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Data migration is almost universally dreaded by IT professionals undertaking complex, application-level consolidation or renewal projects. A recent survey conducted by Celona among telecom IT professionals shows that 93% of them were fearful of application-level migration. This might seem a surprisingly high number, but, unfortunately, there are sound reasons for this level of unease. According to Bloor Research, over 80% of data migration projects are not delivered on time or to budget. Bloors Phil Howard explains that research has revealed that Forbes 2,000 companies already spend at least $5 bn every year on migrations, and yet cost overruns average 30% and time overruns average 41%.

You might ask how this is possible? The answer is largely due to the fact that data migration is still not regarded as a valued skill and practice in its own right, but is treated as the final hurdle in a complex projectan afterthought once the functionality has been developed. At a recent British Computer Society (BCS) meeting, BTs CIO, Phil Dance, bemoaned this fact. Data migration is the single biggest thing that kills you, he warned. You spend lots of money and effort on building functionality, but then you dont spend the effort on moving the data across, and now moving data isnt a once-in-a-career event, its continuous. And its even worse than that because now were a 24x7 company, we have no time to do it in.

Getting it Right
So what makes one migration work where another fails to get out of the box? What ensures one comes in on budget, while another is massively overspent? Well, a successful migration is founded on getting three things rightpeople, process, and technology. Getting any one or more of these three wrong will destabilize the entire project. This doesnt sound too difficult, does it? Get the right experience, select a good method, then develop or buy a tool to deliver the data for you. But the problem is that large migrations are extremely complex on a variety of levels and the sheer scale of them soon leads to challenges.

Lets consider one of these three key success factorsmigration technology. Analyzing different migration projects reveals that there are five main types of data migration. However, it is unlikely that any one of these will entirely fit all the requirements of a complex project. In other words, the chances are that any program of complex transformation will require a range of approaches to be delivered, as a single project may move through a number of approaches over time or even combine approaches in parallel.

For example, an enterprise might initially decide to go with a dont migrate approach in order to get a new customer service up and running without any delays. Some information may then be synchronised with existing systems (eg, revenues written back to the old accounts receivable system). However, following the launch and trial with new customers, the business may need existing customers who take up the new service to be migrated with their old service information on an event-driven basis. Then, after the new systems have stabilised, the business might decide that incremental or even bulk-load strategies should be used to migrate more customers to the new systems, while at the same time continuing to migrate individual customers when they order a new service.

A complex project may require multiple data migration approaches to be used at different times or in a combination, in order to deliver the results needed by the business. However, data migration tools, whether proprietary or third party, have tended to be built to deliver a particular type of data migration. For example, although they have been used for other types of migration, extract-transfer-load tools (ETL) are designed to bulk load data warehouses. Since most proprietary and third party tools are designed specifically to handle migration in a certain way, they are often not able to accommodate business changes that impact the project, or handle the scenario where the business requires more than one data migration approach to be used. Delivering a complex application migration requires flexibility in the data migration tool used, as it is not always possible to predict how things are going to change during the course of the project, or exactly which approaches will be needed at the start of the project.

In response to the demand for flexible, multi-purpose tools, a new generation of data migration tools is emerging.

Progressive migration tools are one of the third-generation of third-party tools coming in the market. They employ a flexible strategy for application-level data migration, enabling different migration approaches to be used during the course of the project, or in combination. The flexibility inherent in progressive migration tools means they support both project and business change, and deliver a lower risk, faster and business-driven migration. Key benefits of progressive migration include:

• Flexibility: Migration approaches are not cemented at the start of the program and the tool is flexible enough to cope with change
• Business-driven: The business remains in control, deciding which data is moved and when
• Lower risk: Progressive migration minimises the risk of failure
• Faster time-to-value: Progressive migration supports multiple migration approaches which means value from the target systems can be seen earlier
• Accelerated return on investment (RoI): From earlier delivery of new revenues and faster consolidation of legacy systems, as well as by reducing project risk and costly overruns, lowering rework costs (by minimising errors and focusing effort on business priorities), and because a single tool can be used to support all migration approaches required by the business.

Progressive migration delivers against one of the three pillars of a successful migration, but it is also essential that the other two pillars (people and process) are not neglected.

Paul Hollingsworth
maildqindia@cybermedia.co.in
The author is working with Celona Technology

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