The importance of data aggregation

What is data aggregation?

Data is all around us. This makes it essential to understand what data aggregation is. Let’s explore the different facets of data aggregation to get a better understanding.

Data aggregation is a type of data and information mining process where data is searched, gathered, and presented in a report-based, summarized format to achieve specific business objectives or processes and/or conduct human analysis. Data aggregation may be performed manually or through specialized software.

Data aggregation is used to get summarized data for analytics. It helps provide statistical analysis for different objectives.

How does data aggregation help?

Aggregation platforms take care of the collection, processing, and sometimes even the presentation of data. It’s an essential part of data integration. Data aggregation helps summarize data from different, disparate and multiple sources. It increases the value of information. 

The best data integration platforms can track the origin of the data and establish an audit trail. You can trace back to where the data was aggregated from. It’s important to understand that aggregate data is not limited to numbers. Data aggregation may be performed manually or through software expressly written for such purpose.

What are the steps in data aggregation?

To accomplish data aggregation, you need a data integration platform that helps in collecting data from multiple sources. The next step is data processing to enrich the data and finally, we arrive at the data aggregation stage. This is where the data is statistically analyzed for the latest insights. We explain the steps involved in the data aggregation process below:

Data Collection

A data integration platform extracts data from different sources and stores it either on the cloud, on-premise, or data warehouse. This data may have originated anywhere. It could have been extracted from sources such as social media, eCommerce platforms or it may be data stored in files when it comes to IoT or sensor data. The advantage of a data integration platform is that it makes it easier and seamless to bring all the information from all the different data silos together.

Data Processing

During the data processing stage, the data that has already been collected is processed for interpretation. This processing is done using a combination of smart machine learning algorithms. The method of processing can vary depending on the source of data being processed. Your data source could be data lakes, social networks, connected devices or any other source. The type of processing can also vary based on the intended use of this data.

This data can also be processed in different forms. It could be in the form of an image, a graph, a table, a vector file, audio, charts or any other format of choice.

Data Presentation

Once your data has been processed, developing and delivering an effective data-driven presentation is crucial. Data analysis tools first analyze and process the raw data, after which the aggregated data is presented in a summarized form.  How the data is presented will vary based on the business.  

Once the data is collected and processed, all the aggregated data can be presented in a summarized form. How it is presented depends highly on the type of business. Data is most commonly presented either in textual, tabular or diagrammatic forms (bar charts, pie charts, line graphs, scatter graphs).

Sophisticated statistical algorithms can be used to analyze the data and derive insights from it. 

What makes data aggregation so useful

Making sense of the avalanche of data isn’t as easy as it may seem in the age of big data. This is where data aggregation can prove helpful. Data aggregation brings together data from multiple sources and summarizes all this data in a uniform manner. Companies that need to gain market intelligence rely on software tools for data aggregation. These tools can be used to perform the following actions:

Data extraction- This involves the targeting or isolation of relevant data from the aggregated data to ensure that it meets the needs of a particular business.

Modification- Modifying or transforming the data in such a way that it corresponds to the prescribed format for data analysis.

Data visualization and analysis– A visual representation of analyzed data and KPIs which can be used for actionable business intelligence.

Once this aggregated data is analyzed, it can be used to create actionable business intelligence or guide you through the decision-making process. You can easily evaluate where your business needs to improve with these metrics.

Consider the case of the restaurant industry. A quick-service restaurant can leverage the data it collects through a data integration platform to benefit from competitor research, price monitoring, market intelligence, average order time and more.

Used this way, data aggregation is a boon for business analytics. The summarized aggregated data can help leaders make well-informed decisions. It is an effective means for companies to gain critical insights into customers. Enterprises can gain deep insights by aggregating data from disconnected, siloed sources such as social media, web analytics or even CRM tools. Businesses can also leverage solutions that offer comprehensive CRM development services such as Microsoft Dynamics CRM Development Solutions.

Advantages of Choosing DataChannel 

• 100+ Data Sources: We support trending and established data sources related to advertising, marketing, CRM, financial, and eCommerce platforms, along with support for ad-hoc files, google sheets, cloud storage, relational databases and ingestion of real-time data using webhooks. If we do not have the integration you need, reach out to our team and we will build it for you for free.
• Powerful scheduling and orchestration: our fully automated platform follows all ETL best practices and deploys granular control over scheduling down to the exact minute.
• Granular control over what data to move: Unlike most tools which are highly opinionated and dictate what data they would move, we allow you the ability to choose down to field level what data you need. If you need to add another dimension or metric down the line, our easy-to-use UI lets you do that in a single click without any breaking changes to your downstream process.
• Reliable pipelines: We offer extensive logging, fault tolerance, and automated recovery, allowing for dependable and reliable ETL pipelines. If we are unable to recover, the extensive notifications will alert you via slack, app, and email for taking appropriate action.
• Built to scale at an affordable cost: Our best in class ETL tool is built to handle billions of rows of data and will scale with your business when you need them to, while allowing you to only pay for what you use today.
• Get Started within Minutes: We offer a self-serve UI, and our onboarding experts are always there to help you through the process. 
• Managed Data Warehouse: While cloud-first data warehouses offer immense flexibility and opportunity, managing them can be a hassle without the right team and resources. If you do not want the trouble of managing them in-house, use our managed warehouse offering and get started today. Whenever you feel you are ready to do it in-house, simply configure your own warehouse and direct pipelines to it.
• Activate your data with Reverse ETL: The unidimensional approach toward data management (movement from apps to warehouses) is evolving constantly. Now you can use DataChannel’s reverse ETL capabilities to send data to the tools your business teams use every day. Set up alerts & notifications on top of your data warehouse and sync customer data across all platforms, converting your data warehouse into a powerful CDP (Customer Data Platform). You can even preview the data without ever leaving the platform.