The digital world of business continues to open up new and exciting opportunities as advancements in technology and communication continue. Over the last several decades, advances in technology have broadened the horizon of what is truly possible when it comes to starting and running a business. As dependence on the digital age continues to grow, data is becoming more and more important to companies that want to be taken seriously.
While this is nothing new, and data has always been one of the most valuable resources that a business can own, managing that data has always presented a challenge. As a business grows, so also does the amount of data that it needs to steward and utilize. Data is a valuable resource that promotes analytics and helps drive data-driven decisions that can steer businesses clear of failure. Without proper data analytics, there are a whole lot of problems and limitations that could face a company.
The problem is that as data grows, so also does the workload to understand and use it. This can become expensive and requires data teams to work hard to accomplish. One of the most fundamental aspects of managing your data is data integration. Data integration is a crucial step in helping to get data where it needs to be so that it can be used effectively.
If you have wanted to find out more about data integration, here is everything you need to know and some tips that will help you in this process.
What Exactly is Data Integration?
Data integration may sound like taking data from one source and moving it to another, and to some degree, that is correct. However, data integration is a little more complicated and takes the process one step further. Data aggregation is the collection of data into one centralized location. However, this is also one of the very first problems that plagued the digital world with data silos.
Data silos were aggregates of data that were either impossible to access or overly complicated to use. Data integration is the integration of data into one centralized location in a usable, uniform fashion. This means that it’s not only important for data to simply be in one centralized location, it needs to be formatted and accessible.
In the past, the most effective answer to a silo of data was the data warehouse. This provided companies with a way of moving data that had been created from disparate sources into one centralized location. However, as time has gone on, the same problems that faced siloed data are now facing data that has been moved into warehouses or databases.
While tools like ETL and ELT have been used to solve the problem of data silos, so now there are tools to help companies actually integrate their data in one useful location. This process utilizes APIs to consolidate data from disparate sources into one centralized location. Those sources could be everything from SaaS tools to data warehouses or databases.
Pick The Data Integration Tool That’s Right For You
Data integration is something that you have to take seriously, and there are a plethora of tools to help data teams overcome these challenges. When it comes to finding out what tools you need to use, taking in the needs of your team is important. For example, if you have a smaller data team, then incorporating tools like debt Cloud into your data stack might be necessary.
Data integration can take a lot of time and effort, and for smaller teams, using tools in their data stack that help them leverage their time for success is paramount. The needs of every company are different, and some companies have the capacity for large data teams while others are making do with small ones. Create your data stack to reflect the needs of your business at the stage that it’s at, with tools that allow you to scale as necessary.
Reverse ETL Can Help Integrate and Enrich Data
When it comes to methods that can help improve data integration, ETL and ELT have always been traditional choices. These methods take data from disparate sources, centralize it, and, depending on whether it’s ETL or ELT, transform the data inside or outside of the data warehouse. This transformed data is then uniformed and ready for use.
Reverse ETL is a new concept that takes data from a centralized location and pushes it back out to cloud-based applications. This helps push data back into the tools that run a business. This puts valuable data hands of the people who need it, and it actively enriches the data as it is used and then returned to the warehouse.
Conclusion
Data integration is a vital part of the data process. With the right tools in your data stack and the right methods that fit the needs of your team, this is something that your business can accomplish.