Topic "Data Quality"

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

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 on their prices resulting from the U.S. tariffs recently imposed. The current state of uncertainty apparently had them question... more

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 how do you define your rules? How do you work out their logic, agree on their conditions for success? Most importantly, how... more

Value of an Enterprise Intelligent Data Governance Framework

Some challenges The adoption and rollout of Data Governance at an enterprise level is often impeded for several reasons, but commonly it is because the communities of data consumers in the business don’t see the value of engaging with it. Data Governance may be seen as an overhead to the business in terms of time,... more