Enterprise DataOps – Curating Trusted Data as a Service from Data Lake to Data Marketplace (25-26 March 2019, Helsinki)
Smart Infrastructure & Smart Applications for the Smart Business – Infrastructure & Application Performance Monitoring
Data Warehouse Automation & Real-time Data – Reducing Time to Value in a Distributed Analytical Environment
This two-day, in-depth seminar is intended for chief data offices, enterprise architects, data architects, master data management professionals, business professionals, database administrators, data integration developers, and compliance managers who are responsible for management and governance of enterprise data.
The seminar takes a detailed look at the business problems caused by poorly managed data including inconsistent identifiers, data names and policies, poor data quality, poor information protection, and piecemeal project oriented approaches to data integration. It also defines the requirements that need to be met for a company to confidently define, manage and share reference data, master data and transactional data across operational and analytic applications and processes both on-premise and in the cloud.
Having understood the requirements, you will learn what should be in a data management strategy and what you need in terms of people, processes, methodologies, and technologies to bring your data under control. In addition we will look at how to introduce governance into different data management disciplines including data naming, enterprise metadata management, data modelling, data relationship discovery, data profiling, data cleaning, data integration, data service (Data-as-a-service) provisioning, reference data management and master data management.
During the seminar we take an in-depth look at the technologies needed in each of these areas as well as best practice methodologies and processes for data governance and master data management.
This seminar is intended for business and IT professionals responsible for enterprise data governance including metadata management, data integration, data quality, master data management and enterprise content management. It assumes that you have an understanding of basic data management principles as well as at least a high level of understanding of the concepts of data migration, data replication, metadata, data warehousing, data modelling, data cleansing, etc.
Attendees will learn how to set up an enterprise data governance program and to determine what technologies they need for enterprise data governance, data integration and master data management (MDM). In addition they will learn when to use certain technologies over others and methodologies to use for metadata management, data integration, and designing and implementing data governance and MDM solutions.