Going mobile with your data? Don’t think you can forget data quality. In fact, data quality takes on a new importance when you’re dealing with enterprise mobility, warns David Akka, head of Magic Software’s UK branch.
“In an enterprise mobility project, we typically have the same challenge of presenting information from multiple systems to the user on a single screen, but mobile brings other challenges as well,” writes Akka in a recent Enterprise Apps Tech column. “For example, typing on a small touchscreen increases the chance that critical data may be misspelled (increasing the chance of duplicating customer records); and users are also far less likely to search multiple records, as they get frustrated faster on mobile.”
What surprised Akka, and prompted his blog post, is that he found that a major automotive industry company is outsourcing data quality to an external agency — despite the fact that data quality could easily be added into the integration workflow.
It’s been said before, but it bears repeating: Data quality is not a one-time project. Actually, it’s an on-going challenge, a point Akka makes well by citing a few telling statistics:
Akka points out that data standards, types and quality differ across systems.
The business impact of this is real and extends beyond mobile initiatives, of course. Specifically, data quality problems can make it difficult to measure the profitability of a product or a customer’s lifetime value, he writes, adding that it can also thwart efforts to upsell or cross-sell products.
Akka explains a bit about the nuts and bolts of data quality. This might be of interest to business users or leaders who are uncertain about the specific meaning of “data quality” and how IT typically resolves duplicates and other issues.
But his ultimate point is that you need to shift away from a data quality process that requires a lot of manual intervention:
”Just as our enterprise integration needs a smart platform that can follow business logic between systems, and enterprise mobility needs to be able to work natively across multiple channels and ecosystems from a single source, data quality also needs a smart solution that can automatically cross-check customer data across multiple systems.”
He mentions early in the post that one way to achieve this is through master data management, or MDM — not to be confused with mobile device management. He outlines some specific capabilities, but generally, coupling a mature data integration platform with master data management as a discipline — and a tool — will get you there.
You might also look into how a mobile application development platform can assist with integration and the related data problems. Obviously, mobile application development platforms are useful for developing mobile apps, but they can also help solve integration. As this recent vendor piece explains it, these platforms basically act as middleware that helps you develop integration points via SOAP or REST APIs — in much the same way cloud integration platforms handle SaaS integration.
For a more detailed analysis, you can read the 2013 Gartner Mobile Application Development Magic Quadrant Report, which I found available for free download on SAP’s site.
Loraine Lawson is a veteran technology reporter and blogger. She currently writes the Integration blog for IT Business Edge, which covers all aspects of integration technology, including data governance and best practices. She has also covered IT/Business Alignment and IT Security for IT Business Edge. Before becoming a freelance writer, Lawson worked at TechRepublic as a site editor and writer, covering mobile, IT management, IT security and other technology trends. Previously, she was a webmaster at the Kentucky Transportation Cabinet and a newspaper journalist. Follow Lawson at Google+ and on Twitter