What is Data Aggregation? A Guide for CFOs

Balancing and understanding a massive influx of data and reports can feel like too much to handle. But, as a financial leader, you know that using such insightful information is paramount for proper decision making. To alleviate the burden of having too much information without knowing what it means, you can rely on data aggregation and automation tools for assistance. 

Data aggregation and automation tools provide you with easy to read reports at your fingertips. Here, we will take a look at the different types of data aggregation that exist, as well as how automation tools can help. 

What is Data Aggregation?

Data aggregation is the process of pulling together information to provide meaningful insights. It is often done before statistical analysis is performed. To accomplish data aggregation, data is searched, gathered and then presented in reports. 

As a subset of business intelligence solutions, data aggregation serves all industries. When it comes to financial data aggregation, it allows for a snapshot of all accounts and transactions in one centralised location. This easy to read information is used for better and more desirable decision-making. 

For example, in the financial industry, data aggregation offers immense benefits to both the business and the banker. It allows clients to see all their accounts in one view. It enables the financial institution to see a full picture of all its business dealings and complete, timely reports more efficiently. 

Choosing the Right Tool for the Job 

When do you know if it’s the right time to incorporate data aggregation into your business process? Well, for starters, if you are looking to achieve efficiency, decrease costs and increase employee satisfaction, then now is a good time. Data aggregation tools are useful for a business of any size and can undoubtedly provide many benefits. 

However, the bigger question is, how do you choose the right tool?

To incorporate data aggregation successfully within your business, you’ll want to opt for a solution that meets the following criteria:

• An Enterprise-Grade Solution: the solution should be designed for scalability and ease of use. For the last part, it should contain the option to link existing systems through APIs. 
  

• Flexible Setup: The design of the system should be able to adjust according to business needs and consumer demands. 
  

• Quick to Market: The solution should be up and running without much hassle. If the system takes too long to get up and running, is too difficult for employees to use, or requires a lot of technical support from a dedicated team, then it may not be worth it. 
  

• Cost/Benefit: The price and value of the solution must meet your current needs and resource allocation. 
  

• Steady Performance: Searches should feel instantaneous, thereby providing you with the information you need when you need it. 
  

These are just a few of the main components to check for when looking for the right automated aggregation tool. SolveXia provides all of these, along with a supportive team that is always there to help. 

Type of Data Aggregation

There are two main ways to categorise data aggregation, namely:

• Time aggregation: This represents all data points for a single resource over a defined period. 
  

• Spatial aggregation: This represents all data points for a group of resources over a defined period. 
  

Time Intervals for Data Collection

To collect data within the period, there are different ways to view the reports (or data aggregation). These include organisation by:

• Reporting period: A reporting period defines the period in which data was collected for reporting. For example, this is typically determined by daily, weekly, monthly, quarterly or yearly intervals. 
  

• Granularity: This refers to the period in which data is collected for aggregation. To exemplify, say you want to take the average sales within 30 days, then the granularity is 30 days. This is an element of spatial aggregation. 
  

• Polling period: The polling period is how often resources are sampled to pull data. So, say you are pulling data points every 30 minutes. Then, the polling period is 30 minutes. This is also an element of spatial aggregation. 
  

Manual Data Aggregation Vs. Automated Data Aggregation

As mentioned above, it’s always the right time to incorporate automated data aggregation in your business. Both manual and automatic aggregation include the following steps: 

• Review and standardise

• Map, merge and split data

• Fill in holes

• Implement added attributes

• Monitor and adjust

• Change file type
  

But, the differences between automated and manual aggregation come to life in the results. Performing data aggregation manually can result in an immense amount of human error and data entry mistakes. It also means that data is not centralised and can be easily missed. It may also lack proper security and create bottlenecks for teams. With manual aggregation, you risk the following:

• Inability to scale

• Slow time to market

• Reliance on internal teams 
  

Automated Aggregation 

When you select an automated data solution like SolveXia, you can count on a solution that is: 

• Reliable 

• Scalable

• Secure 

• Easy-to-use 

• Quick to market 
  

Benefits of Data Aggregation & Analytics 

As CFOs and financial teams lean more into serving as analysts and decision-makers, they need insights to back up their choices. Data aggregation provides organisations with necessary insights to better position businesses for success. Data aggregation gives you:

• Real-time data: Information is presented as it is happening. Real-time insights show where your company is at the current moment, and it also helps to highlight any errors for quick correction. 
  

• Virtualisation: Data aggregation tools like SolveXia give you a look at the current financial standing of your business in an easy-to-read dashboard. This dashboard is accessible around the clock and is easy to share with relevant internal and external stakeholders. 
  

• Gather Meaning and Insights: Having data without a way to use it for insights would be as useless as having a radio with no sound. Moving data aggregation into the next step of statistical analysis paves the way for a business leader to know what processes are working and what may need correction. It also provides access to information that will help scale and grow to provide your business with a competitive advantage. 
  

Data Aggregation at Work: Examples by Industry 

Interested in learning more about how data aggregation can work for your business? Let’s take a quick look at some examples outlined by industry.

• Finance: The financial industry is dependent on current trends in the market. Data aggregation can pull headlines and customer data for an easy to read an overview of what’s currently happening in the market and within your business. 
  

• Retail: When it comes to retail, competition is fierce. One way to stay ahead of the pack is to monitor pricing carefully. With data aggregation, retailers can track their competitions’ sales and promotions. 
  

• Travel: It pays to know where your customer wants to go when you work in the travel industry. With data aggregation, hotels and airline carriers can see where demand is high and adjust their marketing campaigns based on where people are looking to go. 
  

The Bottom Line 

No matter the current size or state of your business, data aggregation will provide you with unparalleled benefits. As companies continue to rely on data for informed decision-making, data aggregation is one of the first steps in pulling all the pieces together for insights and reporting. 

Automation tools like SolveXia make data aggregation seamless, secure and accessible to all those who need to view reports and dashboards.