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Most Informatica Cloud customers use it to integrate Salesforce.com CRM with on-premise ERP or finance apps, says Daniel Niemann, VP of business development for the service, while a few are doing cloud-to-cloud integrations and others on-premise to on-premise.

Mastering integration

But Niemann insists that this is more than just a point integration tool located in the most convenient environment for cloud apps. He believes that, just as SaaS applications such as Salesforce.com have allowed business units in corporations to acquire functionality independent of the IT department, Informatica Cloud will help business analysts – who typically design information architectures before handing them over to the IT department to implement – master their integration challenges by themselves.

“With a typical integration project, a business analyst would decide what fields have to go from one app to the other, and the changes that need to happen to that data, and they would describe all this in Excel,” he explains. “And they would then hand that over to some IT guy who would recreate that Excel spreadsheet in middleware.

“So with Informatica Cloud we’ve built a user experience in an integration product that the business analyst guy can use to actually put his integration into production,” Niemann says. This is not motivated by a desire to grant business analysts self-determination, he adds; it is rather the fact that their time costs less than that of middleware experts. 

DataFlux’s Fisher says that components of his company’s new platform were designed to be used by so-called ‘business users’, i.e. non-IT experts. “We’ve done a number of things such as reporting and dashboarding that are designed to help the business user understand the IT infrastructure,” he says.

"We have seen a shift of the responsibility for data management from IT to the business user"
Tony Fisher, DataFlux

This has been motivated by what Fisher described as “a shift of the responsibility for data management from IT to the business user. What we see now is that the business user is having a very active role in technology decisions, especially around data.”

What Fisher is referring to is by far the most important shift currently under way in the field of data management – much more significant than system design or vendor consolidation. This is the slowly developing recognition that the business must take ownership of and responsibility for the quality and accuracy of data. 

Data governance

“The vast majority of data management enquiries I field from my clients are not about technology,” says Forrester’s Karel. “They’re about the soft stuff: how do we organise ourselves, how do we build a business case, how do we engage the business, how do we define return on investment, how do we decide roles and responsibilities. This is what my clients are feeling pain around; this is data governance.”

The term data governance describes the best practices for handling data that organisations must adopt if they are to derive the most value from it, and minimise the risk to which they are exposed in doing so. It is, Karel says, “an incredibly immature set of practices”.

“Those organisations that have done it well have done it in a very targeted fashion, not enterprise-wide data governance because the problem is too great,” he explains. “If you aim to govern the 20% of the data that impacts 80% of your processes and operations, that’s a great start.”

Businesses seeking to solve deep-rooted data quality problems that have undermined their long-term IT investments must begin by sorting out whose responsibility it is to maintain which data, Karel says. Decisions about technology follow long after.

“All these vendors are tools vendors, so absolutely they are going to evangelise about the tools that support the data governance processes,” he says. “But the tools are not solving the problem. They are simply enabling a data governance process that must be designed and owned by the organisations themselves.”

So what does that mean for the industry? Will the gradual adoption and maturing of data governance lead to the anticipated MDM sales, or will customers discover that, with discipline and best practice, they can make do with traditional data integration and data quality tools? 

“That depends on the business objectives of each company,” says Karel. “For some organisations with complex environments, data governance programmes may absolutely lead to the development of a strategy that would recommend the use of MDM technologies.

“But for other organisations, where their master data requirements are really focused on enabling a trusted view in a targeted data warehousing environment or in a CRM application, data integration and data quality technologies may be all that they require.”