Why Work With a Financial Data Provider?

What should a good financial data partner offer?

Here is a list of functions that a good financial data partner will take care of for you:

  • Sourcing
  • ETL
  • Validation
  • Data standardization and cleaning
  • Continuous updates
  • Ongoing data quality
  • Storage, compute & networking
  • Entitlements
  • Permissioning
  • Exchange relations & agreements
  • Documentation
  • Dev tools
  • Product Enhancements
  • Support

What is the ETL process?

Next up is the ETL process. This stands for extract, transform, and load. This is the technical term for the data integration process. You definitely need an experienced engineer for this, since it involves connecting to the source and getting the data loaded into a database. It’s not wildly complex, from an engineering perspective, but it does take time, talent, and resources.

Understanding the validation process

After the data is loaded into a database, there are multiple ways that it needs to be validated.

What is the standardization and cleaning process?

Validation is just one piece to the puzzle after getting your hands on the data. Standardization is the next step. This is especially important for complex historical datasets like fundamental data, but it applies to all datasets.

Continuous updates are a must

Sourcing, storing, validation, standardizing and cleaning data is great, but that needs to happen constantly. The data needs to be updated on a continuous basis. Again, this can be automated in many cases, but does require engineering work, money, and time. If something breaks in the integration, you sure as hell want to know that an engineer or a process will make sure the file comes through.

Understanding storage, compute, and networking

Keep in mind that the work required in every step we’ve gone through so far is required for every type of data you are consuming. Which can be dozens if not hundreds of data feeds. All of that data is going to need to be stored, which costs money. I’m talking about terabytes of cloud storage. Not cheap. In addition, the CPUs required for sourcing, ETL, validation, standardization, continuous updates, and data quality are nothing to balk at.

Digging deeper into the process

Ok, now that we’re through the backend engineering parts of the journey, let’s talk about following the rules. Just getting your hands on the right data, in the right format, isn’t enough to keep you from lawsuits or worse. Financial data can be a heavily regulated space and if you aren’t an expert in navigating it, you will need help.

Gain access to best developer tools and documentation

Still not convinced that it’s worth working with a data partner to handle all of this? Let’s talk about developer tools.

Product enhancements and support that make a difference

Another critical process happening behind the scenes at a data company is the continuous enhancement of data products. New product features roll out from time to time that can be valuable additions to your investment models or provide new insights to your users. Without a team consistently focused on improving data feeds, your app, platform, or algo can run stale.

Where can I find a great financial data provider?

Would you design your own project management software or rebuild quickbooks to keep your business going? When you take a trip, you don’t build an airplane, you buy a ticket. The same goes for data. If your business needs data, buy it, don’t build it. Let’s divide and conquer so you can keep innovating and building the future of finance. Intrinio is an excellent data provider that specializes in custom data solutions. If you are in need of a data partner to help with all of this, please reach out to one of our data experts today!



Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store


High-quality financial data. Tools built for developers. First-class, US-based support. Data doesn’t have to be hard or expensive.