How to Choose a Futureproof Data Integration Solution

Key takeaways:

• Quickly adapt to market changes by easily adding new data sources and targets, ensuring your IT landscape evolves at the pace of your business.
• Gain a competitive edge with real-time data integration, crucial for time-sensitive decisions and actions in fraud detection and customer interactions.
• Deploy effortlessly across any environment with solutions that require no special coding, keeping your operations agile and responsive to new opportunities.
• Ensure your business grows without limits with scalable and reliable integration solutions that guarantee data integrity, even during peak demand.

A “typical IT landscape” is quickly becoming a thing of the past 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 operate with a mix of cloud, hybrid cloud, and on-premises 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.

Whatever your approach may be, enterprise data integration has taken on strategic importance. The sudden popularity of cloud data platforms like Databricks, Snowflake, Amazon Redshift, Amazon RDS, Confluent Cloud, 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 evolve.

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, you need to think in terms of future-proofing your data integration solutions.

Let’s explore five key capabilities that ensure your data integration solution will be ready to keep up in a constantly evolving environment.

1. 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 your IT landscape, or as complex as acquiring a competitor and incorporating their information systems into your company. In either case, there’s usually some kind of data integration involved. To complicate matters further, any resulting integration solutions will likely change over time.

In the old world, each major change to the IT landscape might call for a distinct project involving custom code, extensive quality assurance testing, and a go-live cutover scheduled during off-peak times.

Now, times have changed – rapidly. That approach is no longer a viable way of doing business. It’s essential to have the capacity to quickly and easily add data sources and targets to your integration landscape, without needing 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.

2. Real-time Integration with Change Data Capture (CDC)

As noted earlier, the old practice of batch-mode integration simply is no longer enough. 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. Artificial intelligence (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’s 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 of 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.

3. 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 ability to:

• deploy your integration solution to new environments, without the need to redevelop or re-design your streaming data pipelines
• insulate your organization from the disruption that might otherwise occur as your IT landscape evolves
• make changes to your data sources and targets – no coding, tuning, or redevelopment required.

Redeployment of applications to the cloud, likewise, should be achievable without major disruption to your integration design.

4. 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.

That’s what makes it so important to 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
• sharp spikes in usage during times of peak demand

As you shop for the right data integration software, ask vendors how they deliver both reliable, predictable performance and scalability.

Reliability also means being resilient when something goes wrong. Even a momentary network outage can risk some data not being 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.

5. Integrated data catalog for metadata support

As you build out your IT ecosystem, it is important to leverage tools that have the capabilities to support forward-looking use cases. A notable capability that achieves this is the data catalog. A data catalog is a core component of data governance, providing a go-to knowledge base of data for users across an enterprise.

A well-integrated data catalog supports the extensive discovery, access, use, and sharing of both technical and business metadata – automating and improving your data integration and operations tasks. It synthesizes all the metadata around your organization’s data assets and arranges the information into a simple, easy-to-understand format.

Additional data governance capabilities to look for include those that support governance mandates – like data quality, data lineage, and policy enforcement – while handling data for meeting specific use cases, including master data management.

 Your Next Steps

It’s time to future-proof your data integration today so you’re ready to tackle whatever comes tomorrow.

You need flexibility, scalability, and bulletproof reliability, all in a single enterprise-grade data integration solution that works with on-premise systems, legacy mainframes, cloud-based SaaS applications, and next-gen cloud and data platforms. You make it all possible with Precisely Data Integration Solutions.

Want to learn more? Read the eBook Buyers Guide and Checklist for Data Integration for a straightforward guide to the 10 key features to know about in a data integration solution. It provides the details you need to know about these capabilities – and the most important questions to ask prospective vendors.