Data Aggregation

Data Aggregation is any process where data is gathered and expressed in a summary form. Data aggregation is often used to enable statistical analysis of large data sets for business intelligence (BI) and analysis.

Data aggregation is often done on a large scale, through software tools known as data aggregators. Data aggregators typically include features for collecting, normalizing (processing), anonymizing, and presenting aggregate data. Data aggregators help business analysts examine large data sets more easily. Data aggregation is presented in ways that removes personal information from the data set (aka: anonymization or de-identification). 

Some examples of data aggregation are: 

• Graduation rates for schools
• Voter turnout by state or county 
• Average age of consumer for a specific product 

We live in the era of big data and data monetization. Understanding the impact of data aggregation and business intelligence can help most businesses improve their profitability, customer satisfaction, support and much more.

Source: TechTarget

Additional Reading: Data Aggregation May Be The Key To Building The Bank Of Google

Related Terms: Data Mining

What does this mean for an SMB?

The use of Data Aggregation (DA) is something most organizations or businesses can benefit from. DA can help in businesses with their finance, business strategy, product planning, product and service pricing, operations optimization, and even marketing strategy. For Business Intelligence (BI) purposes, data can be aggregated into summaries that help leaders make well-informed decisions. User data can be aggregated from multiple sources, such as social media communications, browsing history from IoT devices and other personal data, to give companies critical insights into consumers and their behaviors. If your organization isn’t aggregating data to help make business decisions; maybe it’s time to hire a data analyst or third-party to aggregate important data for your company. 

To learn more about Data Aggregation, watch this short video:

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