Data aggregation A Guide for Understanding

Data aggregation A Guide for Understanding
Data aggregation A Guide for Understanding

Data aggregation has become a crucial part of the world. It has brought ease in many complex procedures of the world. Its main purpose is to compile a large amount of information provided from a database and organize it accordingly into a more bite-size and comprehensible form. The best feature of this process is that it is applicable at various scales regardless of the specificity of the industry.

Basic aggregation is done through the information obtained through public records and another government database. This information is then compartmentalized and then sold to various business establishments. However, it is not just limited to businesses. This information is also sold to local or state government agencies.

Data aggregation used in the marketplace

One other purpose data aggregation companies are in high demand is its use in marketing. This information is sold to creditors, employers, insurance companies, franchises, etc. They use this information according to their need to the target an audience that is more likely to respond to their advertisement.

Data aggregation makes conclusions based on its data-enriched findings and uses them to conclude information to derive near-accurate conclusions.

Personalization metrics have become increasingly notorious as accessibility, and its growth can be seen in a wide array of enterprises. However, it is mostly due to its relevance in modern practices. Data aggregation is opening gates for continual betterment in an organization’s operations throughout the globe.

How is data aggregation applicable?

To aggregate data is to simplify your large chunks of information. It can help you with analyzing your data in ways that can provide insight into various resources. It includes getting an average, maximum, or minimum limit, sum, total count, etc. There are two types of aggregation:

  • time aggregation
  • spatial aggregation

Time aggregation is the collection of data points from a singular source for a limited period. On the contrary, spatial aggregation collects data points from a group of resources.

Types of data aggregation

There are four primary types of aggregation of data. Although these are some basic functions, they can prove to be fundamental for simplifying complex data. These functions are mainly uses for to produce a mathematical function.


It adds up all the provided data to produce a total.


It shows the highest value in the data of the given category.


The lowest value of each category can be seen in the provide data.


It counts the number of data given in each section.


It evaluates the mean value of the given data.

Data aggregators

We can do aggregation through various data aggregating tools. These tools collect the data, process it accordingly, and then present it as aggregate data. Following are some data aggregating tools that companies and enterprises have been using over the years to convert a statistical analysis of research data into a summarized form.

Looker by Google

Google’s Looker is a business intelligence platform for embedding analytics and data application. Looker enables you to visualize your enterprise’s data more simply, making more profitable decisions for your company.

Looker’s working

Looker uses a modeling language known as LookML. It allows Looker to process the data and present it in an uncomplicated way to be easy to read for everyone in an organization. LookML also produces ways to see the data patterns, thus creating customized data experiences and applications. Additionally, Looker allows everyone to access the company’s information in a simplified fashion.


Is another data aggregator that draws out information from its numerous sources. Uses this information for its various sales and marketing campaigns. It can be on many levels. some of them are:

  • Advertisement level
  • campaign level
  • Keyword level

Zoho analytics

It is another data analyzing software that creates simplified data visualization and enables its users to view the data from a different perception.

Methods of Data Aggregation

There are four main types of data aggregation processes are use as per their need.

In-network aggregation

It is a data-gathering process that later reroutes the information via a multi-hop network.

Tree-based aggregation

This approach constructs an aggregation tree. The tree’s structure illustrates a minimum spanning tree, where the sink nodes are refer to as its roots. And the leaves are denote as the source notes. Subsequently, the information flow starts from the source notes to the sink nodes.

Cluster-based aggregation

Thi approach assembles large amounts of data from the whole network and divides it into smaller clusters. These clusters have a cluster-head which is present between the cluster members.

Multipath aggregation

The multipath aggregate approach partially aggregates the data that is sent to a single parent note. In terms of the aggregation tree, it is the root node. A node then sends data through various routes in which each node sends out packets of data to as many inputs as possible.

Legal setbacks

Handling vast amounts of data can be a risky business. Therefore numerous law enforcement agencies and multiple financial institutions are apprehensive towards data aggregation. It can potentially cause security threats, liability issues, and even intellectual property infringement.

One way to deal with it is if data aggregation companies and financial institutions find some common ground and settle upon an agreement that empowers the customer. Then, an open financial exchange can be set, which allows the institution to supply the aggregators with opportunities to provide full service to protect their customer’s benefit.

Screen scraping is another way these financial agencies want to protect their customer’s privacy. It lets the customer see all activities taking place with their data on the internet and can even see where their accounts were open throughout the internet.

Master at Data Aggregation

At this level, you’ve seen how tedious marketing dashboards can be, and you are over it. How do you accelerate this process? By automating. Masters at Data Aggregations have an automated funnel set up, so they can see insights from their marketing data in real-time.

Marketing data aggregations tools like improvado is an incredibly helpful data aggregation tool for marketers, because it was designes by marketers, for marketers. The platform lets you gather all campaign data into a single dashboard in real time, combined with the ability to view that data in automated reports and well-designed custom dashboards. Improvado pipe your data from marketing platforms and send that data wherever you want it to go – into a data warehouse, a spreadsheet or straight into your visualization tool.


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