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  1. What Is Data Aggregation? (Examples + Tools)

    • Sectors as diverse as healthcare, financial services, and e-commerce all rely on data aggregation for top-level analysis, core analytical functions, and day-to-day tasks. With such broad applications, data ag… See more

    What Is Data Aggregation?

    Data aggregation entails collecting raw data into a centralized source, and summarizing the data for analysis. The term is typically defined from the viewpoint of a technical user. In th… See more

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    Data Aggregation For Business Users

    However, this narrow definition of “data aggregation” typically excludes the kind that occurs every day among business users. SalesOps managers aggregate data all the time. And t… See more

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    Additional tools and solutions can help companies with data aggregation, especially if they maintain many different data sources, and need to analyze large volumes of … See more

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    In a modern enterprise, most team members will leverage aggregated data to solve problems and make decisions. For many business users, the spreadsheet remains th… See more

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  2. Examples of data aggregation include1234:
    1. Time aggregation: Gathering all data points for one resource over a specific period of time.
    2. Spatial aggregation: Collecting all data points for a group of resources over a given time period.
    3. Attribute aggregation: Summarizing data based on specific attributes or categories, such as customer segment, job title, or product category.
    Learn more:

    There are several ways that data is aggregated, but time, spatial, and attribute aggregation are the 3 primary types:

    • Time aggregation refers to gathering all data points for one resource over a specific period of time.
    www.qlik.com/us/data-management/data-aggregation
    • A SaaS company combining last year’s overall revenue, average deal size, and deals per rep to forecast sales
    • A fintech leveraging average date to default, default rate by income, and debt per customer to model risk for loan origination
    coefficient.io/data-aggregation

    The four most common types of data aggregation are:

    • Time aggregation collects all data from a single source during a set period of time.
    • Spatial aggregation retrieves data from multiple data sources during a set period of time.
    segment.com/data-hub/data-aggregation/

    Common types of data aggregation include:

    • Temporal Aggregation: Temporal aggregation involves grouping data based on time intervals, such as hourly, daily, weekly, or monthly periods.
    • Spatial Aggregation: Spatial aggregation groups data based on geographic location or areas.
    www.10xsheets.com/blog/data-aggregation
     
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