Clemens is a domain expert in the field of Data Management with a key focus on Master Data Management. Clemens supports customers in the Finance, Retail and Manufacturing sector, meeting with customers at senior level discussing the benefits of Data Quality, Data Governance and MDM and works closely with SAS R&D to ensure customer and market direction input is reflected in on-going software releases.
SAS Intelligent Decisioning enables users to create, test, control versioning and trace analytically driven decisions all in one solution.
SAS Decision Manager enables you to build and test decisions to use in batch processes, real-time web applications or with SAS Event Stream Processing. In this blog, I explain how to use Rulesets in an Event Stream Process project. If you are streaming data using SAS Event Stream Processing and
With SAS Data Preparation and SAS Decision Manager, you can perform out-of-the-box column and row transformations to increase your data quality and build the foundations for data-driven innovation. This blog will discuss how you can leverage SAS Decision Manager to enrich data when preparing it through SAS Data Preparation.
With SAS Data Management, you can setup SAS Data Remediation to manage and correct data issues. SAS Data Remediation allows user- or role-based access to data exceptions. Last time I talked about how to register and use a Data Remediation service. This time we will look at how to use
IT organizations today are constantly challenged to do more with less. Reusing data processing jobs and employing best practices in monitoring the health of your data are proven ways to improve the productivity of data professionals. Dataflux Data Management Studio is a component of both the SAS Data Quality and
With DataFlux Data Management 2.7, the major component of SAS Data Quality and other SAS Data Management solutions, every job has a REST API automatically created once moved to the Data Management Server. This is a great feature and enables us to easily call Data Management jobs from programming languages
For a long time, master data management (MDM) practitioners boasted about their ability to build a 360° view of customers by aggregating and proactively managing information coming from various business applications such as CRM systems, ERP applications, and other operational systems. But was it really a 360° view? What about
