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What’s the Difference Between Live Data and Replicated Data?

Published
  • April 06 2000, 1:00am EDT

A business associate of mine did very well when the company he was with went public. "Worth millions" is the phrase that comes to mind. He needed something to do with his money, so he opened a substantial account, million-dollar minimum, with one of the big name brokerage firms. He’s a very active investor, and sometimes we trade stock tips and war stories. Last week he was complaining about his account. It seems that all the online information he gets is a day old. But he found a way to get around this problem. He set up a shadow account in Yahoo where he can get up-to-the-minute information.

When I pointed out the irony of having to use a Yahoo service to overcome the shortcomings of his "special" brokerage account, he became a little agitated. Seeing a great opportunity to needle him (I don’t get many), I pressed on. "Aren’t you one of their elite customers?" "Don’t you pay a hefty management fee?" "Shouldn’t you at least get the same information that I get from my tiny E*Trade account?" "How can you trust your money to a company that can’t master simple technology?" By the time I finished, steam was coming out of his ears. He swore that he would get real-time information or close the account.

Why was the data he was getting old? He was looking at replicated data. What’s the difference between live data and replicated data? For a brokerage firm, the answer is the loss of a multimillion dollar account and probably others. The data accessible by the customers is only refreshed periodically (usually every 24 hours), so if the customer happens to check his account before the replication, he is looking at old data. This is a common problem in all traditional businesses; corporate information typically lives in incompatible silos. The brokerage firm that my friend uses is an IMS and UNIX shop. The trading systems are UNIX-based, and the customer information and back-office systems are IMS based – virtually incompatible systems. In order to get its data on the Web, the brokerage firm built a replicated database to feed the customer Web site. I’m sure they made a significant investment in this solution, but I’m not sure they accomplished exactly what they intended – day- old information, an angry customer and the loss of a million-dollar account.

This brick-and-mortar company can’t become E*Trade. They can’t scrap their current infrastructure and build a new one. The investment is too huge. They have to find a way to leverage their existing data and infrastructure to provide the same level of information that the new Web-based competitors can provide. That means easy access to real-time information. Because of the risk of losing customers, they need to accomplish this quickly.

The key to providing real-time data lies in the production day, in accessing the existing production data with no impact on performance. A few years ago it would have been impossible. Today there is a new class of products that will address these data-centric applications – e-data engines. They have the ability to give applications such as customer service Web sites direct access to multiple data sources without effecting the production applications. E-data engines can quickly solve problems such as day-old data and turn years of legacy data and incompatibilities into a corporate asset.

These established companies need to respond quickly to the threats posed by new Internet services. Using traditional solutions won’t work, but the simple addition of an e-data engine can quickly put them light years ahead. E-data engines are quick to implement and cost a fraction of what it would cost for a traditional solution requiring programmers and hardware. With an e-data engine they’ll be up and running in no time and be able to respond quickly to customer needs.

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