Companies now have realized that data is a rich source of information and thus are focusing on using specialized services from Data Aggregation Companies. This is very key for the growth of any enterprise.
However, this data is not normally available and if available, it’s not normally stored in a single and centralized location.
It’s up to the enterprise to look for the data sources it needs to draw insights from and bring it together for analytics, a process known as Data Aggregation.
What is Data Aggregation?
Data Aggregation refers to the process of collecting and presenting data in a summarized format for analytics with an aim of achieving business objectives.
Data Aggregation plays an important role in data warehousing as it helps businesses to make decisions based on huge amounts of data. It gives companies the ability to forecast future trends and it facilitates predictive modeling.
Data should be collected based on the information provided by the user and the needs of the business. In most cases, the data is collected from multiple sources and put in a summary form for analysis.
This is a very crucial step because the accuracy of insights from data analysis is heavily dependent on the amount and the quality of data that has been used.
What is the Data Aggregation Process?
There are many Data Aggregation Tools available in the market. Data Aggregation companies The Data Aggregation process generally takes place in 3 steps, listed below:
- Data Collection: It includes collecting data from different data sources. All the business data exists in multiple Databases in heterogeneous format and needs Data Pipelines to load data to common storage.
- Data Processing: After collecting data, the Data Aggregation companies use Data Aggregation tools to clean and transform data into an analysis-ready form. You can try Hevo for auto-mapping the fields and performing transformations using its drag-and-drop feature without writing a single line of code.
- 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.
8 Best Data Aggregation Companies
Data Aggregation is one of the fastest-growing sectors in the world today. Due to the huge size of data that is generated by companies, a high number of Data Aggregation Companies have been started. However, your enterprise should be keen when looking for a Data Aggregation Company to help it achieve its goals.
Data Aggregation Companies differ based on factors such as coverage, pricing, focus, and developer friendliness. When looking for Data Aggregation Companies as an option for your enterprise, ensure that you put all the above factors into consideration.
The following are the best Data Aggregation Companies:
1) MX
MX has partnered with more than 1,800 financial institutions and 43 top digital banking providers in the U.S and Canada.
The company has made tremendous growth which has seen it move from just Data Aggregation into data visualization, personal finance management, and data analytics.
MX also works with other Data Aggregation Companies to route traffic to 48,000 connections, ensuring constant access to the underlying account data. Some of its public clients are USAA, BBVA Compass, Boeing Employees Credit Union, Ally, National Bank of Canada, and several others.
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2) Finicity
They are connected to up to 15,000 financial institutions in North America, with a 95% coverage of US deposit accounts and the same coverage in wealth management.
The company differentiates itself in credit decisions. It also acts as a credit reporting agency for some of its products.
Finicity has partnered with FICO and Experian and launched a new credit scoring methodology named UltraFICO that will expand credit accessibility for millions of Americans. Some of its public clients are FICO, Experian, Ellie Mae, Freddie Mac, Fannie Mae.
3) Fiserv / CashEdge
Fiserv is a Data Aggregation service provider with tremendous success in the sector.
It acquired CashEdge in 2011, now serving as the cornerstone of Fiserv’s account aggregation offering.
Fiserv has grouped its Data Aggregation tools into three different products serving the financial advisory industry, general audience, and another one to act like a PFM. One of its public clients is FinLocker.
4) Mobius Services
They are one of the best Data Aggregation service providers with an active presence in India, UK, and the USA.
They offer services such as data enrichment, digital marketing, retail content services, research and consulting. They focus on industries like information providers, travel and hospitality, oil and gas, e-commerce and retail, finance, real estate and shipping.
5) Yodlee
Yodlee was founded in 1999 and it’s the father of the Data Aggregation industry. It went public in 2014 and Envestnet acquired it in 2015.
Research has shown that its data coverage is very comprehensive and one of the best in the industry. Yodlee provides many tools and services, which makes it good for the financial sector for the provision of various services.
Yodlee has also introduced an incubator and a launchpad to encourage the uptake of its tools and data by the fintech industry. Some of its public clients are ING, Microsoft, Tandem, Transferwise, Personal Capital, and Experian.
6) 3iDataScraping
3iDataScraping is a Data Aggregation Company located in India and the USA.
They offer their clients with Data Aggregation services, web data extraction, web scraping, data capture, web data mining, and email scraping. They can help you turn your unstructured data into structured data.
3iDataScraping can scrape data from e-commerce websites like Amazon and eBay, online travel sites, and social media platforms like Facebook and LinkedIn.
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7) Plaid and Quovo
This is a Data Aggregation service provider that has brought attention to the market for financial account data.
They have received a lot of attention from the media and a lot of capital. It prides itself on being the most developer-friendly data aggregator, and it promotes its APIs and coolness factor to banks and other firms in the fintech industry.
It upgraded its Auth product in February 2019, and it now claims to be covering every financial institution in America. In 2019, Plaid acquired Quovo, a key player in the Data Aggregation sector. Some of its public clients are Venmo, Transferwise, MoneyLion, Upstart, Acorns, Robinhood, and Betterment.
8) Akoya
Fidelity and 11 major U.S. banks own and operate Akoya. It intends to serve as an intermediary between providers and recipients of data through its Access Network.
It focuses on financial data security through its data access network, which is API-connected. It can help you in budget planning, payment processing, investment management, and loan applications.
Manual vs Automated Data Aggregation
Let’s examine the difference between manual and automated Data Aggregation methods companies practice.
1) Manual Data Aggregation
Companies in their initial years usually use manual Data Aggregation because of lesser data volume and fewer business activities. They export data into spreadsheets and manually transform it to match other data sources.
Users often manually match data columns by columns and row by row, which is a very time-consuming and error-prone task. Even a minor mistake can cause a significant change in the outcome.
Organizations that use manual Data Aggregation carry risk, a wrong practice when dealing with data. With this, it becomes more complex to identify patterns in data with the naked eye.
2) Automated Data Aggregation
Automated Data Aggregation process uses Data Aggregation Tools that simplify all the hustle for you. Companies use open-source Data Aggregation tools and 3rd party Data Aggregation Tools depending on the business requirements and budget. These automated Data Aggregation Tools pull data from data sources without writing a single line of code.
Limitations of these 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 for some time for your data to be ready for analysis. 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 the privacy of your company, 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.
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Conclusion
In this article, you learnt about Data Aggregation and why you need it for your enterprise. You also read about the best Data Aggregation Companies in the world. By implementing a Data Aggregation tool to cater to your business needs, you can save time and resources.
Discover top data analytics companies and learn how they can drive your business strategy with advanced data analysis.
If you will set up an effective Data aggregation solution, then Hevo Data is the right choice for you! Hevo will help you simplify the Data Aggregation, ETL, and Data Management process of both the Data sources and the Data Destinations.
FAQs
What is a data aggregation company?
A data aggregation company collects, organizes, and compiles 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.