Despite the fact that the importance of data is widely recognized among company executives, there is a gap between this recognition and the number of organizations that are leveraging data to empower business decisions. To close this gap, organizations are investing in data management practices to establish trust and control of their data.
An effective data management strategy is good for your business. As organizations today rely on their data to help drive business initiatives, the quality of that information is growing increasingly important. But you probably already knew that. It turns out that data professionals spend a lot of time talking about data in terms of its accuracy and a lot less time talking about its accessibility and readiness. While the importance of accurate data is undeniable, organizations should understand that having accurate data is only a benefit if you can access that information when it’s needed.
Let’s face it, depending on your institution’s resources and how you go about it, credit reporting can be a huge pain! Whether you provide consumer data to one or several Credit Reporting Agencies (CRAs), whether or not you use a third party to submit data, and whether you test data proactively or reactively, (or not at all) dealing with bureau rejects, data monitoring, and disputes can require significant time and resources.
It is important for companies to comply with the Office of Foreign Assets Control (OFAC) regulations. Failure to do so can result in fines and even imprisonment. Experian Data Quality offers an OFAC-compliant software called ISTwatch, which allows companies to search and match names against a number of compliance and global watch lists.
So you’re tasked with your organization’s next big data migration. Maybe you’re moving to a new CRM system. Maybe you’ve just acquired another company and need to integrate their data into your system. Whatever the reason, data migrations are critical processes that many businesses go through. The continuing explosion in the volume of data businesses collect, store and use suggests that the trend of most companies engaging in some data migration project isn’t letting up anytime soon. According to a recent data migration study, 91% of companies engage in data migration projects.
No matter what industry you work in, what your job title is, or what your responsibilities are, it is almost a guarantee that you rely on data in some way, shape or form at least once a day; and sometimes you might not even know it!
Data is absolutely everywhere, and it’s quickly becoming the lifeblood of most organizations.
The real question is – do you use it to your advantage? Think about it for a second….
Businesses talk a great deal about being data-driven. Yet, using data for strategic purposes can often prove to be more challenging than it would first appear. Organizations today are at the center of a data dilemma, plagued by inaccurate and unstandardized data, information that is scattered across disparate systems, and a lack of defined processes and skilled employees. Yet, business users are demanding access to data with greater urgency than ever before.
It’s 8:30 in the morning on Day 3 of the MDM & Data Governance conference and Aaron Zornes, Chief Research Officer of The MDM Institute, is about to introduce a panel of three experts who will address an intimate room of 100 or so attendees.
The Data Governance and Information Quality (DGIQ) Conference and Dataversity took their talents to sunny San Diego this week. DGIQ looks at the latest trends and practices used by the leaders in the data space and how they apply strategies around data governance and data quality. This event had a heavy focus on the emergence of data governance and regulatory issues companies are facing in regards to their own data as well as the importance of understanding the integrity and quality of their data moving forward to help drive the bottom line.
In the world of data management, there is a lot of terminology that is used interchangeably. For example: validation and verification or fuzzy matching and identity resolution; these are similar terms that are widely used in our ecosystem. Data quality and data governance are two examples of terms that are not synonyms, but are often confused, and with good reason. These two terms are symbiotic, meaning they are interdependent on each other. You don’t really want to do one without the other.