How to Choose a Futureproof Data Integration Solution
It seems there is no longer a “typical IT landscape” among today’s enterprises. It’s a constantly changing world, as systems are routinely extended to include trading platforms, external data sources, and edge applications that serve to improve the customer experience.
Most companies today are operating with a mix of cloud, hybrid cloud, and on-premise solutions. Many continue to run their most mission critical operations on mainframe and IBM i computers, respected and appreciated for their high security and scalability, but not built to integrate with modern distributed systems.
Enterprise data integration has taken on strategic importance. The sudden popularity of cloud data platforms like Databricks, Snowflake, Amazon Redshift, Cloudera, and Azure Synapse has accelerated the need for powerful data integration tools that can deliver large volumes of information from transactional applications to the cloud reliably, at scale, and in real time.
The old days of running overnight ETL (extract, transform, load) batch jobs are over. That simply doesn’t deliver the immediate results that today’s enterprises require. Perhaps even more importantly, it lacks the flexibility necessary to adapt to the needs that arise as the corporate IT landscape and customer requirements constantly evolves.
The new paradigm is dynamic and fluid. It’s about delivering data to business users quickly, wherever they may need it. To operate effectively in this new landscape, businesses must think in terms of future-proofing their data integration solutions.
Adding New Sources and Targets
Just as the value of a network is a function of the number of nodes in the network, the value of an integration solution is a function of its capacity to quickly and easily add new data sources and targets.
Today’s organizations are constantly innovating. That might be something as simple as adding a new application to the IT landscape, or as complex as acquiring a competitor and incorporating their information systems into the parent company. In either case, there’s usually some kind of data integration involved. To complicate matters further, it’s highly likely that any resulting integration solutions will change over time.
In the old world, each major change to the IT landscape might call for a distinct project involving custom code, extensive QA testing, and a go-live cutover scheduled during off-peak times. In today’s rapidly changing environments, that approach no longer a viable way of doing business. Organizations need the capacity to quickly and easily add data sources and targets to their integration landscape, without the need to launch a major new IT initiative.
The best enterprise data integration tools will be capable of connecting with a range of different sources and targets, including mainframe and IBM i systems. Mainframe and IBM i data is inherently challenging because it defies the standard used by most modern distributed computing systems.
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Read this eBook to discover 10 key features to help you choose a vendor that offers both software and an approach that can grow and change with your organization.
Real-time Integration with Change Data Capture (CDC)
As noted earlier, the old practice of batch-mode integration simply no longer works. Today’s enterprises need real-time or near real-time performance, depending on the specific application. Timing matters.
Consider, for example, the challenge that credit card companies face in detecting fraudulent transactions. AI algorithms are trained to detect anomalies. These can range from identifying transactions that originate from a country known to be a common source of fraud, to cross-referencing transaction amounts and locations to look for common patterns that may be suspicious.
It does very little good, however, to spot a fraudulent transaction after it has already been processed. That’s where real-time integration makes a difference. The same is true of systems that monitor trading exchanges, ATM transactions, telecommunications network outages, suspicious network traffic, and more. Real-time visibility to data is a competitive advantage.
Perhaps more importantly, the converse is true; when information is delayed, it brings less value to the business. In today’s world, real-time integration is no longer optional.
Easy Deployment in New Environments
The best data integration tools enable simple, rapid deployment, without the need for specialized skills. Deployment should be resource-efficient and easily targeted to fit your use cases.
This includes the capacity to deploy your integration solution to new environments, without the need to redevelop or re-design your streaming data pipelines. The integration software you choose should insulate your organization from the disruption that might otherwise occur as your IT landscape evolves. Changes to your data sources and targets should not require coding, tuning, or redevelopment effort. Redeployment of applications to the cloud, likewise, should be achievable without major disruption to your integration design.
Bulletproof Reliability and Scale
Not all integration software is created equal. Low-cost solutions may perform well when transaction volumes are low but can become bottlenecks as volumes increase. Look for software that can scale up effectively as your company’s needs expand. Your data integration tools should accommodate growing volumes of data, an increasing number of users, and sharp spikes in usage during times of peak demands. As you shop for the right data integration software, ask vendors how they deliver both predictable performance and scalability.
Reliability also means being resilient when something goes wrong. A network outage, even if it’s just momentary, can create risk that some data may not be delivered to its intended destination. The best enterprise data integration tools have built-in resiliency, with guaranteed delivery and data integrity. That means every record gets delivered as intended, with no duplicates for dropped transactions.
Precisely Connect helps you future-proof your data integration. Connect works with on-premise systems, legacy mainframes, cloud-based SaaS applications, and next-gen cloud and data platforms. It provides flexibility, scalability, and bulletproof reliability, all in a single enterprise-grade data integration solution.
As you look toward future-proofing your organization’s data integration solution, we urge you to consider a checklist approach to evaluating vendors and products. Read the eBook Buyers Guide and Checklist for Data Integration to discover 10 key features to help you choose a vendor that offers both software and an approach that can grow and change with your organization.