How to manage data integration during an acquisition

Innovation is crucial for business growth. IT teams hold a lot of innovation power, as effective use of emerging technologies is crucial for informed decision-making and is key to staying a beat ahead of the competition. But adopting modern-day, cutting-edge technology is only as good as the data that feeds it. Cloud-based analytics, generative AI, predictive analytics, and more innovative technologies will fall flat if not run on real-time, representative data sets.

Organizations need effective data integration and to embrace a hybrid IT environment that allows them to quickly access and leverage all their data—whether stored on mainframes or in the cloud.

Easily said—but let’s throw in a curveball, something that happens in business all the time: a merger or acquisition (M&A). How does a company approach data integration and management when in the throes of an M&A?

Organizations may feel the need to consolidate some of the new data they’ve acquired to better manage and glean straightforward insights, but this is not the case. A hybrid cloud approach means data storage is scalable and accessible, so that more data is an asset—not a detriment. The ability to store, manage, control and replicate data between the mainframe, on-premise software, and public cloud platforms in real time will allow businesses to tap into innovation, no matter how large the data set or how quickly it needs to be integrated.

Data synergy

For many navigating the M&A process, managing data can be overwhelming and must be properly managed or else run the risk of unorganized and displaced data.

Organizations need to integrate on-premises systems, like mainframes, with cloud platforms to best manage influxes of data and stay ahead of the curve amongst competitors. With a wide range of varying data, the ability to leverage the reliability, data integrity, and scalability of the mainframe with the accessibility and collaborative benefits of the cloud is the best solution for overall data visibility and control. For this to be possible, data integration tools must also allow access to and replicate data from intricate mainframes, preserving the value of historical data.

Implementing hybrid-cloud solutions also dismantles data silos that have plagued businesses for years.

Data synchronization

Another wrinkle when managing data during an M&A is making sense of the ever-expanding volume of data—data that’s come at IT all at once. The more data the better in terms of informed decision-making, but only if it is up-to-date and synchronized across systems.

Implementing real-time synchronization capabilities into business’s storage systems is crucial to ensure that data reflects their operational realities within a rapidly changing economic landscape. Without real-time updates, IT teams could run the risk of making misinformed decisions based on outdated data, which can cost the business money.

With real-time data syncing, data integration tools can run historical, on-premises data for cloud-based AI and ML analytics, which are especially important datasets that are often not utilized, especially when a company is dealing with competing priorities in an acquisition. The use of AI will only continue to rise, making this capability crucial for decision-making.

Software development

Software development is another crucial reason why well-managed and up-to-date data is crucial. This is especially true for quality assurance (QA) testing of companies’ applications.

When organizations leverage DevOps practices in their software development processes, testing applications in isolated environments is no longer sufficient. Teams must integrate up-to-date data into the testing process to replicate real-world scenarios, which ensures that software functions as expected under various conditions.

Using realistic data sets during testing allows teams to validate application performance, security, and user experience more effectively. It also enables proactive issue identification, leading to faster bug detection, reduced development time, and an overall enhancement of application performance.

Integrating extensive datasets during an M&A can be quite intimidating, but leveraging solutions—like those from Rocket Software—that enable businesses to efficiently store, oversee, govern, and duplicate data across mainframe systems, on-site infrastructure, and public cloud platforms instantly is the answer to unlocking innovation during an acquisition.

Data Management