In the past, data engineers had to manually upload their data into their BI tool every time they wanted to update the data that it had access to. Now, with cloud-based BI solutions, BI tools try to do as much of this work automatically as possible. The idea is that a BI tool can automatically pull data from other software and load it into the BI tool’s storage systems, all without human input.
However, not every piece of business software generates and stores its data in exactly the same way. BI tools can’t use one-size-fits-all solutions to transfer data from one tool to another, since every tool has its own nuance. This means that, for the most part, BI tools have to use separate, unique connections for each other piece of software that it wants to connect with.
What is a data connector?
These connections are called “connectors” or “integrations” and they’re an important part of selecting the right business intelligence solution for your company. The nature and quality of the integrations that your BI tool has with the other software that you use is one of the most important factors that determines how useful that BI tool will be for you.
Not all connectors connect in the same way, and that means not every connector is the same quality. Some connectors are mostly seamless and will cause few, if any problems; other connectors might be more temperamental. In general, the seamlessness of a connector corresponds pretty closely to which of the three main styles of connector it is.
Connectors are classified based on the relationship between the organization that made the connector and each of the two tools that the connector is going to connect. Depending on this relationship, a connector may be an invisible piece of code that works perfectly, or a complex code solution that technical staff are required to maintain and upkeep.
There are three different kinds of connectors:
1. Native connectors (or first-party connectors)
These data connectors integrate two pieces of software that have a common codebase and that are often owned by the same company.
An example of a native connector is the connection between Tableau and Slack. Since both tools are owned by Salesforce, both the Tableau and Slack team can devote resources to building a robust, useful connector with no bugs or issues. There’s no need to do some complex procedure to connect the two apps; they can talk to each other very easily.
Native integrations are usually the most painless integrations, and data tends to flow very easily across them. If there is a problem, either vendor can step in to fix it. However, native integrations are only possible between vendors owned by the same company or vendors that are willing to work that closely, so each tool will only have a very limited amount of native integrations.
2. Built-in connectors
These data connectors are native and built-in to one of the pieces of software, that connects to the API of the other piece of software. They’re built with the involvement of only one of the two vendors, but the vendor that builds it, builds it directly into their tool.
Many BI vendors offer a frankly insane number of built-in connectors. Domo, for example, offers over 1,000 built-in connectors with common software (like Salesforce or Quickbooks). Since BI software relies so heavily on powerful connectors, it makes a lot of sense for BI vendors to devote time and resources towards building these connectors for their customers.
A built-in connector might not always be as seamless as a native connector, but in most cases, they’re very good. A business might use a built-in connector to transfer millions of different data sets over a thousand different sessions, and never once have a problem with it. In addition, if a built-in connector fails, it’s easy enough to start bugging your BI vendor to fix it.
3. Third-party connectors
These are the last type of connector, and they’re the ones that vary most widely in quality. They’re made by third parties, people unrelated to either one of the two pieces of software that you’re trying to connect.
These connectors can range from somewhat uninvolved connectors between two simple tools that both have open APIs, to massively complicated workarounds to connect data between tools that would have no chance of communicating otherwise.
There are some common reasons why a company might be forced to use a third-party connector to transfer data between software. In some cases, it’s just that one of the tools is so obscure that no one’s bothered to build a connector for this tool into their software. Hopefully, in that case, it shouldn’t be too much of an issue to build a connector that can work well enough.
In some cases, though, it’s because a business is trying to connect one of their tools to some piece of legacy software. These tools rarely have any modern connectivity niceties like APIs, so those that want to build connectors with these tools have to find complex workarounds that rarely work as well as they’d hope.
What data connector should I use?
If it were an option, businesses would want all of their connectors to be native connectors. Native connectors are the connectors that work the best, are simplest to implement, and don’t require any sort of technical expertise to figure out.
However, it’s not feasible to expect every tool that you plan to use to connect natively with your BI tool.
Find the easiest tool for the job
For most businesses, built-in integrations are the gold standard and should make up the bulk of, if not all of, the integrations on their software suite. They have many of the same benefits as a fully native integration, like support from a software vendor if something goes wrong. They’re also far more common than native integrations; a BI tool might only have a handful of native integrations but offer hundreds of built-in connectors.
Built-in connectors usually work about as well as a native connector, but work much better than a third-party connector. Businesses mostly can’t decide whether or not they want to use a native integration; either the business has a native integration, or it never will. They can and should, however, decide to use built-in connectors rather than third-party connectors if they have the option.
Find a vendor that has pre-built connectors for your software
Businesses should consider the native integrations available when selecting a BI tool. Most native connectors either connect two popular tools (like Marketo and Salesforce) or they connect a piece of software with some other proprietary tool that no one uses.
Popular tools will have good built-in connectors in basically every BI tool since there are so many users that want to connect to that tool. Usually, native integrations aren’t so much better than built-in connectors that it’s worth picking a whole tool just for it. Same thing with the smaller, proprietary integrations; it’s not worth moving crucial operations over to some under-featured proprietary tool just to access a native integration.
However, built-in integrations should be a major factor that helps a business select its tool. Built-in connectors are so much better than trying to implement a third-party connector that it’s worth looking for BI tools that have them. Plus, built-in connectors are so common in the industry that it’s not unreasonable to expect your BI tool to have built-in connectors for all of the tools on your stack.
Data connectors are a valuable tool for your business. By automating the routine data entry that takes place with business intelligence, data connectors allow your team to focus on what they’re best at: analyzing the data and extracting key insights to help the business. Modern BI tools offer several different types of data connectors that should be considered when considering vendor options. By choosing a vendor that has pre-built connectors for you data sources, you can ensure a fast implementation and effective use of the BI tool.
Check out some related resources:
10 Ways to Turn Data into Actionable Insights
How a private equity firm uses data to expand and enhance its business portfolio
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