Integrating data from various sources can be a challenging task, particularly if the sources are disparate. Typically, the process includes various steps including data mapping, creating data flows, running different transformations, and loading it into a data warehouse for analytics, reporting and business intelligence (BI) initiatives.

There are two ways organizations can integrate their data for various business activities. One is a tedious, time-consuming, and error-prone manual process, while the other is what is commonly known in the industry as automated data integration. With continuously increasing volume, variety and velocity of incoming data, self-service BI and analytics require that the data be processed efficiently. This is where automated data integration software come in.

In other words, automation integration is the way forward.

Benefits Of Automated Data Integration

Let us now discuss the benefits of automated data integration.

Operational Efficiency

When tedious, repetitive routine tasks and processes associated with ingesting, synchronizing, and replicating data are automated, organizations end up increasing their operational efficiency significantly. Development teams will need not be dedicated to writing codes and configuring complex tools, instead, they will have more time to spend on data analysis and driving innovation.

Human, IT, And Development Costs

While manually integrating data may come with some specific benefits, it certainly does have a lot of costs that make the organizations question its feasibility. In the short term, it might appear as if manually integrating data saves costs. However, when all the factors and costs that go into setting up a manual data integration system are accounted for, automated data integration software still comes out as the more cost-effective option. By automating the process, organizations save not only time but also costs associated with building, training, and retaining IT and development teams, maintaining the data pipelines, investing in the infrastructure, etc.

Productivity and Business Intelligence

One of the major benefits of automating the entire data integration process is increased productivity. As briefly discussed earlier, when dealing with large volumes of data coming in at very high speed, manually integrating data will be tedious, time-consuming, and prone to all kinds of errors there can be. This will mean that the data teams will almost always be busy manipulating data and have no time to spend on analysis. This is far from ideal since insights are crucial to driving innovation. With automation integration, not only is the room for errors reduced significantly, but data teams will also be left with time to analyze data, draw insights, and drive innovation.

Scalability

When integrating data, one particularly important factor to consider is scalability. In 2020, it was estimated that over the next three years, more data will be created than the data that has been created over the last thirty years. Moreover, more than three times the data created in the last five years will be created in the next five years. All this tells us is that the amount of data is increasing rapidly and there is no end to it. This is where scalability comes in. Data integration software offer solutions that are truly scalable. Again, this is a major benefit of automated data integration, and a tough nut to crack if the integration solution is manual.

Better Decision-Making

Writing code to integrate data leaves a lot of room for errors, and errors can easily lead to ineffective decision-making. In a fast-paced business environment, decisions not only need to be made fast, but they must also be based on accurate data. With integration software, most tasks and processes can be automated thereby reducing room for errors.

Adaptability, Reliability, and Reusability

Organizations looking to implement an integration solution must ensure that the integrated data is compatible with the latest technologies of the industry like IoT, ML, cloud, etc. Integration software offer native connectors for a wide range of data sources and destinations for seamless data integration. Automating this process will further improve the efficiency. Furthermore, with automated data integration software, businesses get an efficient and reliable method to record, update, and track data accurately.

Using data integration software, routine tasks can be automated easily. Once the workflows are created, they can be orchestrated to be run automatically either in response to a trigger or on a set schedule. This way, a data pipeline that is once created becomes reusable with automation.

Conclusion

It is worthwhile to note that automation applied to an inefficient process will magnify the inefficiency. Likewise, automation applied to an efficient operation will magnify the efficiency. Therefore, before automating the data pipelines, it is critical to ensure that all the dataflows and workflows are designed efficiently.