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Mistake #5: No Processes for Managing Dynamic Business & Data Rules
By: Bryn Davies

One of the most prevalent characteristics of a data migration project is the significant extent of continual change that must be dealt with, often late into the programme. This is... Read More


Mistake #4: Delays Because the Target is Undefined
By: Bryn Davies

We often hear from the project stakeholders that "it is too early for the data migration team to start as we have not yet defined the target". What absolute rubbish!... Read More


Mistake #3: Not Adequately Addressing Data Quality
By: Bryn Davies

There is often a lot of hype and a lot of expectation generated in the process of selling the 'new system', both from external and internal parties, as the motivations... Read More


Mistake #2: Not Involving Business Early Enough
By: Bryn Davies

The data in an organisation belongs to the business, and they have to be the ones making the business decisions about it. Coupled with this, in a data migration project... Read More


The Top Five Mistakes in a Data Migration Project
By: Bryn Davies

Having been involved in a number of large-scale data migration projects, InfoBluePrint has come across some common re-occurring themes that have the potential to derail not only the data migration... Read More


How to Build a Glossary for Data Quality Activities
By: Bryn Davies

Before you launch into your data quality initiative, agree on the exact terms you'll be using for the programme. Bryn Davies explains why this is so important and provides a... Read More


The 'springboard' of data quality and data governance stemming from a data migration
By: Interview by Dylan Jones, CEO of Data Quality Pro.

Bryn Davies, Managing Director of InfoBluePrint, discusses the 'springboard' of data quality and data governance stemming from a data migration. Dylan Jones: Thanks for taking time out to talk Bryn. Let's... Read More


Where do you start your typical DQ initiative?
By: Di Joseph

You should start by understanding the quality of the existing data. This is best done by conducting a formal objective Data Assessment. Place a stake in the ground and determine... Read More


How do you go about ensuring that new data collected, from the initial process to the final steps, is of good quality?
By: Di Joseph

Whether the organisation wants to do this is the Million Dollar Question! The short answer to this question is?Continuous Process Improvement across all areas of data collection and usage. This... Read More


How do you go about improving the quality of existing data?
By: Di Joseph

Now this is an interesting question - there are several ways in which to improve the quality because there are several ways in which the data can be defective. Depending... Read More


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