies and procedures that enable organizations to have control over business-critical data.
The data lake is where long-term data containers gather that capture, clean, and explore any raw data format at scale. Data subsets are powered by low-cost technologies that many downstream possibilities can benefit from, including data warehouses, and recommendation engines.
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