Creating Data Products in a Data Mesh, Data Lake or Lakehouse for Use in Analytics (9-10 June 2022, Stockholm)
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
One of the highest priorities in organisations today is to address the issue of untrusted data which leads to inaccurate predictions, recommendations, reports and dashboards. In order to solve this, many companies are looking at creating a standard data curation process to create trusted data assets and make them available services in an enterprise data marketplace so that it is easy to find, access, share and reuse across the enterprise. This session looks at building an enterprise data marketplace, the key technologies needed and the challenges in operating one.
- The problem of untrusted data
- What’s needed? – Findable, accessible, reusable and trusted ready-made data assets
- Manufacturing ready-made data assets – from data lake to enterprise data marketplace
- What is an enterprise data marketplace? – A new role for a Data Catalog
- What types of data and analytical assets should you expect to see in one?
- How should an enterprise data marketplace function?
- What is needed to operate a data marketplace in terms of people, processes and technologies?
- Why is data virtualisation critical to serving up trusted data assets from a data marketplace
- Maximising reuse by integrating self-service BI tools and Data Science workbenches with the marketplace
Mike Ferguson, Intelligent Business Strategies
Paul Moxon, Denodo
Andy Steed, Big Data LDN