Data is the big thing in business these days. Big Data. Information that is gathered by the organization, retrieved from a Web service, or collected from social media can create big problems regarding the way your applications perform.

More and more enterprises today are looking to leverage the cloud for all the benefits it brings. But these enterprises fall into three buckets, according to Don Tirsell, vice president of worldwide technical alliances at Informatica.

First, he said, are the born-in-the-cloud software vendors looking to launch an application. “They write the app and get going, but the apps are bottlenecked by on-boarding data,” Tirsell said. “Usually it’s from a legacy system that a cloud service is replacing. But the legacy system often is not being turned off due to an on-premises requirement to pull data back into the system, for such things as reporting.”

Next are the ISVs that have traditionally shipped software that runs on servers in the organization’s data center. But that organization now realizes it has to move to a cloud model. “Healthcare, financial services…the customer base (for ISVs) is bifurcating,” Tirsell said. “The companies that want to sell them cloud services are having trouble getting data” due to governmental or industry regulations.

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Tirsell used the example of a hospitality software package that runs on a PC, even as the industry as a whole wants to go to the cloud. “The ISVs still want to offer additional services to those hotels, such as validating addresses, handling e-mails, offering better reporting. They need to get the data out, but the hotel needs to get the data back.

“The data access challenges are plentiful,” he continued. “There are legacy systems with complex data formats, so managing hierarchies and understanding the data become difficult. Then there are regulations around how transportable the data is, that impact the ability to move to the cloud.”

The third bucket, Tirsell said, is related to analytics. “Because of the volume of data, you need parallel processing, maybe archiving and data compression. We’re seeing the market go to Big Data architectures to process data more easily. The analytics are often bottlenecked by data issues,” he said.