In RPA, the ability to integrate with third-party applications is the key to achieving maximum functionality. However, integration with the database layer is not as simple as connecting to it from an RPA tool. Database integration can pose many challenges, such as information security, that your business should be aware of. In this blog, we will cover the recommended practices when automating database interactions in RPA.
Beware of Database Integrity
The core strength of RPA tools is that they can automate processes at the user interface layer. This ensures that any data rules or controls you have implemented through your systems can be maintained when automation is introduced. Using RPA tools to directly interact with a database could lead to compromising your data stores due to the bypassing of rules implemented in your user interface (such as validation or formatting of collected information).
So, while RPA tools have the ability to make direct changes to the database layer, we recommend that they only be used via a user interface. This way, the automation will execute database-related tasks just like a human would, ensuring that data stores are kept away from risky interactions.
Risk-Assess Your Integration
There are cases in which direct access to a database might be required, and they are as follows. If your business lacks a user interface for interacting with data, there might be no other way to access or update the database. Another case is if your business has a user interface, but experiences slow turnaround times due to functional latency. In this case, only if the data is in a read-only format, do we advocate directly accessing the database layer. The RPA tool can then be used to read in items from database and circumvent the slow user interface. In either of these cases, it is important to risk-assess the work and ensure that the integration is validated by experienced developers.
Select the Right RPA Tool
When a direct integration is warranted, the variation in RPA tool connectivity can make a difference. Many database languages and systems exist, such as SQL, DQL, Oracle, SAP Microsoft Access, and Microsoft Excel. Each of these systems requires different forms of integration to achieve full connectivity. Therefore, it is ideal to select an RPA tool that can connect well with multiple systems, especially one that matches the existing systems of the business. You will find a minute lag in querying a data item can be greatly amplified over time if the database is under constant use.
Database systems are prevalent in business applications. While it may seem attractive to directly hook them up to an RPA solution, caution should be exercised. Symphony advocates that the integrity of your business’s data should be prioritized. That is why direct access from an RPA tool should only be implemented as a last resort. If you want expert advice on developing RPA solutions and selecting an RPA tool, the Symphony team has wide range of implementation experience to offer. Learn more about the technical aspects of RPA through other blogs in our Technical Blog Series.
This is part 9 of a 22 part blog series by the leading experts at Symphony Ventures. It addresses how to choose the right RPA tools for your business needs. Drawing from our global team’s extensive knowledge in automation consulting, implementation, and managed services across a range of diverse industries, we’ve drilled into the technical criteria to consider when selecting which RPA software best enables your company’s digital operation strategy. Read part 8, How Sustainable RPA Design Can Pay Dividends Down the Road