Companies gain more and more information by collecting data. But simply collecting data is not a guarantee for success. The challenge is to transform collected data into data insights. The good news: artificial intelligence (AI) and machine learning (ML), in terms of learning from data and automating repetitive tasks, can support you in your data management activities.
Today, access to valuable data is a superpower. But just having a lot of data is not enough. In one of our most recent eBooks, CDQ data experts from the Competence Center Corporate Data Quality (CC CDQ) explain how to turn data into business value using a simple model: the Data Value Formula.
How many customers does your business have? This is a simple question, but not one that's always easy to answer accurately. Do customer accounts with multiple addresses count only once, or are they listed multiple times in your CRM system?
Many are unware that their business partner master data entail information of natural persons. If this data stays unrecognized, GDPR-compliant processing of that information is impossible. Simultaneously, the risk of possible fees and the possibility of damaging the company image increases.
Invoice fraud is a growing threat to business. In our Data Sharing Community, we use our cloud platform to rate bank accounts' trustworthiness and alert our members to new fraud attempts.
Many corporates have already invested heavily in centralizing data across the company, engineering resources. They have created one place that can be used by all, is updated by all and refer to it as their ‘single source of truth’. And this is the point where it gets tricky. How is data maintained, enriched, and most of all used?
