Introduction

From the Editor

Welcome to the CBR Data Quality Management zone, brought to you in association with Experian.

Here you'll find a wealth of information on the latest challenges around data quality, and how modern technologies and approaches can help you and your organisation to overcome them.

First up you'll find a video interview between myself and Experian Data Management Director, Colin Rickard, in which he explains what is meant by data quality management, and whether companies can really measure the cost or opportunity cost of poor data quality. There is also discussion of the desirability of treating data as a strategic asset; the role of the latest technologies in enabling data migration projects; and how companies are now finally able to achieve that long-sought goal: the Single Customer View .

You'll also see there are a number of on-topic white papers for your perusal, and coming soon, three CBR articles that will comprise a Data Quality Management Special Report. So check back soon to view those, as well as to keep an eye on the latest data quality news via Experian's Twitter feed, below.

Jason Stamper, CBR editor.



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A CBR Data Quality Management Special Report

Understanding data quality management

An introduction to the topic of data quality management, looking at its origins, as well as its role in the modern enterprise. It will also look in some detail at the cost implications of poor data quality, and ask how organisations can put a monetary value on their data quality issues.



In search of the Single Customer View

Getting a single view of the customer has been a challenge for most companies for many years. But now, in the era of multi-channel collaboration, social networks and cloud computing, it may be harder than ever to achieve. However, in this article CBR will look at the latest technologies and approaches that might just help organisations to get there.



Data migration: no easy task?

A recent study by Bloor Research put the failure rate for Data Migration projects at 38 per cent. But what are the underlying causes for this staggering failure rate? CBR looks at the challenges of data migration – a hot topic given for example the end of Microsoft support for Windows XP in 2014 as well as cloud, mobile commerce, M&A's and other initiatives that often require some sort of data movement. The article will also ask how organisations can avoid the most common data migration pitfalls.



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Experian Twitter stream (@ExperianQAS_UK)

Experian white papers

  • Data ownership within governance: getting it right

    Data governance is a quality control discipline that covers the acquisition, management, storage and usage of information or data within a business, with the objective of maximising the value of the organisation's data assets. In layman's terms, this means getting your data and related processes in order, so that the business can maximise value from it.

    Read whitepaper

  • Data Migration discussion paper – Improve the success of your Data Migration project

    A recent study by Bloor Research put the failure rate for Data Migration projects at 38 per cent. This is hardly surprising given the underlying issues that can cause projects to fail are often not addressed.

    Read whitepaper

  • Build a successful business case for Single Customer View

    It's clear that UK businesses are aware that they need to create a Single Customer View (SCV) if they are to thrive. However, as the Experian research profiled in this whitepaper shows, this is where the clarity ends.

    Read whitepaper

  • The data revolution: liberating lost budgets

    Recent analyst reports have not made for good reading for those looking for signs of recovery in IT budgets, but as this Experian white paper shows, it is not all bad news.

    Read whitepaper

  • Enabling efficiency through Data Governance: a phased approach

    This paper discusses how adopting data governance through a phased approach can help you understand these underlying causes and introduce efficient solutions that improve data accuracy and quality.

    Read whitepaper