20 Encounters of the Information Management Kind – #7 Data Conversion Strategies is Where Quality Counts

20 Encounters of the Information Management Kind – #7 Data Conversion Strategies is Where Quality Counts

Jun 17, 2013 by

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I don’t believe you can commit to the success of a data conversion without addressing quality (or lack thereof). Do you agree? If so, then why are there so many conversion projects that just move data from one place to another?

 

How Can You Ensure the Readiness of Your Data During Data Migration?

How Can You Ensure the Readiness of Your Data During Data Migration?

Jun 14, 2013 by

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Are you embarking on a data migration in the near future? If so, there is one nagging question that will loom across every stage leading up to the final moment of truth as your data finally lands in the target system:

“Will the migrated data be able to support our business functions post-migration?”

 

Interviews, HR and Hiring Data Scientists

Interviews, HR and Hiring Data Scientists

Jun 13, 2013 by

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What makes a great data scientist? It’s an interesting question and, to be sure, an increasingly important one now that that we’ve entered the era of Big Data.

 

An Issue with Reporting Data Quality Issues

An Issue with Reporting Data Quality Issues

Jun 12, 2013 by

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An organization’s perspective on data quality is often revealed by its data auditing practices. Some organizations practice data quality ignorance by not performing data audits, assuming that if they don’t check it or hear anyone screaming about it, their data quality must be good enough.

 

Ideas for Addressing Customer Classification

Ideas for Addressing Customer Classification

Jun 11, 2013 by

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Last time we started to look at methods used in setting product prices, and I asked whether knowledge of customer type would contribute to the determination of a “fair” price for an item that might change in relation to customer type.

 

20 Encounters of the Information Management Kind – #6 Converting History! Does it Make Sense?

20 Encounters of the Information Management Kind – #6 Converting History! Does it Make Sense?

Jun 10, 2013 by

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There are two cases, that I can think of, where you may have to consider whether to convert history in a data warehouse. They are:

 

Introducing a New Data Quality Dimension: Irrelevance

Introducing a New Data Quality Dimension: Irrelevance

Jun 07, 2013 by

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Do you want to know what one of the single largest causes of bad data is?

Irrelevant data.

Irrelevant data has no value or place within your business, yet for many reasons it is still being maintained (badly).

 

On Data and the Gender Gap

On Data and the Gender Gap

Jun 06, 2013 by

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Sheryl Sandberg’s new book has, as expected, ignited a debate over women in the workplace. Sandberg contends that many women don’t negotiate very well, and this inability is largely responsible for “the gender gap.” 

 

The Fallacy of Defect Prevention

The Fallacy of Defect Prevention

Jun 05, 2013 by

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One of my least favorite phrases in the data quality industry is “getting data right the first time, every time.” It’s not that I disagree with the premise of defect prevention. Even though it’s impossible to truly prevent every defect before it happens, defect prevention is highly recommended because the more control enforced where data originates, the better the overall quality will be for enterprise information.

 

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