In a world overflowing with data, businesses face the challenge of turning scattered information into meaningful insights. That’s where data aggregation companies come into play. These companies simplify the process by collecting, consolidating, and organizing data from various sources into a single, usable format.
From improving decision-making to driving business growth, aggregation is at the heart of modern enterprises. In this blog, look at some of the best companies and data aggregation tools, showcasing how they help businesses discover the true potential of their data. Ready to find the perfect partner for your data needs? Let’s get started!
What is Data Aggregation?
Data aggregation refers to the process of collecting and presenting data in a summarized format for analytics to achieve business objectives. The process generally takes place in 3 steps, listed below:
- Data Collection: This includes collecting data from different data sources. All the business data exists in multiple Databases in heterogeneous formats and needs Data Pipelines to load data to common storage.
- Data Processing: After collecting data, the data aggregation companies use tools to clean and transform data into an analysis-ready form.
- Data Visualization: Once the data is ready for analysis, reporting tools can use this data to generate immersive reports. Moreover, users can use this data to visualize it and generate actionable insights.
Data aggregation plays an important role in data warehousing as it helps businesses make decisions based on huge amounts of data. It gives companies the ability to forecast future trends, and it facilitates predictive modeling.
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What is a Data Aggregator?
A data aggregator is a firm or service that collects data from several sources, processes it, and aggregates the information into one single dataset that is easier to access and analyze for businesses, researchers, or individuals from multiple places in a single format; essentially, they “aggregate” data by collecting it from various sources and placing it together in a usable form.
Examples of data aggregators
- Data aggregators for finance data: Platforms that gather financial information from multiple bank accounts to give an all-in-one view of a user’s finances in one application.
- Business listing aggregators: Companies gather business information from multiple online directories and present them uniformly to increase online visibility.
- Market research data aggregators: Firms aggregating market research data from multiple sources to offer businesses comprehensive insights.
10 Best Data Aggregation Companies And Tools
Data aggregation is one of the fastest-growing sectors in the world today. Due to the huge amount of data that companies generate, many data aggregation companies have started. These companies differ based on coverage, pricing, focus, and developer friendliness. When looking for data aggregation companies, consider all the above factors. The following are the best data aggregation companies and data aggregation tools:
1) Hevo Data
Hevo is a no-code platform for real-time data integration and data aggregation tools. It supports 150+ data sources, enabling businesses to aggregate data into destinations like data warehouses easily.
Key Features
- No-code data pipeline setup.
- Real-time data replication.
- Support for schema evolution.
- Advanced observability for troubleshooting.
Pros
- With Hevo, you get a world-class fault-tolerant architecture that scales with zero data loss and low latency.
- Bring real-time visibility into your ELT with alerts and activity logs
- Hevo automatically maps the source schema to the destination warehouse so that you don’t have to deal with schema errors.
- Discover peace with round-the-clock live chat within the platform.
2) Talend
Talend is a powerful data integration and aggregation tool that combines big data processing with data quality.
Key Features
- Pre-built connectors for databases, applications, and APIs.
- Support for ETL (Extract, Transform, Load) and ELT workflows.
- Data profiling and cleansing tools for improved data quality.
| Pros | Cons |
| Comprehensive real-time monitoring capabilities. | Requires technical expertise for complex tasks. |
| The open-source version allows flexibility. | It can be resource-intensive for large datasets. |
| The enterprise version supports advanced workflows. | UI can feel outdated compared to competitors. |
3) Alteryx
Alteryx is known for self-service data analytics and automation, making it ideal for aggregating data for business intelligence.
Key Features
- Pre-configured connectors to simplify data aggregation.
- Predictive analytics tools integrated into workflows.
- Collaboration tools for teams working on shared data projects.
| Pros | Cons |
| Simple drag-and-drop interface for beginners. | High licensing costs for small teams. |
| Rich library of pre-built workflows. | Limited real-time data processing capabilities. |
| Seamless integration with popular BI tools. | Advanced features require additional training. |
4) Informatica
Informatica offers end-to-end data management and aggregation solutions tailored for enterprises.
Key Features
- AI-driven metadata analysis for smarter data handling.
- Cloud-native architecture with hybrid deployment options.
- Data governance and compliance support for regulatory needs.
| Pros | Cons |
| Scalable to handle large enterprise workloads. | Expensive for small businesses. |
| Strong support for regulatory compliance. | Complex implementation process. |
| Excellent for cloud and hybrid data management. | The interface can feel overwhelming for beginners. |
5) Supermetrics
Supermetrics aggregates marketing and advertising data from platforms like Google Ads, Facebook, and LinkedIn into data warehouses or BI tools.
Key Features
- Pre-built connectors for marketing and advertising platforms.
- Automated data pipelines for scheduled refreshes.
- Compatible with Google Sheets, Excel, and data warehouses.
| Pros | Cons |
| Easy to use for marketers without technical skills. | Limited to marketing-related data sources. |
| Customizable and reporting-ready data outputs. | It is not ideal for aggregating data from non-marketing platforms. |
| Reliable data refresh options to keep reports updated. | Higher costs for advanced plans. |
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6) MX
Key Features
- MX has partnerships with 1,800+ financial institutions and 43 top digital banking providers in the U.S. and Canada.
- Offers data aggregation, visualization, personal finance management, and analytics.
- Routes traffic to 48,000 connections, ensuring stable access to financial data.
- Works with multiple data aggregation companies to enhance data coverage.
| Pros | Cons |
| Strong partnerships with leading financial institutions | Limited presence outside North America |
| Comprehensive financial data visualization tools | Data privacy concerns due to extensive aggregation |
| Reliable and stable data connectivity | Competitive market with similar service providers |
7) Finicity
Key Features
- Finicity has connected 15,000 financial institutions in North America.
- 95% coverage of US deposit accounts and wealth management.
- Focuses on credit decisions and financial data aggregation.
- Acts as a credit reporting agency for specific products.
- Partnered with FICO and Experian to develop UltraFICO for better credit accessibility.
| Pros | Cons |
| High coverage of financial institutions in North America | Limited global presence |
| Strong focus on credit decisions and financial inclusion | Dependency on partnerships for credit scoring tools |
| Collaborations with FICO and Experian strengthen credibility | Primarily useful for credit-related use cases |
8) Fiserv / CashEdge
Key Features
- Fiserv acquired CashEdge in 2011 to enhance data aggregation capabilities.
- Provides data aggregation solutions tailored for financial advisors and general audiences.
- Offers personal financial management (PFM) solutions.
- Powers account aggregation services for financial institutions.
| Pros | Cons |
| Well-established brand with strong industry experience | Limited to financial advisory and PFM use cases |
| Reliable data aggregation infrastructure | High costs for premium services |
| Trusted by major financial institutions | Acquisition history may impact service continuity |
9) Mobius Services
Key Features
- Mobius specializes in data enrichment, digital marketing, research, and consulting.
- Active presence in India, the UK, and the USA.
- Focuses on industries like finance, retail, travel, oil and gas, and real estate.
- Provides customized data aggregation and analysis services.
| Pros | Cons |
| Strong expertise in data enrichment and consulting | Less recognized brand compared to bigger players |
| Serves multiple industries beyond finance | Limited public client list |
| Global presence in key markets | May not offer as many automation features as competitors |
10) Yodlee
Key Features
- Yodlee was founded in 1999 as one of the pioneers in data aggregation.
- Acquired by Envestnet in 2015.
- Extensive financial data coverage across institutions.
- Offers an incubator and launchpad for fintech innovation.
- Supports various financial services like lending, wealth management, and personal finance.
| Pros | Cons |
| Established brand with decades of experience | Regulatory scrutiny over data privacy policies |
| Comprehensive data aggregation coverage | Some fintech startups prefer newer alternatives |
| Wide range of financial tools and services | This may involve higher costs for premium services |
Examples of Data Aggregation
- Analyzing User Behavior: Websites aggregate data like page visits, time spent on pages, and clicked links to understand user navigation patterns. This helps identify popular content and areas needing improvement, enhancing user experience.
- Tracking Sales Performance: E-commerce sites use aggregated data on product views, add-to-cart actions, and purchases to monitor sales trends, identify bestsellers, and optimize inventory strategies.
- Improving Marketing Campaigns: Aggregated data from website traffic, email clicks, and ad interactions helps businesses evaluate campaign performance and refine strategies to target their audience effectively.
- Monitoring Website Performance: Data on server uptime, page load times, and error rates can be aggregated to ensure smooth site operation and improve technical performance.
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Limitations of Data Aggregation Companies
Although the above companies will help you aggregate the data that your enterprise wants, you will experience the following challenges:
- You will have to wait sometime for your data to be analyzed. This may delay the data analysis and decision-making process for your enterprise.
- You’ll give third-party access to your data. This may violate your company’s privacy, especially when dealing with sensitive data.
- They don’t offer tools for collecting and aggregating data in real-time, which means your enterprise may lack up-to-date data for analysis and decision-making.
For a comprehensive look at effective data consolidation, explore the key techniques and challenges businesses face.
Conclusion
In this article, you explored the concept of data aggregation and its importance for enterprises. You also discovered some of the leading companies offering data aggregation solutions along with the best data aggregation tools. Implementing the right tools can help streamline your business processes, saving time and resources.
If you’re looking for an efficient solution to manage your data needs, Hevo Data is a great option. It simplifies the processes of data collection, transformation, and integration, making it easier to connect multiple data sources and destinations seamlessly. Sign up for a 14-day free trial and make your data transfer easy! Also, check out our unbeatable pricing for the best plan that fits your needs.
FAQs
What are data aggregation companies?
Data aggregation companies collect, organize, and compile data from multiple sources into a unified format. These companies provide aggregated data to businesses for analysis, marketing, or decision-making purposes.
What is an example of an aggregation business?
An example of an aggregation business is Yelp, which collects user-generated reviews and business information from various local businesses.
What are the risks of data aggregation?
The risks of data aggregation include data privacy breaches, inaccurate data collection, unauthorized access, and potential misuse of sensitive information.
Nicholas Samuel is a technical writing specialist with a passion for data, having more than 14+ years of experience in the field. With his skills in data analysis, data visualization, and business intelligence, he has delivered over 200 blogs. In his early years as a systems software developer at Airtel Kenya, he developed applications, using Java, Android platform, and web applications with PHP. He also performed Oracle database backups, recovery operations, and performance tuning. Nicholas was also involved in projects that demanded in-depth knowledge of Unix system administration, specifically with HP-UX servers. Through his writing, he intends to share the hands-on experience he gained to make the lives of data practitioners better.