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Not Your Usual Business Rules for Data Quality
Every business rule is a mission statement in miniature. Every good rule says something meaningful about your organization – where you are today, what direction you’re headed, where you want to be. But...
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Econometrics and Infonomics: A Tariff Story
A recent call from a sales colleague prompted me to write this post. His client asked us to give them guidance on how our solutions and data management practices in general can help combat the effect...
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What’s the Most Challenging Part of AI? The Answer in 2019 May Surprise You
I travel a lot for work, and one of the most rewarding parts of travel is meeting with customers and listening to their stories. Very often I’ll hear a story that offers particular insight into the...
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Getting Application Modernization Right with Informatica Cloud Application...
Why App/API Integration and Data Quality Matter When You’re Trying to Avoid Code, Load and Explode Co-authored with Ruma Sanyal, Director, Hybrid Integration Platform and iPaaS. Application...
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Data Quality Is Central to All Data Integration Projects
When doing some research for this article I came across the following quote from TDWI in 2006: “Profiling, data quality, and data integration are three business practices that go together like bread,...
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Informatica Named a Magic Quadrant Leader Again—For The 13th Time
Gartner just published its 2020 Magic Quadrant for Data Quality Solutions, recognizing Informatica as a Leader for the thirteenth time. As someone who has worked for Informatica on every Data Quality...
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Data Quality Is Key for Effective Crisis Response
The COVID-19 pandemic has had a dramatic impact on society worldwide. The emotional and economic damage will be felt for a long time. And the crisis is still evolving, with some countries opening up...
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What is Data Profiling and Why Profile Your Data?
Data profiling is the process for assessing the quality and structure of data sources so you have a complete, 100-percent-accurate picture of your data. Data profiling verifies that data columns are...
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Data Quality for Everyone, Everywhere
A series of blogs about the importance and the value of consistent, comprehensive, and pervasive approach to data quality Poor data quality costs businesses millions of dollars every year. Depending...
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Why Data Quality Does Not Extend To Everyone, Everywhere Today
Welcome back to part two of my blog series on Data Quality for Everyone, Everywhere—let’s jump straight in. (If you missed Part 1, you can find it here.) If your organization is like most, you know...
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How to Improve Data Quality with Data Enrichment
Some people already know everything they need to know about their customers – for everyone else, there’s data enrichment. In today’s digital economy, knowing how to deliver a positive customer...
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Seven Metadata Management Best Practices Every Successful Data Leader Must Know
Companies are accelerating digital transformation for varied business reasons – to drive innovation, build new business and customer engagement models, and enhance operational efficiencies through...
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The importance of high-quality data requires constant vigilance
First in a two-part blog series about monitoring data quality performance using data quality metrics. Organizational data quality management is often introduced as a reaction to an acute issue or...
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The importance of high-quality data requires constant vigilance: Dimensions...
The second in a two-part series about monitoring data quality performance using data quality metrics. Welcome back to part 2 of my series about the importance of high-quality data and how it...
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