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Data is one of the most valuable resources that modern businesses can steward and represents one of its most significant challenges. While the digital age has afforded many advancements to modern businesses in ways that they can creatively interact with their customer and improve customer experience, it’s also brought on the challenge of data. 

The simple truth is that data is created with every interaction and the digital world itself is as complicated as it is fine-tuned. Finding better ways to aggregate, integrate, enrich, and use data is something that modern companies have to take seriously if they want to stay relevant. Because of the variety of disparate sources that data can be created from inside one company, data integration is a vital part of the process. 

If you have been wanting to find the best tools for data integration, here is everything you need to know!

Data integration is the process of moving data that is created in disparate sources to one centralized location. Aggregating data into one centralized location has a lot of advantages and this can streamline a company’s view of their customers which gives rich analytical insight. The reason this can be so hard is that various cloud-based apps, databases, and warehouses can all hold data that relates to each other but need to be combined. 

By utilizing data integration, companies can start to see robust 360 views of their customers, and their journeys and gain powerful insights into their companies that wouldn’t be an option otherwise. Being able to gain a stronger view of their customer gives companies the perfect opportunity to make data-driven decisions that will improve customer experience. The core value of data integration is that it helps improve a company’s data over time. 

Not only that but successful data integration can lead to smoother collaborations and easier workflows overall. Without good data integration tools, a company can be seriously handicapped in their efforts to understand their customer’s needs and how to improve their company. 

One of the oldest forms of data integration, and yet still one of the most effective, is ETL or ELT. These tools take data from disparate sources and integrate them into a data warehouse where that data becomes a source of truth across a company. The two methods are composed of the three same steps, however, they have unique orders. 

ETL stands for Extract (the process of pulling data from disparate sources), Translate (turning disparate data into a uniformed format), and Load (moving that formatted data into a centralized location - typically a data warehouse). ELT uses the exact same steps, however, it focuses on loading the data into a data warehouse before transforming it to a uniform format. 

iPaaS, or Integration Platform as a Service, is a field of services dedicated to helping bring a tangible solution for data integration to businesses. iPaaS has the advantage of being diverse as they come in various shapes and sizes and offer the benefit of customization that can be profitable for businesses that want to outsource this process. 

In general, these tools operate on a trigger response that sends data to one of their platforms where further steps are taken for data integration. 

A more modern take on data integration and the traditional ETL process, reverse ETL provides a powerful tool for both data integration and data enrichment to take place at the same time. This process, as its name implies, moves data out of a centralized location and back out to the tools that use it. Reverse ETL has the benefit of helping businesses utilize their sources of truth in real, practical ways that improve the quality of their data.

The problem that can face centralized locations of data like warehouses or databases, is that the data found there can be difficult to access. The data warehouse was created as a solution to the problematic data silo, however, these same problems can begin to affect the warehouse. Reverse ETL provides a unique solution in that it moves data out to disparate sources, where it can be enriched, and then brought back to a centralized source of truth.

Lastly, CDPs or Customer Data Platforms are focused on giving companies a tool that focuses on data collection. Data collection is the act of gathering data into measurable information in a systematic way. This is similar to data integration, however, they are not the best tools for the actual work of data integration as it focuses on collecting data from disparate sources into one centralized source of truth. CDPs don’t just focus on moving data between sources as is the case with integration; instead, CDPs are much more useful for marketing teams to build profiles of their customers.

Finding the right data integration tool will look different for every company. The good news is that there is a variety of options that can help companies reach their goals and achieve data integration. 

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