Topic "Data Quality"

DevOps for Data

InformationWeek’s Lisa Morgan just made the call – data specialists need to get some DevOps religion. DevOps, which is attaining almost religious status within many technology-driven organizations, is about one simple yet effective idea: it’s better to have consistent cadence of deliverables moving through the pipeline, versus unpredictable spurts of development. Developers, known to work... 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

Data Quality and Governance: An Informatica World 2017 Preview

Here we are. Just a few short days away from Informatica World 2017. If you haven’t registered yet, I encourage you to consider coming out and joining us for the most informative data event that you’ll attend all year. And it’s in the heart of San Francisco! If you have registered, perhaps you’re starting to... more

Data Quality: Self-Service Advancements for a Hybrid World

Last week, my colleagues and I joined together to give you a sneak-peek at the latest updates to Data Quality, PowerCenter, and Data Integration Hub with version 10.2. If you missed the webinar, I’d encourage you to take a moment and watch the replay. We showcased the latest advancements and how they will help you with some... more

Consistent, Curated Data Though Hub-based Data Quality and Enrichment

Data fragmentation and poor quality data are significant challenges for large organizations around the world.  The old computing adage of “garbage in, garbage out” is as true now as it has ever been and inconsistencies between data processing done in separate, parallel point-to-point integrations feeding different systems done on a project basis over time can... more