Big data is not the biggest change in the IT industry but data usage. To become more data driven and to succeed with their digital transformation, organizations are using their data more extensively to improve their business and decision processes. Unfortunately, it is hard for current data delivery systems to support new styles of data usage, such as data science, real-time data streaming analytics, and managing heavy data ingestion loads. This session discusses a real big-data-ready data…

Data virtualization is being adopted by more and more organization for different use cases, such as 360 degrees customer views, logical data warehouse, democratizing data, and self-service BI. The effect is that knowledge about this agile data integration technology is available on how to use it effectively and efficiently. In this session lessons learned, tips and tricks, do's and don'ts, and guidelines are discussed. And what are the biggest pitfalls? In short, the expertise gathered from…

As the data landscape becomes more complex with many new data sources, and data spread across data centres, cloud storage and multiple types of data store, the challenge of governing and integrating data gets progressively harder. The question is what can we do about it? This session looks at data fabric and data catalogs and how you can use them to build trusted re-usable data assets across a distributed data landscape.

Target Audience: CDO, Data Engineer, CIO, Data Scientist, Data Architect,…

Metadata is a long-time favourite at conferences. However, most attempts to implement real metadata solutions have stumbled. Recent data quality and integrity issues, particularly in data lakes, have brought the topic to the fore again, often under the guise of data catalogues. But the focus remains largely technological. Only by reframing metadata as context-setting information and positioning it in a model of information, knowledge, and meaning for the business can we successfully implement…