Topic "Data Quality"

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 cloud modernization. The common theme across all these business priorities is the need for trusted data to enable agile, informed decision making. And this trusted data needs to be made... more

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 experience is a significant competitive advantage. Customers expect every interaction with every company to be contextual, relevant, and effortless – every time. Organizations that put... more

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 you have data quality issues everywhere. It’s also very likely that you’re tackling them in an ad hoc way because it’s hard to pinpoint where the problems are... more

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 on which analyst survey you read, the direct cost of poor data quality is between $9.0 million and $15.0 million per year. The business impact... more

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 Magic Quadrant since 2006 (the first year it published), I have seen the data landscape evolve over time. There are now more data users,... more

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, butter, and jam. . . data management professionals and their business counterparts need to coordinate efforts and design projects that integrate all three... more

Getting Application Modernization Right with Informatica Cloud Application Integration and Data Quality

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 modernization is the refactoring, re-purposing, or consolidation of legacy software programming to align more closely with current business needs. As Orbis Research’s Global Application Modernization Services Market 2019... more