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Monthly Archives: January 2015

Solving for the data problem: Making information work for your business

Erin Haselkorn

Erin Haselkorn

January 28, 2015

Data quality

Data is an essential part of any organization today. We rely on it to tell us about our customers, what products we should invest in, how we should adjust our sales and marketing strategies, what new markets to invest in and much more. We have become obsessed with data and the insight it can provide.

However, the information we are often relying on for critical business decisions is flawed. On average, organizations in the U.S. believe 32 percent of their data is inaccurate. That is a 28 percent increase over last year’s figure of 25 percent. When one considers how much data is used across the business, it is easy to see how this high level of inaccuracy can create wide-spread business problems. Many organizations experience consequences such as a poor customer experience, impacts to revenue or efficiency, and much more.

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Top 5 questions for data quality vendors

Erin Haselkorn

Erin Haselkorn

January 12, 2015

Data quality

Many of us today are in the market for data quality solutions. In fact, 89 percent of companies are planning to invest in some sort of data quality solution in the next year, with an average of a half a million dollars in budget. But, some companies are already spending much more. Thirteen percent are spending between two and five million dollars and seven percent are spending over five million dollars.

This high degree of investment is not something that should be taken lightly. Companies need to be sure they are working with the right vendors and selecting solutions that can have a material impact on the quality of data and show a return on investment.

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Avoid a recipe for disaster: Baking and data quality have a lot in common

As a marketer here at Experian Data Quality, I am by no means a technical expert on data quality. However, what do know is that I've found many similarities between data quality and one of my personal passions: baking! Both require pre-planning, solid execution and refinement after the fact.

Here are three tips that you can use when making amazing homemade cookies or implementing a data quality strategy.

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