A data integration strategy is essential for success in hybrid data environments
As your business grows the volume and complexity of your data is likely to increase at exponential rates. So if you’re currently having trouble relying on your data and turning it into something meaningful, imagine how challenging these processes could become several years in the future.
Trusting the accuracy of your data is even more difficult when working with hybrid data environments. Even if you have complete confidence that your on-premise data is trustworthy and accurate, your cloud-based data probably doesn’t live up to those same standards.
The importance of a data integration strategy
Failing to create an integration strategy that manages both on-premise and cloud-based data can lead to costly and devastating mistakes. Consider the case of the Office Max mailing that listed a customer’s name, followed by “Daughter Killed in a Car Crash” right within the address line.
Unfortunately, the recipient’s daughter had recently passed away in an accident, making this story even more troubling. Who was to blame for this inappropriate data? While the company pointed out that it received the information from a third-party broker, it was ultimately Office Max’s responsibility to ensure that all their incoming data was properly analyzed and cleansed before being used.
Even if your organization doesn’t commit a headline-grabbing mistake like this one, failing to put a data integration strategy in place can contribute to lower efficiency levels throughout your organization. When you work with untrustworthy data, your team is forced to double and triple check its accuracy. Customers may also not feel confident in the data you initially present, which means your employees have to spend valuable time reassuring them that the data is actually correct.
This cycle leads to lost productivity, diminished customer satisfaction levels and lower revenues.
Components of a data integration strategy
Implementing a data integration strategy empowers your team members to react more quickly and accurately. A strong data integration strategy carries out several functions, including:
• Managing the lifecycle of the data
• Architecting the flow of the data
• Establishing how the data will be maintained over time
Data integration strategies for a hybrid data environment must be nimble enough to integrate and accommodate both on-premise and cloud-based data in a wide variety of formats.
Data must also reach various applications quickly so your business leaders can react to changing information and shifting market conditions as they happen. One critical way to encourage fast reaction times is to implement a strategy with massive data scalability (MDS). MDS allows you to process your data in parallel, significantly reducing time spent handling substantial workloads.
As vital as speed is, your data integration strategy must also be flexible enough to support multiple platforms, simple enough to integrate into your existing processes and easy enough for your team members to quickly understand and adopt it.
One of the overlooked aspects of a robust data integration strategy involves determining when to archive or dispose of old data. Rather than holding on to everything “just in case,” organizations should use their data integration strategy to eliminate outdated data that unnecessarily stretches resources and increases operational costs.
Data integration strategy solutions
A market leader in integration strategy, IBM offers a range of solutions that empower organizations to reduce risk and improve efficiency while operating within a hybrid data environment. These solutions include:
- IBM InfoSphere Information Server for Data Integration
- IBM InfoSphere Data Replication
- IBM InfoSphere Federation Server
- IBM InfoSphere Optim
To explore how you can achieve success from your own hybrid-data integration strategy, please explore the approaches spelled out in this informational IBM Analytics resource.
Learn more about data integration by downloading our e-book or connecting with an IBM expert today.