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What is data aggregation?
Data aggregation is the process of gathering data and presenting it in a summarized format. The data may be gathered from multiple data sources with the intent of combining these data sources into a summary for data analysis.
What is data aggregation with example?
Data aggregation is a process where raw data is gathered and expressed in the form of a summary for statistical analysis. For example, new data can be aggregated over a given period to provide statistics such as sum, count, average, minimum, maximum.
What is aggregation in OLAP?
An Aggregation object represents the summarization of measure group data at certain granularity of the dimensions. This precalculation of summary data occurs during processing and is the foundation for the rapid response times of OLAP technology.
What is the purpose of data aggregation?
A process in which data is searched, gathered, and presented in a summarized, report-based form, data aggregation helps organizations to achieve specific business objectives or conduct process/human analysis at almost any scale.
How is data aggregation done?
Data aggregation is any process in which data is brought together and conveyed in a summary form. It is typically used prior to the performance of a statistical analysis. You can aggregate your data from one specific campaign, looking at how it performed over time and with particular cohorts.
What is the meaning of OLAP?
online analytical processing
OLAP (for online analytical processing) is software for performing multidimensional analysis at high speeds on large volumes of data from a data warehouse, data mart, or some other unified, centralized data store.
What are the OLAP operations?
There are primary five types of analytical OLAP operations in data warehouse: 1) Roll-up 2) Drill-down 3) Slice 4) Dice and 5) Pivot. Three types of widely used OLAP systems are MOLAP, ROLAP, and Hybrid OLAP.