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30 Jun 2008

dn:Director for data migration and integration

Businesses worldwide spend large sums of money installing, upgrading and enhancing their applications. This work can become over complex, time consuming and expensive and, as a result, the data migration efforts that support them can often be perceived as a subordinate cost.

Too often this view creates an over-simplified and under-funded approach to data migration, which in turn can lead to poor data quality in the target application and underperformance when it’s unveiled to the world.

Managing the quality of your data as a key part of an application migration and/or integration project will pay dividends in terms of ensuring future system performance. It will provide source data that’s fit for purpose and the checks and balances during key parts of the project that will help you steer the whole exercise in on time and on budget.

Data Quality to Maximize Your Return On Application Investment

Accurate data is the raw material that drives better business decisions and maximizes the value of enterprise applications. New application initiatives - such as CRM or ERP deployments or upgrades - will usually need to glean their data from existing systems. As such, your current sources need to be validated before they’re moved so that you avoid starting life in the new application with an incomplete, out of date, redundant, or duplicate data set.

Things to consider before application migration takes place are:

  • Extensive querying of the source system
  • Analysis of a suitably large sample set of source data
  • Full knowledge of how the source systems work
  • Provision and/or review of source system documentation
  • Full knowledge of how the target system works
  • Proper project input from business leaders

The Datanomic Approach - Understand Your Data, Safeguard its Quality

The most effective way of delivering a data migration program is to fully understand the data sources before you create any migration mapping code. This is best achieved by conducting a complete profile and audit of all source data within scope at an early stage.

dn:Director enables you to run all candidate data through a robust profile and audit process, which gives the you complete visibility of the full source data set. This enables you to solve potential data quality issues before they impact your migration/integration work.

dn:Director’s holistic approach to data quality management enables business and technical users to work collaboratively. By providing a simple reporting dashboard for your data quality work, you’re more able to share insights and create better rules for planning, mapping, building and testing the migration process.

Armed with this knowledge, you can be more confident that your decisions are founded on known facts rather than untested assumptions. The risk of late delivery due to new data discoveries is reduced and, most importantly, you can increase your confidence in the data that you deliver to the target system.

Find out more about the market’s leading Data Quality solution today…