One of the most difficult parts of any business’s BI strategy is connecting all of their data sources. A business intelligence tool can be an extremely powerful solution for data analytics and visualizations, but it can only provide that power if it can access all of a business’s data.
BI tools need to connect to the tools that your business uses to collect and generate data. Otherwise, there’s no way that you can use that data to drive decisions or find insight.
The technology of data connections has changed a lot in the past few years, but many businesses haven’t changed their data connection strategy since they first implemented their software stack.
Using outdated or obsolete data connection strategies makes your job much harder than it needs to be. By upgrading your data connection solutions, you can make data access easier, simplify your data pipeline, and access up-to-date analytics from anywhere.
To modernize your data connections, you need to understand the basics of data integration, what you need to change, and why a modern data connection strategy can benefit your business.
The basics of data connections
For years, businesses that wanted to transfer data between their business tools had to do that data manually. For example, they might have to download their data as a CSV, save that data to a physical, on-premise database, and then upload that data to their data analytics tool.
For many businesses, that’s still the process that they use. That doesn’t have to be the case, though. Now, there are data connection solutions that can completely automate the data connection process.
Data integrations are code solutions to the data connection problem. They act as a bridge between your BI tool and your data sources, allowing for automatic data transfer.
These code connections are much easier to manage than manual data updates; they can update data automatically, without any human input. Once someone has set up the initial integration, then ideally, no more human input should ever be necessary.
However, businesses that want to use data integrations to connect their data sources usually have to find their own solutions. Data sources rarely have in-built data integration functionality, so businesses need to find their own data integration to transfer the data.
When businesses start to look for data integrations, they have three main solutions. These solutions and their availability will drastically affect how easily they’ll be able to connect with their data.
Native integrations, or first-party integrations, exist between tools built on the same architecture and usually sold by the same vendor. Since the tools use the same formats to store their data, they can communicate their data natively.
These sorts of integrations are usually the easiest to set up and the least error-prone, but they’re very rare. For these sorts of integrations to be useful, you need to be using two or more tools built by the same vendor. With most BI tools, that’s just not something that’s going to happen that often.
If your system offers a native integration or two, that’s great; just don’t expect to rely on native integrations for most of your data sources.
The main types of data integration that most businesses actually use are called pre-built, in-built, or second-party integrations. These are integrations built by someone, like a BI vendor or data integration consultant, that connect a BI tool to a data source.
These integrations are like native integrations in that they don’t require much code input to work. However, it may take more work to connect them. You may need to enter credentials or access an API key to connect the two tools.
The major advantage of these integrations is that they’re common. Market-leading BI vendors aim to provide pre-built integrations with the most popular business tools and data sources, regardless of their type.
If you can’t find a pre-built integration that’ll connect to your data source, you generally have no choice but to build a connector yourself, or hire another company to build one for you.
This is much harder and more complicated than just using a pre-built visualization, and it’s best to just use a pre-built visualization if one exists. However, in situations where there’s no choice, custom integrations are valuable.
The one advantage of a custom integration is that you can build it exactly how you want it. You have complete control over the integration and how it works, which some companies see as a valuable advantage.
How can I upgrade my data connection strategy?
With better knowledge about the options that exist, businesses can start to plan out their general data integration solution. They can upgrade and modernize their data connectors so that they don’t need to keep updating their data manually.
Figure out data integrations
The first step in modernizing a data connection strategy is replacing older, manual workflows and systems with modern data integrations.
If you already use a modern BI tool, then the process should be pretty easy. Most modern BI tools have some sort of app store or connector database where you can browse and access their available pre-built integrations.
In some cases, there may be complications. You might need to access admin credentials for the tool you want to connect to, or navigate their API documentation to get API keys.
If you don’t use a modern BI tool, then the first step is to replace your legacy, outdated BI tool with something more effective. If you want to modernize your data connections, you have to modernize every part of your data connection strategy, even your BI tool.
If you use a legacy or niche tool, it might be harder for you to find a pre-built integration for your data. In that case, you might have to build a custom integration. Often, you can reach out to your vendor to see if they have any resources that can help you to accomplish that.
Replace legacy tools
One of the biggest obstacles that prevent businesses from connecting their business tools is the tools themselves. Often, businesses that are struggling to access their data are fighting with legacy business tools that aren’t up to modern standards.
To build an effective data connection strategy, businesses need to replace their legacy or niche tools where they can. The larger and more market-leading a tool is, the more likely it is that pre-built integrations already exist between that tool and your BI system.
Connecting to legacy tools in this way is much more difficult, and in some cases, it’s completely impossible. Even if integrations do exist, they’re going to be clunkier, less user-friendly, and more prone to errors than integrations with more popular tools.
Consider cloud-based solutions
One major problem with legacy tools is that many of them are exclusively on-premise solutions, which makes it very hard for cloud-based tools to access the data they contain. Businesses can solve this problem by moving exclusively to cloud-based tools.
Cloud-based tools don’t live on your own computers and servers. Instead, they live on remote, third-party servers that you can access through the Internet. Cloud-based tools are much easier to access than on-premise tools, since they can be accessed from anywhere with an Internet connection.
Data integrations are also much easier between cloud-based tools. If you’re having problems connecting your data and you primarily have on-premise tools, you should consider replacing them with cloud-based tools.
Often, vendors offer a data transfer service where you can switch from the on-premise version of the tool to the cloud-based one. This is generally a better solution than replacing an on-premise tool entirely.
Data integration—bringing real-time data success
Data integrations are much more valuable than previous, manual data connection strategies. They can update data automatically and in real time. This allows businesses to track their metrics exactly and see problems as soon as they occur.
Businesses that are struggling to connect their data in an efficient, modern way should rethink the strategies that they’re currently using. With a modern data connection strategy with data integrations at the center, it’s much easier to make decisions and drive insight.
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