TDWI Upside - Where Data Means Business

How to Bypass the Infrastructure Roadblock on the Path to Digital Transformation

Modern data integration and management capabilities are must-haves for digital transformation, but it's important for IT leaders to choose the right infrastructure strategy.

Digital transformation isn't a luxury. The capacity to use technology to deliver products and services in new ways is what defines winners in the data-driven economy. However, many companies encounter a major roadblock on the path to digital transformation: an aging data integration and management infrastructure.

For Further Reading:

Data Management Best Practices for Cloud and Hybrid Architectures

In the Middle of DatA Integration Is AI

Q&A: What's Ahead for the Data Landscape

Digital transformation requires the ability to securely share and apply massive amounts of data generated by an ever-increasing number of devices and applications. The data is incredibly valuable because the insights it contains are what make new products, services, and buying experiences possible.

The ability to effectively integrate and manage data is a precursor to digital transformation, but too many businesses are being left behind, and they are starting to realize it. A recent PwC survey found that businesses are less confident in their ability to benefit from technology now than they were back in 2015.

Legacy Technology as a Roadblock

What's behind this lack of confidence? Legacy technology as a roadblock to digital transformation is one explanation. Aging, on-premises integration infrastructures slow down the pace of change. Cloud applications are driving the demand for digital transformation, but legacy technologies hold many companies back.

Technologies such as enterprise service bus/electronic data interchange (ESB/EDI), managed file transfers (MFTs), and middleware solutions weren't designed to integrate massive amounts of data arriving in a range of formats from new cloud-based sources. To find the path to digital transformation, companies need integration infrastructures that are also cloud-based and capable of handling all patterns of data from a variety of sources.

Do-It-Yourself (DIY) Solutions Come Up Short

Integration-platform-as-a-service (iPaaS) solutions are one option for IT organizations looking for ways to integrate data from existing systems and cloud applications. However, they are a short-term fix; they are built on the same aging legacy technologies that hold companies back.

As currently defined by industry analysts, iPaaS platforms provide developers with the tools to create DIY integration workarounds. The problem is that new data sources come online constantly, and building point-to-point integration solutions takes a considerable amount of time and money, consuming IT resources that could be more profitably focused on digital transformation.

Companies are rightly excited about new data sources such as the Internet of Things, so they allocate resources to integration projects involving iPaaS platforms. However, enterprises that want to disrupt industries by hiring data scientists to derive insights from data are finding instead that their highly paid, hard-to-find data scientists spend most of their time as "data janitors."

Integration projects take longer than expected, which delays getting new digital business models and processes to market. Enterprises find themselves bogged down in tasks related to data security and privacy compliance as enterprise data regulations evolve and increase. Instead of capitalizing on their data, companies using iPaaS are forever playing catch-up and coming up short.

A Better Option: Managed Services

Enterprises have another option: partnering with an expert to handle data integration and management on a managed services basis. It fits a trend in which companies seek outside expertise for functions that aren't in their core competency. The right partner can deliver quality data on a cloud-based, vendor-neutral platform that doesn't restrict users to a specific application ecosystem.

By offloading data integration and management functions, enterprises can access the infrastructure they need to take in data from diverse sources today and can flexibly manage new sources and patterns of data tomorrow. With the right partner, they can confidently outsource concerns about evolving data security threats and increasingly complex data privacy regulations.

A managed services approach frees in-house developers from endless DIY integration projects. It allows data scientists to focus on innovation instead of data cleanup tasks. Depending on the partner's capabilities, companies that take a managed services approach can even start benefiting from moving data integration and management to a purpose-built platform on the cloud now without disrupting business operations.

When contemplating leveraging a managed services provider (MSP), be aware of key trade-offs or allowances required to realize the corresponding benefits. The best MSPs treat cloud providers as highly differentiated, not as commodities. However, MSPs should also explicitly help customers choose where, and to what degree, they will accept the risk of lock-in in return for ease of integration, agility, and faster time to value.

MSPs with strong cloud-native skills and expertise in DevOps -- and with experience migrating customers from traditional operations models toward greater automation in conjunction with continuous integration and continuous delivery (CI/CD) -- are best positioned to help customers operate efficiently over the long term.

Trusting Your Vendor

Your enterprise will be entrusting your integration and data management needs to an IT services vendor. This is a significant step for two work streams that are so vitally important to today's market and to digital transformation strategies. You must make sure (that is, adequately vet) that the vendor has the processes, people, and technology to manage the enterprise's functions effectively, scale with the company, and meet the required service-level agreements (SLAs) better than internal teams and processes can. Also, determine if your vendor can handle incidents, outages, and change management with proper controls and respond as quickly as internal teams -- be sure such promises are part of your SLA as well.

A Final Word

Effective data integration and management is a necessary precondition of digital transformation, and digital transformation is needed to be successful in the data-driven economy. Companies must get past their outdated-infrastructure roadblock. A partnership with a data integration and management expert can be the bypass route they need.

About the Author

Don Terry is the vice president of North American sales at Liaison Technologies. He is a 25-year industry software sales veteran who believes that data is the new currency in today’s digital enterprise. In this pivotal role, Don helps companies realize and unlock the value of their data throughout the value chain. Don has held leadership roles at Splunk, Oracle, EMC, and Pivotal Software.


TDWI Membership

Accelerate Your Projects,
and Your Career

TDWI Members have access to exclusive research reports, publications, communities and training.

Individual, Student, & Team memberships available.